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The European Union, in pursuit of the goal of reducing emissions by at least 55% by 2030 and achieving climate neutrality by 2050, is deploying different actions, with industry decarbonization as a key strategy. However, increasing electricity demand requires an intensification of energy generation from clean technologies, and the energy system's expansion is hindered by renewable generation's climatic dependencies and the imperative for substantial electrical infrastructure investments. Although the transmission grid is expected to grow, flexibility mechanisms and innovative technologies need to be applied to avoid an overwhelming growth. In this context, this paper presents a thorough assessment, conducted within the FLEXINDUSTRIES project, of the flexibility potential across seven energy-intensive industries (automotive industry, biofuel production, polymer manufacturing, steel manufacturing, paper mills, pharmaceutical industry, and cement production). The methodology followed during the analysis entails reviewing the state-of-the-art existing flexibility mechanisms, industries' energy markets engagement, and technical/operational readiness. The results highlight the feasibility of the proposed actions for enabling energy market flexibility through demand-response programs, quantifying energy opportunities, and pinpointing regulatory and technical barriers. [ABSTRACT FROM AUTHOR]

The transition process from fossil fuels to environmentally friendly renewable energy sources carries the risk of creating new environmental damages. Photovoltaic technology represents one of the alternatives with the least risk of harmful environmental impact. However, this technology has two important drawbacks: the significant land occupation for the installation of PV systems and the uncontrollability of production. By constructing floating photovoltaic plants on hydroelectric reservoirs, both of these problems can be reduced to an acceptable level. Some artificial reservoirs, originally built for hydroelectric power plants, have acquired a significant secondary function as recreational areas and fish breeding sites. Therefore, there is justified resistance from the local community to change the existing appearance and purpose of such reservoirs. This paper proposes a completely new concept of integrating the interests of the local community into such objects. In addition to preserving existing uses, the concept also offers new features. This can make the entire system environmentally friendly and sustainable. This paper details the technology behind the construction of floating photovoltaic power plants on artificial reservoirs and emphasizes their various advantages. These benefits include the non-utilization of cultivable land, the ease of assembly and construction, integration into existing power grids, and the potential to address electricity storage issues. For instance, Buško Lake, covering an area of 55.8 km2, may host 2.93 km2 of installed floating photovoltaic (FPV) facilities, enabling a total installed capacity of 240 MW. With an average of 5.5 h of daily sunshine, this totals 2007 annual hours, equivalent to a 55 MW thermal power plant. An analysis showed that, with losses of 18.2%, the average annual production stands at 302 G W h , translating to an annual production value of 18 million € at 60 €/MWh. The integration of this production into an existing hydroelectric power plant featuring an artificial reservoir might boost its output by 91%. The available transmission line capacity of 237 MW is shared between the hydroelectric power plant (HPP) and FPV; hence during the FPV maximum power generation time, the HPP halts its production. HPP Orlovac operates a small number of hours annually at full capacity (1489 h); therefore in combination with the FPV, this number can be increased to 2852 h. This integration maintains the lake's functions in tourism and fishing while expanding its capabilities without environmental harm. [ABSTRACT FROM AUTHOR]

Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade. [ABSTRACT FROM AUTHOR]

With the high proportion of renewable energy sources and power electronic devices accessed in the distribution network, the harmonic pollution problem has become increasingly serious. The traditional centralized harmonic mitigation strategy has difficulty in effectively dealing with these scattered and random harmonics. Therefore, a distributed harmonic mitigation strategy based on the dynamic points incentive of blockchain communities is proposed in this paper. Firstly, a comprehensive voltage sensitivity partitioning method with harmonic weight differentiation is proposed to realize the reasonable partitioning of each control node and controlled node in the distribution network concerning variability in harmonic components and their distribution. Then, a harmonic mitigation strategy based on the dynamic integral excitation of self-learning algorithms is constructed to promote self-organized optimization and active distributed coordinated control of mitigation devices. The strategy ensures that the total harmonic voltage distortion rate of each node meets the requirements by adjusting the partitioned collaboration to realize optimal harmonic mitigation. By setting optimized partitions in different scenarios and conducting simulation verification, the results demonstrate the effectiveness of the strategy in this paper. It stimulates synergy between devices through a dynamic incentive mechanism and significantly reduces the total harmonic voltage distortion rate across various test scenarios, reflecting the adaptability of the harmonic mitigation method presented. [ABSTRACT FROM AUTHOR]

This paper investigates whether renewable energy influences economic growth and happiness. Using panel data from 25 European Union countries for the period 2012–2022, this study employs a panel model for estimation with fixed and random effects, and robust HAC standard errors. According to the research results, in general, the growing share of renewable energy in the energy mix has a positive impact on economic growth and the happiness of citizens. However, detailed research has shown that this effect depends on the type of energy; a significant positive impact was recorded only in solar share energy, wind share energy and economic growth. However, almost all types of renewable energy were included, i.e., biofuel, hydro, solar and other renewable share energy, and all had a significantly positive impact on the level of happiness. The exception was wind share energy, which showed a significant negative impact. The research findings of this paper provide empirical support for promoting renewable energy, which is positive both for economies and the happiness of citizens. It is one of the main aspects of sustainable economic growth. [ABSTRACT FROM AUTHOR]

The integration of renewable generation presents a promising venue for displacing fossil fuels, yet integration remains a challenge. This paper investigates Demand Response (DR) as a means of economically integrating Renewable Energy Resources (RERs). We propose Incentive-Based DR (IBDR) programs, particularly suitable for small customers. The uncertainties in the electricity market price pose a challenge to IBDR programs, which is addressed in this paper through a novel and robust IBDR approach that considers both the electricity market price uncertainties and customer responses to incentives. In this paper, scenarios are simulated premised on the Western Electricity Coordinating Council (WECC) 240-bus system in which coal-fired power plants become inactivated, while the RER contribution increases in the span of one year. The simulation results indicate that the proposed IBDR program mitigates the issues associated with renewable expansion, such as utility benefit loss and market price volatility. In addition, the proposed IBDR effectively manages up to 30% of errors in day-ahead wind forecasts that significantly reduce financial risks linked to IBDR programs. [ABSTRACT FROM AUTHOR]

Aiming at the problem of source-load uncertainty caused by the increasing penetration of renewable energy and the large-scale integration of electric vehicles (EVs) into modern power system, a robust optimal operation scheduling algorithm for regional integrated energy systems (RIESs) with such uncertain situations is urgently needed. Based on this background, aiming at the problem of the irregular charging demand of EV, this paper first proposes an EV charging demand model based on the trip chain theory. Secondly, a multi-RIES optimization operation model including a shared energy storage station (SESS) and integrated demand response (IDR) is established. Aiming at the uncertainty problem of renewable energy, this paper transforms this kind of problem into a dynamic robust optimization with time-varying parameters and proposes an improved robust optimization over time (ROOT) algorithm based on the scenario method and establishes an optimal scheduling mode with the minimum daily operation cost of a multi-regional integrated energy system. Finally, the proposed uncertainty analysis method is verified by an example of multi-RIES. The simulation results show that in the case of the improved ROOT proposed in this paper to solve the robust solution of renewable energy, compared with the traditional charging load demand that regards the EVs as a whole, the EV charging load demand based on the trip chain can reduce the cost of EV charging by 3.5% and the operating cost of the multi-RIES by 11.7%. With the increasing number of EVs, the choice of the starting point of the future EV trip chain is more variable, and the choice of charging methods is more abundant. Therefore, modeling the charging demand of EVs under more complex trip chains is the work that needs to be studied in the future. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids' efficient, stable, and economical operation in their initial stages. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This paper presents a comprehensive review of the state-of-the-art research and developments concerning the flexibility in the operation of low-carbon integrated gas and electricity networks (IGENs) as part of the whole system approach. Methods and solutions to provide and improve flexibility in the mentioned systems are studied and categorized. Flexibility is the system's ability to deal with changes and uncertainties in the network while maintaining an acceptable level of reliability. The presented review underscores the significance of this convergence in facilitating demand-side management, renewable energy integration, and overall system resilience. By highlighting the technical, economic, and regulatory aspects of such integration, this paper aims to guide researchers, policymakers, and industry stakeholders toward effective decision-making and the formulation of comprehensive strategies that align with the decarbonization of energy systems. [ABSTRACT FROM AUTHOR]

Human activities overwhelm our environment with CO2 and other global warming issues. The current electricity landscape necessitates a superior, continuous power supply and addressing such environmental concerns. These issues can be resolved by incorporating renewable energy sources (RESs) into the utility grid. Thus, this paper presents an optimized hybrid fuzzy logic self-tuning PID controller to control the automatic generation control (AGC) of various renewable sources. This controller regulates the frequency deviations of the power system and governs the change in the tie-line load of a multi-area hybrid energy system composed of wind, biomass, and photovoltaic energy sources. MATLAB Simulink software was applied to design and test the system. The PID controller has been tuned using four algorithms, namely, genetic algorithm (GA), pattern search (PS), simulated annealing (SA), and particle swarm optimization (PSO), and we compared the results with the proposed novel optimized PID controller (GA-fuzzy logic self-tuning technique) to validate it. The results show the superiority of the proposed hybrid GA-fuzzy logic self-tuning algorithm over the other algorithms in bringing the power system back to its regular operation. The paper also proposes an operation strategy to lower the utilization of biomass energy in the presence of other renewable energy sources. [ABSTRACT FROM AUTHOR]

This study explored the association between renewable energy uptake and digitalization in the sector by reviewing relevant literature (published 2010–2022), with the aim of identifying the existing utilization of digital technologies within the sector, challenges to adoption, and future prospects. Different search engines (SCOPUS, Web of Science, and Google Scholar) were used to locate relevant papers and documents. The results revealed the high significance of digital technologies in supporting the renewable energy sector, with high costs and security risks representing the key challenges. Most papers reviewed had a positive outlook, but recommended further research and development for effective energy transition and resilient infrastructure. The current drivers of the integration of digital technologies to support the diffusion of renewable energy sources appear to extend beyond energy demand and involve many aspects of sustainability and sustainable development. Compared with previous reviews, this work has unique scope and novelty since it considers the bigger picture of the coupling between digitalization and the renewable energy sector, with a greater focus on critical areas in these two interconnected bodies that need to be addressed. The relatively small sample of relevant papers (69 from 836 hits) located in the literature review confirms the need for more research covering the subject in greater depth. [ABSTRACT FROM AUTHOR]

Due to a rising share of renewable energy sources on the production side and electrification of transport and heating on the consumption side, the efficient management of flexibility in distribution networks is crucial for ensuring optimal operation and utilization of resources. Nowadays, the sensitivity-based approach is mainly used in medium-voltage (MV) networks for regulating voltage profiles with reactive power of distributed energy resources (DER). The main disadvantage of the simplified sensitivity-based method is its inaccuracy in case of a high deviation of the network voltage from the nominal values. Furthermore, it was also noted that despite the fact that the method is well described in the literature, there is a lack of systematic approach to its implementation in real-life applications. Thus, the main objective of this paper is to address this disadvantage and to propose an algorithm designed to calculate required consumer flexibility in near real-time to ensure distribution grid operation within operational criteria. In the first part of the paper, network state, including line loading and node voltages, is assessed to determine distribution network node capacity. By analyzing the sensitivity of network busbars to changes in consumption and production, our algorithm effectively identifies the most efficient nodes and facilitates strategic decision-making for resource allocation. We demonstrate the effectiveness of our approach through simulations of real-world distribution network data, highlighting its ability to enhance network flexibility and improve resource utilization. Leveraging sensitivity coefficients, the algorithm enables flexible consumption and production management across various scenarios, supporting the transition to a more dynamic and efficient power system. [ABSTRACT FROM AUTHOR]

Hydrogen-powered mobility is believed to be crucial in the future, as hydrogen constitutes a promising solution to make up for the non-programmable character of the renewable energy sources. In this context, the hydrogen-fueled internal combustion engine represents one of the suitable technical solutions for the future of sustainable mobility. As a matter of fact, hydrogen engines suffer from limitations in volumetric efficiency due to the very low density of the fuel. Consequently, hydrogen-fueled ICEs can reach sufficient torque and power density only if suitable supercharging solutions are developed. Moreover, gaseous-engine performance can be improved to a great extent if direct injection is applied. In this perspective, a remarkable know-how has been developed in the last two decades on NG engines, which can be successfully exploited in this context. The objective of this paper is twofold. In the first part, a feasibility study has been carried out with reference to a typical 2000cc SI engine by means of 1D simulations. This study was aimed at characterizing the performance on the full load curve with respect to a baseline PFI engine fueled by NG. In this phase, the turbocharging/supercharging device has not been included in the model in order to quantify the attainable benefits in the absence of any limitation coming from the turbocharger. In the second part of this paper, the conversion of a prototype 1400cc direct injection NG engine, running with stoichiometric mixture, to run on a lean hydrogen combustion mode has been investigated via 1D simulations. The matching between engine and turbocharger has been included in the model, and the effects of two different turbomatching choices have been presented and discussed. [ABSTRACT FROM AUTHOR]

A new passivity-based voltage tracker for islanded Direct Current (DC) microgrids is presented in this paper. The proposed design develops a new sufficient condition for passivity-based state feedback with proportional and integral control using the attracting ellipsoid method. In this paper, we consider the time behavior of the extended vector, which completely describes the principle properties of the closed-loop system such as the boundedness of the trajectories within some ellipsoid and the dependence of its "size" on the feedback gains. The next step, which we are realizing in this paper, is the minimization of the attractive ellipsoid by selecting the "best" admissible feedback parameters. Here, it is important to note that the applied feedback is of PD-type (proportional differential) on the system state and I-type (integral) on the output. This is a new construction of the suggested feedback which gives several advantages for a designer. The suggested control is decentralized and uses only the local states; it is cost-effective and avoids the time delays in the communication networks which are needed if centralized control is used. The suggested control is carried out in the bilinear matrix inequality (BMI) framework. Extensive simulation is performed on a test system composed of renewable energy sources, under plug and play (PnP) operations, and uncertainties in distribution lines and loads. The performance of the proposed decentralized voltage controller is compared with that of a voltage tracker present in the literature. The comparison shows the improvements introduced by the proposed control ensure the stability of the dc bus voltage and a quick response under different scenarios of operating conditions. [ABSTRACT FROM AUTHOR]

Low or even zero carbon dioxide emissions will be an essential requirement for energy supplies in the near future. Besides transport and electricity generation, industry is another large carbon emitter. Hydrogen produced by renewable energy provides a flexible way of utilizing that energy. Hydrogen, as an energy carrier, could be stored in a large capacity compared to electricity. In Sweden, hydrogen will be used to replace coal for steel production. This paper discusses how the need for electricity to produce hydrogen will affect the electricity supply and power flow in the Swedish power grid, and whether it will result in increased emissions in other regions. Data of the Swedish system will be used to study the feasibility of implementing the hydrogen system from the power system viewpoint, and discuss the electricity price and emission issues caused by the hydrogen production in different scenarios. This paper concludes that the Swedish power grid is feasible for accommodating the additional electricity capacity requirement of producing green hydrogen for the steel industry. The obtained results could be references for decision makers, investors, and power system operators. [ABSTRACT FROM AUTHOR]

Access to clean energy remains a major issue in developing countries, particularly Sub-Saharan Africa, despite successive policies and the assistance of international institutions or organizations. The United Nations (UN) launched some of the most ambitious initiatives with the Millennium Development Goals and, more recently, the Sustainable Development Goals and Power Africa, a United States (US) government initiative. Sub-Saharan Africa has an important potential in renewable energy for both biogas and solar photovoltaic energy, but they remain underexploited. This paper presents the challenges of access to clean energy in developing countries and the failure of remedial policies mostly based on public–private partnerships (PPPs) in the context of endemic poverty of rural populations. In addition, the development of modern energy technologies remains very limited. Appropriate reforms should be carried out to change the paradigm and allow universal access to clean energy. This paper also addresses the different structural barriers that hinder access to technology in Sub-Saharan Africa and the consequences of access to clean energy in the context of poverty. [ABSTRACT FROM AUTHOR]

The emerging energy transition is particularly described as a move towards a cleaner, lower-carbon system. In the context of the global shift towards sustainable energy sources, this paper reviews the potential and roadmap for hydrogen energy as a crucial component of the clean energy landscape. The primary objective is to present a comprehensive literature overview, illuminating key themes, trends, and research gaps in the scientific discourse concerning hydrogen production and energy policy. This review focuses particularly on specified geographic contexts, with an emphasis on understanding the unique energy policies related to renewable energy in Brazil, Austria, and Germany. Given their distinct social systems and developmental stages, this paper aims to delineate the nuanced approaches these countries adopt in their pursuit of renewable energy and the integration of hydrogen within their energy frameworks. Brazil exhibits vast renewable energy potential, particularly in wind and solar energy sectors, positioning itself for substantial growth in the coming years. Germany showcases a regulatory framework that promotes innovation and technological expansion, reflecting its highly developed social system and commitment to transitioning away from fossil fuels. Austria demonstrates dedication to decarbonization, particularly through the exploration of biomethane for residential heating and cooling. [ABSTRACT FROM AUTHOR]

In city-integrated energy systems containing electric–thermal multi-energy sources, the uncertainty of renewable energy sources and the fluctuation of loads challenge the safe, efficient, economic and stable operation of the integrated energy systems. This paper introduces a novel approach for the operation of a carbon capture plant/CHP with PV accommodation within a city-integrated energy system. The proposed strategy aims to maximize the utilization of photovoltaic (PV) power generation and carbon capture equipment, addressing issues related to small-scale CHP climbing constraints and short-term output regulation. Additionally, this paper presents a multi-timescale optimal scheduling strategy, which effectively addresses deviations caused by PV fluctuations and load changes. This was achieved through a detailed analysis of the CHP climbing constraints, carbon capture equipment operation and real-time characteristics of PV power generation. This paper introduces a fully distributed neural dynamics-based optimization algorithm designed to address multi-timescale optimization challenges. Utilizing rolling cycles, this algorithm computes both day-ahead and real-time scheduling outcomes for urban integrated energy systems. Theoretical analyses and numerical simulations were conducted to validate the precision and efficacy of the proposed model and algorithm. These analyses quantitatively evaluate the scheduling performance of PV power generation and carbon capture CHP systems across various timescales. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

In the European Union, increasing attention is already being paid not only to the development of renewable energy sources, but also to the establishment of solutions to achieve local energy self-sufficiency while increasing the role of citizens in managing the energy they generate. This approach is expected both to have a positive impact on the environment and the reduction of greenhouse gas emissions, and to enhance energy security—both in economic and civic terms by, i.a., combating energy poverty. The development of local energy communities promoted in the EU is supported i.a. by energy cooperatives. These contribute to the efficient harnessing of renewable energy potential in rural and urban-rural areas, and have been developing in Poland for several years now. In their previous studies, the authors of this research paper attempted to verify the generation (number, type and capacity of installed sources) and consumption (energy demand) configurations in which an energy cooperative would be a viable solution for prosumers who might establish it. However, over the past few years, the conditions for prosumers and the method of their accounting with the electricity seller have changed radically in Poland (shift from net metering to net billing). This situation has opened up space for further research and encouraged the authors to revisit the problem of analyzing the viability of establishing energy cooperatives in relation to the rules of operation of individual prosumers. This research was carried out for three scenarios, and the horizon of the analyses conducted and described extends to 2045. The comparative analysis included energy consumers without their own generation sources, prosumers with a photovoltaic generation installation covered by the net billing model, as well as a scenario involving prosumers' cooperation within an energy cooperative, which by law is settled in the net metering model. Conclusions from the research and simulations made it possible to confirm the claim that, despite changes in the rules of prosumer billing, developing energy independence in the energy community formula results in a significant reduction in the cost of purchasing electricity (even several times lower purchase costs in the timeframe analyzed) and can lead to a reduction in the payback time of investments in generation sources even by a factor of two. The results presented in this research paper open up space for further research. The outcomes allow us to assume that energy cooperatives—in the organizational and institutional model in Poland—are a good tool for reducing the phenomenon of energy poverty on a local scale. [ABSTRACT FROM AUTHOR]

This review paper synthesizes the recent advancements in voltage regulation techniques for active distribution networks (ADNs), particularly in contexts with high renewable energy source (RES) penetration, using photovoltaics (PVs) as a highlighted example. It covers a comprehensive analysis of various innovative strategies and optimization algorithms aimed at mitigating voltage fluctuations, optimizing network performance, and integrating smart technologies like smart inverters and energy storage systems (ESSs). The review highlights key developments in decentralized control algorithms, multi-objective optimization techniques, and the integration of advanced technologies such as soft open points (SOPs) to enhance grid stability and efficiency. The paper categorizes these strategies into two main types: analytical methods and computational methods. In conclusion, this review underscores the critical need for advanced analytical and computational methods in the voltage regulation of ADNs with high renewable energy penetration levels, highlighting the potential for significant improvements in grid stability and efficiency. [ABSTRACT FROM AUTHOR]

Offshore wind energy is considered as one of the most promising resources of clean and renewable energy to replace fossil fuels. Additionally, its cost is expected to be lower than onshore wind energy as the technology matures. Offshore wind turbines (OWTs) normally operate in harsh ocean environments, which could impact their structural integrity. Scour erosion around foundations of OWTs can substantially change the overall stiffness of these structures and shorten their lifetime. Currently, there are a limited number of studies on countermeasures and their engineering requirements for decreasing the scouring effect; this is due to their different hydraulic circumstances, such as their stability, reliability, and resistance capacity. To this end, advancements in scour protection measures in the offshore energy sector are evaluated in this paper through a thorough and critical review following the PRISMA systematic literature mapping approach. This includes 68 papers on scour protection and over 30 scour protection designs for various types of wind turbine foundations. Here, we aim to provide an overview of the latest scouring protection measures and their comprehensive assessment, as well as their prospects and future challenges. The findings of this study will provide key insights into scour protection measures for OWTs and will subsequently contribute to the future growth of the offshore renewable energy sector. [ABSTRACT FROM AUTHOR]

Static-voltage stability has become one of the most significant risks faced by large-scale renewable energy integration. However, traditional methods for static-voltage-stability analysis are often overly complex. This paper constructs an equivalent impedance model for renewable energy-integrated distribution power systems, proposing a static-voltage analysis method for renewable energy-integrated distribution power systems based on an impedance model index. This method has been verified to be applicable not only to a renewable energy single-infeed system but also to a multi-infeed system. Furthermore, an analysis is conducted on the influence of the integration capacity, location of renewable energy, and the topology of networks on the impedance model index, indicating that a higher impedance model index corresponds to greater static-voltage-stability margins in the system. Hence, during the planning of renewable energy integration, the plan with the highest impedance model index should be selected. Finally, the accuracy of the analysis method and conclusions in this paper was validated based on the IEEE 14-node system. [ABSTRACT FROM AUTHOR]

The global energy crisis, which began in 2021 due to the extraordinary economic recovery after the pandemic and intensified after Russia's invasion of Ukraine in February 2022, has changed the conditions of energy management, paying more attention to energy efficiency. Natural gas prices have reached record levels and, consequently, so have electricity prices in some markets. Oil prices have reached their highest level since 2008. Higher energy prices have contributed to sharply increased inflation. Households are again becoming interested in buying coal as a source of heat. High energy and gas prices have pushed many families into poverty and forced some factories to cut production or even close. They have also slowed economic growth to the point where some countries are heading for a serious recession. Paradoxically, the negative effects of the energy crisis may accelerate the introduction of cleaner, sustainable, renewable energy such as wind and solar energy. The energy crisis is comparable to the oil crisis of the 1970s, when it contributed to significant advances in energy efficiency. The current crisis has highlighted the importance of investments in renewable energy resources and initiated the process of integrating regional markets, developing energy efficiency and promoting renewable energies. The aim of this article is to comprehensively explore the complex relationship between energy awareness, consumption patterns, and energy efficiency, with a focus on both individual consumers and industries, during the global energy crisis. This paper is based on a literature review, overarching policy documents, energy reports, and other secondary documents. The primary research method was the systematic literature review method, based on which the impact of the global energy crisis on energy efficiency was evaluated. This study emphasizes the diverse influences on energy awareness, ranging from economic factors to consumer preferences and environmental consciousness. The findings of the paper underscore the significant responsibility of industries in contributing to energy-saving efforts and the active role of consumers in the energy market. The responsibility of industries in contributing to energy efficiency is highlighted, with a call for a comprehensive approach that integrates energy-saving criteria into product development and corporate social responsibility. [ABSTRACT FROM AUTHOR]

To advance carbon neutrality policies, many countries are increasingly integrating Renewable Energy Sources (RESs) into their energy mix. However, for harnessing natural energy in power generation, RESs present challenges in output control, potentially leading to power imbalances. Such imbalances, when coupled with an excessive reliance on unpredictable RES, may necessitate the curtailment of grid-integrated renewable generation, halting production despite available capacity. This paper proposes strategies to mitigate the economic and operational efficiency impacts of increased RESs on the power grid. It focuses on the optimal operation of Battery Energy Storage Systems (BESSs) and Power to Gas (P2G) technology, which flexibly converts surplus electricity into hydrogen. By employing Mixed Integer Linear Programming (MILP) for optimization and Stochastic Programming (SP) for the management of the uncertainty of renewable energy output, this paper evaluates the anticipated benefits of BESS and P2G applications. [ABSTRACT FROM AUTHOR]

The application of electrochemical cells as a source unit of electrical energy is rapidly growing—used in electric vehicles and other electric mobility devices, as well as in energy supply systems—as energy storage, often together with renewable energy sources. The key element of such systems is the power electronic converter used for DC energy storage and AC grid interfacing. It should be bidirectional to charge and discharge the battery when it is necessary. Two-stage battery interface converters are the most common; their DC-DC stage controls the battery current and adjusts voltage, but the DC-AC stage (inverter or frontend) controls the current in the grid. The use of unfolding inverters in two-stage battery interfaces can have some advantages. In this case, the DC-DC converter produces half-sinewave pulsating voltages and currents, but the unfolding circuit changes the polarity of the voltages and currents and produces no switching losses. Another trend of modern power electronics is the principle of partial power processing. In this case, power electronic converters deal only with a part of the total power; therefore, losses in such converters are reduced. This paper considers combining unfolding frontends with partial power DC-DC converters that enable the further reduction in losses. In this paper, it is shown that such implementation of the partial power conversion principle in semi-DC-AC systems is really possible based on the real-time matching of the voltage of the partial-power DC-DC converter, battery voltage (which depends on its state of charge) and the rectified instantaneous voltage of the AC grid. [ABSTRACT FROM AUTHOR]

Modern electrical power systems are characterized by a high rate of transient processes, the use of digital monitoring and control systems, and the accumulation of a large amount of technological information. The active integration of renewable energy sources contributes to reducing the inertia of power systems and changing the nature of transient processes. As a result, the effectiveness of emergency control systems decreases. Traditional emergency control systems operate based on the numerical analysis of power system dynamic models. This allows for finding the optimal set of preventive commands (solutions) in the form of disconnections of generating units, consumers, transmission lines, and other primary grid equipment. Thus, the steady-state or transient stability of a power system is provided. After the active integration of renewable sources into power systems, traditional emergency control algorithms became ineffective due to the time delay in finding the optimal set of control actions. Currently, machine learning algorithms are being developed that provide high performance and adaptability. This paper contains a meta-analysis of modern emergency control algorithms for power systems based on machine learning and synchronized phasor measurement data. It describes algorithms for determining disturbances in the power system, selecting control actions to maintain transient and steady-state stability, stability in voltage level, and limiting frequency. This study examines 53 studies piled on the development of a methodology for analyzing the stability of power systems based on ML algorithms. The analysis of the research is carried out in terms of accuracy, computational latency, and data used in training and testing. The most frequently used textual mathematical models of power systems are determined, and the most suitable ML algorithms for use in the operational control circuit of power systems in real time are determined. This paper also provides an analysis of the advantages and disadvantages of existing algorithms, as well as identifies areas for further research. [ABSTRACT FROM AUTHOR]

Reduction or elimination of reliance on traditional fossil fuels and of the emission of greenhouse gases and pollutants into the environment are affecting energy technologies, systems, and applications. In this context, one potential approach to achieving sustainability, decarbonization, and ensuring the energy and economic viability of existing and future energy systems involves adopting one or more renewable sources. The presented paper concentrates on examining the performance of a small-scale hybrid renewable polygeneration system. This system utilizes biogas produced through anaerobic digestion, which is then supplied to an internal combustion engine, along with solar energy converted into electrical energy by photovoltaic modules and wind energy harnessed through a wind turbine. A small-scale user, represented by residential buildings and a zootechnical farm with heating, cooling, and electrical energy demands, serves as the case study. TRNSYS software is employed to design and model the system, considering realistic assumptions about technical aspects and user energy requirements. The investigation involves analyzing the system's operation, considering both energy and economic perspectives. The paper discusses the pros and cons of combining biogas, solar, and wind energy in the proposed hybrid system under the considered case study. Despite non-satisfactory economic profitability without incentives, the proposed system allows one to save significant amounts of primary energy and carbon dioxide equivalent emissions. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) play a crucial role in the global transition towards decarbonization and renewable energy resources (RERs). As EVs gain popularity, this has resulted in various challenges for the power grid, such as an intensified peak-to-valley load differential, causing transformer overloading. Vehicle-to-grid (V2G) technology has emerged as a promising solution due to its controllable charging and discharging capabilities. Mature business schemes can incentivize the development of V2G technology. However, the business schemes of V2G technology are still unclear. Therefore, this paper provides a comprehensive review of the business schemes associated with V2G technology, especially focusing on its feasibility and challenges with respect to the electricity market. In this paper, several business schemes with respect to the electricity market are explored by conducting extensive literature reviews, including peak-to-valley arbitrage, the spot market, demand–response (DR), frequency regulation, voltage regulation, spinning reserve, and black start. Next, application scenarios and real-world use cases of the V2G technology's business schemes are investigated. Furthermore, the challenges faced by the V2G technology's business schemes are assessed by considering the technical, economical, and social aspects. By identifying these challenges, it is important to highlight the existing shortcomings and areas of interest for V2G technology's research and development. This review contributes to a deeper understanding of V2G technology and its implications for the energy sector. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RESs) offer key transformative potential from a societal point of view due to their modularity and ability to generate energy at the local level, allowing for the development of grassroots democratic and participatory initiatives. The paper aims to share insights into the processes of creating RES cooperatives in Poland. One of the first cooperatives to be established in the Upper Silesian region in Poland was the energy cooperative (EC) "Our Energy". This study presents an in-depth empirical analysis of a community-based renewable energy cooperative. The study employed a case study methodology, including a SWOT analysis framework, to describe the research subject and identify its strengths, weaknesses, opportunities, and threats. Key findings indicate that members benefit from stable energy prices and full recovery of the energy produced, and the cooperative is at the forefront of energy-sharing practices that minimize costs through direct transactions with the local municipality. The strategic goals of the EC focus on expanding membership, increasing the number of photovoltaic installations, implementing energy balancing, combating energy poverty, and reducing emissions. Challenges such as financial constraints and a lack of real-time monitoring of energy distribution are acknowledged, and carbon footprint reduction innovations and stakeholder engagement are highlighted as forward-looking approaches. The study highlights the role of cooperatives as a model for community-led sustainable energy initiatives. However, the study acknowledges the limitations of its small sample size, suggesting the need for broader research to understand the impact of collaborative energy on decarbonization. Future research directions are proposed, focusing on the long-term sustainability and socioeconomic impacts of energy cooperatives. This study contributes to the scholarly discourse on renewable energy cooperatives by offering insight into their potential to bridge the gap between energy producers and consumers and support sustainable community development. The main novelty of this paper lies in its detailed examination of a specific renewable energy cooperative, incorporating SWOT analysis, stakeholder perspectives, quantitative assessments, and a forward-thinking approach. This multifaceted analysis contributes to the existing literature on renewable energy initiatives, providing a valuable reference for researchers, policymakers, and practitioners in the field. [ABSTRACT FROM AUTHOR]

ANNs have become a cornerstone in efficiently managing building energy management systems (BEMSs) as they offer advanced capabilities for prediction, control, and optimization. This paper offers a detailed review of recent, significant research in this domain, highlighting the use of ANNs in optimizing key energy systems, such as HVAC systems, domestic water heating (DHW) systems, lighting systems (LSs), and renewable energy sources (RESs), which have been integrated into the building environment. After illustrating the conceptual background of the most common ANN architectures for controlling BEMSs, the current work dives deep into relative research applications, thereby exhibiting their methodology and outcomes. By summarizing the numerous impactful applications during 2015–2023, this paper categorizes the predominant ANN-based techniques according to their methodological approach, specific energy equipment, and experimental setups. Grounded in the different perspectives that the integrated studies illustrate, the primary focus of this paper is to evaluate the overall status of ANN-driven control in building energy management, as well as to offer a deep understanding of the prevailing trends at the building level. Leveraging detailed graphical depictions and comparisons between different concepts, future directions, and fruitful conclusions are drawn, and the upcoming innovations of ANN-based control frameworks in BEMSs are highlighted. [ABSTRACT FROM AUTHOR]

This document discusses the challenges of achieving high-power quality in modern power grids with a large share of distributed power production, particularly due to the integration of renewable energy sources (RES). The variable nature of RES can lead to disturbances and power quality degradation. The document highlights the importance of voltage source converters and control systems in enabling the flexible operation of RES. It also mentions the concept of microgrids, which are closely connected to power quality and other factors such as the Internet of Things and cyber security. The document includes eight research papers covering various topics related to power quality analysis and control of renewable energy sources in power grids. These topics include power factor correction, supercapacitor parameters identification, pulse width modulation, disturbance analysis, vibration analysis of motors, control of converters, phasor measurement units, and optimization of controller parameters. The document concludes by expressing gratitude to the authors, staff, and reviewers involved in the research papers. [Extracted from the article]

There is currently exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the associated charging demand. If, on the one hand, the introduction of energy generation from renewable energy sources can be used to meet that requirement, the intermittent nature of some of these sources will challenge the mandatory real-time equilibrium between generation and consumption. In order to use most of the energy generated via these sources, mechanisms are required to manage the charging of batteries in electric vehicles, according to the levels of generation. An effective smart charging process requires communication and/or control mechanisms between the supply equipment and the electric vehicle, enabling the adjustment of the energy transfer according to the generation levels. At this level, the ISO 15118 standard supports high-level communication mechanisms, far beyond the basic control solutions offered through the IEC 61851-1 specification. It is, thus, relevant to evaluate it in smart charging scenarios. In this context, this paper presents the development of a charge emulation system using the ISO 15118 communication protocol, and it discusses its application for demand response purposes. The system comprises several modules developed at both ends, supply equipment and electric vehicles, and allows the exchange of data during an emulated charging process. The system also includes human interfaces to facilitate interactions with users at both ends. Tests performed using the implemented system have shown that it supports a demand response when integrated with a photovoltaic renewable energy source. The dynamic adjustment to charging parameters, based on real-time energy availability, ensures efficient and sustainable charging processes, reducing the reliance on the grid and promoting the use of renewable energy. [ABSTRACT FROM AUTHOR]

The integration of renewable energy is rapidly leading the existing grid systems toward modern hybrid power systems. These hybrid power systems are more complex due to the random and intermittent nature of RE and involve numerous operational challenges. This paper presents the operational model for solar integrated power systems to address the issues of economical operation, reliable solar share, energy deficit in case of contingency events, and the allocation of system spinning reserve. A mixed-integer optimization is formulated to minimize the overall cost of the system operation and to maximize the solar share under robust system spinning reserve limits as well as various other practical constraints. A Pareto-optimal solution for the maximization of the number of solar power plants and minimization of the solar cost is also presented for reliable solar share. Further, a decomposition framework is proposed to split the original problem into two sub-problems. The solution of joint optimization is obtained by exploiting a Lagrange relaxation method, a binary search Lambda iteration method, system spinning reserve analysis, and binary integer programming. The proposed model was implemented on an IEEE-RTS 26 units system and 40 solar plants. [ABSTRACT FROM AUTHOR]

Microbial fuel cells (MFCs) have garnered significant attention due to their capacity to generate electricity using renewable and carbon-neutral energy sources such as wastewater. Extensive experimental work and modeling techniques have been employed to dissect these processes and understand their respective impacts on electricity generation. The driving force is to enhance MFC performance for practical applications commercially. Among the various statistical modeling approaches, one particularly robust tool is the Design of Experiments (DoE). It serves to establish the relationships between different variables that influence MFC performance and allows for the optimization of the MFC configuration and operation for scaled-up performances in terms of bioelectricity generation. This study focused on optimizing microbial fuel cells (MFCs) for bioelectricity production using industrial wastewater treatment, employing the Box–Behnken design (BBD) methodology. Through an analysis of response surface models and ANOVA tests, it was found that a combined approach of reduced quadratic, reduced two-factor interaction, and linear models yielded sound results, particularly in voltage yield, COD removal, and current density. Second-order regression models predicted optimal conditions for various parameters, with surface area, temperature, and catholyte dosage identified as critical input variables for optimization. Under these conditions, conducted by the four-factor and three-level Box–Behnken design methodology in a double-chamber MFC unit considering eight output variables—CCV yield, % COD removal, current density, power density, % TSS removal, % CE, and % P O 4 3 − —the optimum values were 700 mV, 54.4%, 54.4 mA/m2, 73.7 mW/m2, 99%, 21.2%, and 100%, respectively. At optimum operating conditions, the results revealed a desirability of 76.6% out of a total of 92 iterations. The paper highlights the effectiveness of statistical ANOVA fit-statistics modeling and optimization in enhancing DCMFC performance, recommending its use as a sustainable bioenergy source. Furthermore, validation results supported the above optimization output response findings and confirmed the viability of biorefinery wastewater as an anolyte for scaling up DCMFC bioelectricity generation. [ABSTRACT FROM AUTHOR]

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system. [ABSTRACT FROM AUTHOR]

Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model designed to predict day-ahead electricity prices in the Kyushu area of Japan. To mitigate the inherent uncertainties associated with neural networks, a novel ensemble learning approach is implemented to bolster the DAEPF model's robustness and prediction accuracy. The CNN–LSTM model is verified to outperform a standalone LSTM model in both prediction accuracy and computation time. Additionally, applying a natural logarithm transformation to the target day-ahead electricity price as a pre-processing technique has proven necessary for higher prediction accuracy. A novel "policy-versus-policy" strategy is proposed to address the prediction problem of the zero prices, halving the computation time of the traditional two-stage method. The efficacy of incorporating a suite of multimodal features: areal day-ahead electricity price, day-ahead system electricity price, areal actual power generation, areal meteorological forecasts, calendar forecasts, alongside the rolling features of areal day-ahead electricity price, as explanatory variables to significantly enhance DAEPF accuracy has been validated. With the full integration of the proposed features, the CNN–LSTM ensemble model achieves its highest accuracy, reaching performance metrics of R 2 , MAE, and RMSE of 0.787, 1.936 JPY/kWh, and 2.630 JPY/kWh, respectively, during the test range from 1 March 2023 to 31 March 2023, underscoring the advantages of a comprehensive, multi-dimensional approach to DAEPF. [ABSTRACT FROM AUTHOR]

In recent years, integration of solar photovoltaic (PV) systems into distribution networks has been increasing rapidly, as it has become the most promising renewable energy source (RES) in the transition of power generation from centralised to decentralised systems. With the power electronic (PE) interfaces that use high-frequency internal switching, all renewable energy sources are considered to be harmonic emitters, especially near switching frequencies, i.e., above 2 kHz. This paper evaluates the behaviour of high-frequency harmonics in the 2–20 kHz range due to the parallel operation of multiple solar PV inverters connected to a low-voltage (LV) network. The circulation current component that flows within the installation due to the low impedance paths at higher frequencies is analysed. Summation of high-frequency harmonic currents is observed with phase diversity analysis. The circulating current component can become 14 times higher than the grid current component at higher frequencies. [ABSTRACT FROM AUTHOR]

This paper looks at the changing impact of renewable energy and green innovation on the carbon footprint of eight MENA nations between 2000 and 2020. We investigate this by using the panel Q-ARDL model for the first time, and we find that, with various impacts across different quantiles, a rise in green innovation and renewable energy greatly boosts environmental sustainability in the short run. In the long run, this effect becomes increasingly more noticeable. According to our analysis, the chosen MENA countries quickly embraced energy storage, solar hydrogen, and other technology pathways to diversify their energy mix, which was a turning point in the fight against climate change. Although these factors have been separately examined in different studies, our research merges them into a single non-parametric model. This research is significant as it provides empirical evidence on the efficiency of green innovation and renewable energy policies, and it will guide policymakers and energy stakeholders in developing strategies to achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

The green energy transition calls for various solutions to enhance environmental sustainability. One of these is represented by renewable energy communities, which may help transition from centralized energy production to distributed renewable generation. European countries are actively promoting incentive schemes for energy communities to foster local electricity self-consumption in order to balance demand and renewable generation. In this context, energy storage facilities can be employed to gather the energy production surplus and use it in periods of low generation. In this paper, we focus on the optimal operation of an incentive-based energy community in the presence of energy storage systems. A centralized optimization problem was formulated to optimally operate storage systems at the community level. Starting from this solution, distributed charging/discharging commands were found to optimally operate the single storage units. Moreover, conditions guaranteeing the convenience of using energy storage systems inside the community were derived. Numerical simulations were performed to validate the reported results and to evaluate the potential benefits of energy storage facilities inside renewable energy communities. [ABSTRACT FROM AUTHOR]

This paper investigates grid export constraints applicable to photovoltaic (PV) and wind farm (WF) installations, both with and without behind-the-meter storage, aimed at enhancing grid hosting capacity. The study focuses on static output power limitations, i.e., simple export constraints that are preventively imposed on renewable energy source (RES) plants regardless of the prevailing network congestion conditions. These constraints are easy to apply, implemented ex ante and out of market, and do not require additional investments in energy storage or advanced devices. They also yield a measurable increase in hosting capacity and grid utilization, with their impact on RES plant operation and return of investment straightforwardly calculable. Analysis defines the level and shape of these constraints assuming an indicative acceptable curtailment level of 5% for each RES technology attributed to the preventing action of the imposed limitations, while the respective implications for RES energy yield and investment viability are explored. The findings indicate that an export power limitation of ca. 68% is effective for stand-alone PVs, while a stepwise static limitation is necessary for stand-alone WFs and WFs with integrated storage to manage midday solar generation peaks. PV plants tightly coupled with storage facilities can handle static limitations as low as 35% with minimal impact on the economic feasibility of the investments. [ABSTRACT FROM AUTHOR]

One of the United Nations' 17 Sustainable Development Goals is to "Ensure access to affordable, sustainable, and clean energy for all." Additionally, the growing concerns about climate change and energy security have heightened the importance of exploring alternative energy sources to replace fossil fuels. The utilisation of agricultural waste for bioenergy production has acquired significant attention due to its potential to mitigate environmental impacts and provide renewable energy sources. However, the major obstacle to producing bioenergy is managing the supply chain while considering economic, environmental, and social factors in an optimal way. This paper presents a comprehensive overview of the literature on the management of agriculture waste supply chains, specifically related to the use of modelling and optimisation techniques for planning. The first section describes different stages of the supply chain and various technologies for converting biomass to bioenergy. This is followed by a synopsis of the literature reviewed based on decision levels, objective functions, modelling methodologies, and optimisation approaches. Finally, the review highlights limitations and gaps in current research and the areas with potential for further exploration. [ABSTRACT FROM AUTHOR]

With the energy structure transition and the development of the green power market, the role of electricity retailers in multi-market green power trading has become more and more important. Particularly in China, where aggressive green energy policies and rapid market transformations provide a distinct context for such studies, the challenges are pronounced. Under demand-side response, electricity retailers face the uncertainty of users' electricity consumption and incentives, which complicates decision-making processes. The purpose of this paper is to explore the optimization decision-making problem of multi-market green power trading for electricity retailers under demand-side response, with a special focus on the Chinese market due to its leadership in implementing substantial green energy initiatives and its potential to set precedents for global practices. We first construct a two-party benefit optimization model, which comprehensively considers the profit objectives for electricity retailers and utility maximization for users. Then, the model is solved by the Lagrange multiplier method and distributed subgradient algorithm to obtain the optimal solution. Finally, the effectiveness of the incentive optimization strategy under the multi-market to promote green power consumption and improve the profit of electricity retailers is verified by arithmetic simulation. The results of this study show that the incentive optimization strategy under multi-market, particularly within the Chinese context, is expected to provide a reference for electricity retailers to develop more flexible and effective trading strategies in the green power market and to contribute to the process of promoting green power consumption globally. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy sources (RESs) in transmission and distribution systems presents several challenges for grid operators. In particular, the unpredictable behavior of RESs can disrupt the balance between energy production and load demand, potentially affecting the stability of the entire system. Grid-connected energy storage systems (ESSs) offer a possible solution to manage the uncertainty associated with RESs. In fact, ESSs exchange power with the grid through the adoption of suitable energy management strategies, which are typically implemented by power electronics-based grid interfaces. Unlike other current source converter (CSC) solutions described in the literature, which only interface with a single energy storage device, this paper introduces a novel topology for a three-phase delta-type current source converter (D-CSC), which is capable of integrating three independent ESSs using the same number of semiconductors as traditional CSC solutions. Thus, it considerably enhances the flexibility of a power conversion system (PCS) without increasing the number of converter components. In addition, an innovative energy management control strategy is also introduced. This strategy enables the D-CSC to compensate for energy imbalances arising between the three ESSs, which might be caused by several factors, such as different aging characteristics, converter component tolerances, operating conditions, and temperature drifts. Hence, the D-CSC-based interface is capable of proper grid operation even if the three ESSs have different characteristics, thus opening the possibility of employing this converter to integrate both first and second-life devices. First, the topology of the proposed D-CSC is introduced, followed by a detailed mathematical description of its control strategy. The proper grid operation of the D-CSC was tested under different scenarios, considering the grid integration of three independent superconducting magnetic energy storage systems in a marine vessel. The proposed D-CSC is compared to traditional CSC solutions, highlighting the superior performances of the novel converter topology in terms of efficiency, total harmonic distortion of the output currents, and overall cost reduction for the PCS. [ABSTRACT FROM AUTHOR]

The strategic objective of world climate policy is the decarbonization of industries, aiming to achieve "net-zero" emissions by 2050, as outlined in the European Green Deal and the Paris Agreement. This transition entails increasing the utilization of renewable energy sources (RES) in industrial energy consumption, thereby transforming economies from reliance on fossil fuels to sustainable alternatives. However, this shift poses a significant challenge for many EU countries, with varying degrees of success in adaptation. This paper investigates the process of decarbonizing industries by analyzing trends in the adoption of RES in EU countries and evaluating their progress toward climate targets. Utilizing time series analysis of production, total energy usage, and the proportion of renewables in industrial energy consumption, the study compares two groups of countries: longstanding EU members and newer additions. The aim is to forecast the trajectory of RES integration in industry and assess the feasibility of meeting the targets outlined in the European Green Deal. The findings reveal a considerable gap between the set targets and projected outcomes, with only a few countries expected to meet the EU's 2030 goals. This is highlighted by disparities in RES shares across member states, ranging from 0.0% to 53.8% in 2022. Despite notable increases in the absolute use of renewable energy, particularly in central and eastern European nations, substantial challenges persist in aligning industrial sectors with EU decarbonization objectives. [ABSTRACT FROM AUTHOR]

As the demand for sustainable energy solutions grows, there is a critical requirement for continuous innovation to optimize the performance and safety of renewable energy systems (RESs). Closed-loop digital twins (CLDTs)—synchronized virtual replicas embedded with real-time data and control loops to mirror the behavior of physical systems—have emerged as a promising tool for achieving this goal. This paper presents a systematic literature review on the application of digital twin (DT) technology in the context of RESs with an emphasis on the impact of DTs on the efficiency, performance, and safety assurance of RESs. It explores the concept of CLDTs, highlighting their key functionalities and potential benefits for various renewable energy technologies. However, their effective implementation requires a structured approach to integrate observation, orientation, decision, and action (OODA) processes. This study presents a novel OODA framework specifically designed for CLDTs to systematically identify and manage their key components. These components include real-time monitoring, decision-making, and actuation. The comparison is carried out against the capabilities of DT utilizing the OODA framework. By analyzing the current literature, this review explores how DT empowers RESs with enhanced efficiency, reduced risks, and improved safety assurance. [ABSTRACT FROM AUTHOR]

Geothermal resources have been recognized as important sources of clean renewable energy. The exploration, development, and utilization of geothermal resources, especially hot dry rock (HDR) resources, are highly important for achieving peak carbon and carbon neutrality. However, there is no comprehensive evaluation method for determining HDR target areas, and the evaluation scale and application disciplines are relatively simplistic. In this paper, we sought to optimize the identification of HDR target areas through a multiscale and multidisciplinary method and formed a set of generalized and demonstrative processes to guide the exploration of HDR resources. Through practical application to the Gonghe Basin and the Zhangzhou Basin, it was found that the comprehensive geothermal conditions of the Gonghe Basin are superior to those of the Zhangzhou Basin, and the geothermal reservoir depth, geothermal reservoir temperature, geothermal gradient, and heat flow are the four most important factors affecting hot dry rock geothermal resources. Using this method, the prioritization of target areas changes from a qualitative study to a quantitative and semiquantitative study, increasing the specificity and reliability of the decision-making process. [ABSTRACT FROM AUTHOR]

Over the past few decades, many universities have turned to using microgrid systems because of their dependability, security, flexibility, and less reliance on the primary grid. Microgrids on campuses face challenges in the instability of power production due to meteorological conditions, as the output of renewable sources such as solar and wind power relies entirely on the weather and determining the optimal size of microgrids. Therefore, this paper comprehensively reviews the university campuses' microgrids. Some renewable energy sources, such as geothermal (GE), wind turbine (WT), and photovoltaic (PV), are compared in terms of installation costs, availability, weather conditions, efficiency, environmental impact, and maintenance. Furthermore, a description of microgrid systems and their components, including distributed generation (DG), energy storage system (ESS), and microgrid load, is presented. As a result, the most common optimization models for analyzing the performance of campus microgrids are discussed. Hybrid microgrid system configurations are introduced and compared to find the optimal configuration in terms of energy production and flexibility. Therefore, configuration A (Hybrid PV- grid-connected) is the most common configuration compared to the others due to its simplicity and free-charge operation. [ABSTRACT FROM AUTHOR]

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology. [ABSTRACT FROM AUTHOR]