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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]

The recent passage of the Offshore Electricity Infrastructure Act (2021) (Cth) opened up the potential for Australia to produce renewable energy at unprecedented scale. Six regions have been identified as potential locations for developing offshore wind projects, promising thousands of new local jobs to legacy industrial regions. This paper charts the regulatory framework for Australia's offshore wind industry and how it positions local economic benefits in the licencing of projects. It then draws on interviews with key stakeholders supported by media and policy analysis to examine the early development of offshore wind capability in one of the proposed regions, the Illawarra, in NSW. Here existing steelmaking capacity positions the region to play a key role in supply chains for local and potentially national projects, but considerable structural and geographical constraints in the labour market will need to be addressed. In light of overseas experience indicating that economic benefits often fall short of promises, greater attention by policy makers is required to ensure hosting communities can develop local skills in the industry and facilitate their relative supply chain capabilities. This paper also calls for careful evaluation of early projects to allow for adjustments to policy settings as the industry matures domestically. [ABSTRACT FROM AUTHOR]

The ageing of coal-fired power stations in South Africa has led to regular power outages. Therefore, the country will need to urgently increase its electricity capacity to meet further energy demand from growing urbanization and population growth. This challenge has increased interest in alternative energy sources, such as renewable energy (RE). South Africa is gradually implementing appropriate renewable energy practices, reducing carbon emissions, cleansing the air, and assuring a more sustainable future. This paper summarizes the availability, current state, and future potential of renewable energy choices in South Africa. This paper also evaluates specific policy measures and government actions aimed at eliminating barriers and increasing renewable energy deployment in the future. It also considers the South African network's specialized techno-economic analysis. The findings show that South Africa is still heavily reliant on coal, with 78% of the current installed capacity coming from coal power in 2022, compared to 9.3% for solar and wind energy. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

This paper utilizes social network analysis to examine the structural characteristics and trade dynamics of the renewable energy (hydropower, wind energy, and solar energy) trade network within the RCEP region from 2011 to 2020. The findings reveal: (1) The renewable energy trade network within the RCEP exhibits dynamism, heterogeneity, and an uneven development. The solar energy network is the most balanced and stable, while the wind energy network lags and shows marked fluctuations, with the hydropower network falling between these two. This demonstrates the diversity of energy trade within the region. (2) China, Singapore, and Japan are identified as the key exporting and importing countries, with Vietnam showing substantial growth potential. Individual analyses shed light on the stark disparities in trade status among nations, reflecting the diverse roles and future potential of member countries. (3) The QAP regression analysis reveals a significant influence of environmental pressure, particularly carbon dioxide emissions, on the renewable energy trade network. This study contributes to promoting environmental sustainability and energy security in the RCEP region and provides empirical evidence for global renewable energy trade strategies. [ABSTRACT FROM AUTHOR]

The increasing trend of energy generation and management systems towards decentralized structures such as using renewable energy resources makes it necessary to use digital and smart platforms for exchanging information and even conducting financial transactions in a decentralized manner, known as the peer‐to‐peer model. The decentralized transaction verification of cryptocurrencies makes it possible to use these encrypted currencies and decentralized blockchain networks in energy management systems and carry out financial transactions related to carbon trading. Carbon and other greenhouse gas (GHG) emission trading systems reduce the competitiveness of fossil fuel projects in the market and accelerate investment in low‐carbon energy sources such as wind and photovoltaic power generation units. This market mechanism allows large entities such as countries and companies that emit GHGs into the atmosphere to buy and sell these gases. This paper reviews the blockchain solutions developed for carbon markets. Studies related to the design of smart contracts in the platform of blockchain are investigated. Special cryptocurrencies that are used in the field of green energy transactions and carbon trading are introduced. In addition, the application of artificial intelligence and game theory in energy trading is stated. The study of different blockchain frameworks for carbon trading shows that the use of decentralized platforms in carbon trading can have a significant impact on the trend towards low‐carbon measures and achieving the goals of the Kyoto Treaty, increasing the value of green cryptocurrencies and the volume of transactions. These technologies offer a promising avenue for creating a more decentralized, efficient, and environmentally conscious energy ecosystem. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the development of a floating artificial sustainable energy island at a conceptual design level that would enhance the energy independence of islands focusing on a case study on the island of Crete. This paper provides a baseline assessment showing the immense potential of wind and solar energy in and around Crete integrating the third significant renewable energy source (RES) of ocean waves into the energy island. The selection of the best location for the floating offshore platforms that compose the energy island is addressed through exploiting the great potential of the above-mentioned RES, taking into consideration criteria with regard to several significant human activities. To this end, the concept of an innovative floating modular energy island (FMEI) that integrates different renewable energy resources is proposed; in addition, a case study that focuses on the energy independency of a big island illustrates the concept referring to the substitution of the local thermal power plants that are currently in operation in Crete with sustainable energy power. Although focused on the renewable energy resources around Crete, the work of this paper provides a basis for a systematic offshore renewable energy assessment as it proposes a new methodology that could be used anywhere around the globe. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

Our paper focuses on assessing the role of state funding in supporting wind energy projects with a focus on economic efficiency and risk assessment. In particular, we analyze the new program aimed at supporting Russian renewable energy (RE) projects envisaged for the period from 2024–2035 that involves a reduction in investments in such projects and the introduction of large fines for non-compliance with regulatory requirements for localization and export. These strict rules imposed by the regulatory authorities, as well as the withdrawal by foreign manufacturers of equipment for renewable energy from the domestic energy market, put into doubt the economic feasibility of the participation of sector players in state-supported programs. Our paper assesses the economic justification for the practicality of the Russian energy market to implement renewable energy projects under the influence of negative environmental factors and the reduction of state support programs. We employ a case study of wind energy projects carried out in 2018–2020 as a part of the first sector support program. Our methodology is based on the calculations of the classical indicators of economic efficiency of projects (NPV, IRR, and DPP). Our own approach reveals that these indicators are supplemented by taking into account the cost of specific political, environmental, and economic risks of wind energy projects. Our results reveal that, at the moment, Russian wind energy projects in various scenarios retain a sufficient margin of financial strength and are able to withstand a reduction in the amount of financial support from the state. Our findings allow the formulation of some practical recommendations for reducing the share of governmental support for wind energy projects on the local energy market as a measure of cutting costs and increasing overall economic efficiency. [ABSTRACT FROM AUTHOR]

Power generation using renewable energy sources is becoming popular in current scenario due to their capability of reduction in carbon emission as well as reliable power supply to consumers. However, power generation from a single renewable energy source cannot able to provide stable power. Hence, integration of renewable energy sources-based power generations needs to be established for providing continuous power supply to consumers. Solar energy and wind power are two major available sources on earth, hence, photovoltaic (PV) and permanent magnet synchronous generator (PMSG) based wind power generation system is considered in this paper. On the other hand, many loads are AC loads that required conversion from DC to AC such as inverters. Generally, multilevel inverters can able to provide quality supply to loads than normal inverters. However, the number of switches used in the multilevel inverter is more and also increasing size and complexity by increasing the level of the inverter. Therefore, an aligned multilevel inverter is implemented for a PV-Wind-based stand-alone system that has a smaller number of switches. Both solar irradiance and wind speed are depending on weather conditions and are unstable, hence a battery bank is incorporated with the help of a bidirectional DC to DC converter to provide an uninterrupted power supply to loads. A novel controller for 7 levels aligned inverter is implemented in this paper to supply quality power to loads under various scenarios. The proposed Aligned Multilevel Inverter needs half of the switches when compared to existing multilevel inverters as diode-clamped, flying-capacitor, and cascaded H-Bridge topologies. The hardware-in-loop is developed with OPAL-RT to present results under various case studies. [ABSTRACT FROM AUTHOR]

Conventional energy resource problems made power system planners apply more renewable energy sources (RESs) in the power system. RESs have a significant impact on fulfilling the world's energy demand, protecting the environment at least in the exploration phase, and providing energy reliability as well as security for the new generation of power grids. In this regard, wind power generation is considered a promising solution. However, by increasing the share of wind power generation units in the power sector, some challenges, such as voltage problems, transient stability, increasing system losses, and line congestions can occur. Consequently, an alternative solution is required to accelerate wind power units' connections to the grid by preventing the problems caused by the penetration of wind power. In this regard, Flexible Alternating Current Transmission Systems (FACTS) devices can play an important role while they can improve power grid dynamic performance. This paper presents a review of the optimization techniques applied to accelerate the penetration of wind energy by exploiting FACTS devices. The topic identifies the objectives and optimization formulations, as well as schemes and models available in the published literature. This survey gives noteworthy insights to the researchers to cover available solutions in these regards. The literature in the field is summarized in different aspects, such as FACTS technology, objective functions, constraints, optimization methods, planning or operation purposes, and load flow types. At each aspect, a comparison is derived to recognize the most important issues. The result of the review is the finding of future work and contributions which can be done in the field of wind energy integration acceleration using FACTS devices and the output of the paper can be used as a guide for researchers to find a new path for research in this area. [ABSTRACT FROM AUTHOR]

In the present energy scenario, wind energy is the fastest-growing renewable energy resource on the globe. However, wind-energy-based generation systems are also associated with increasing demands for power quality and active power control in the power network. With the advancements in power-electronics-based technology and its use in non-conventional energy conversion systems, it has witnessed tremendous growth in wind energy conversion systems (WECSs). At the same time, integrating wind farms into the grid system also results in many power quality issues in the power system that involve these renewable energy sources feeding power networks. This paper reports the effectiveness of grid-connected doubly fed induction generator (DFIG)-based WECS with a battery energy storage system (BESS) under variable wind conditions. In this study, a rotor side converter (RSC) is controlled to achieve the optimal torque for a given maximal wind power. The control scheme is simulated using MATLAB for a 2 MW-rated DFIG used in a WECS. Additionally, in this paper, a new fraction order proportional integral derivative (FOPID) controller is introduced into the system's RSC, and its performance is also observed. The BESS technique is used with a DC link to improve the overall performance of the DFIG-based WECS under different wind conditions. To control the BESS, a proportional integral (PI) controller is introduced to increase the charging and discharging rates. Two models are developed in MATLAB/Simulink: one model is a basic model, and other model is equipped with a BESS and a PI controller in the BESS. The results validate the effectiveness of the proposed PI-controller-equipped BESS at improving the overall performance of the WECS system under study. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources is becoming increasingly widespread around the world due to various factors, the most relevant of which is the high environmental friendliness of these types of energy resources. However, the large-scale involvement of green energy leads to the creation of distributed energy networks that combine several different generation methods, each of which has its own specific features, and as a result, the data collection and processing necessary to optimize the operation of such energy systems become more relevant. Development of new technologies for the more optimal use of RES is one of the main tasks of modern research in the field of energy, where an important place is assigned to the use of technologies based on artificial intelligence, allowing researchers to significantly increase the efficiency of the use of all types of RES within energy systems. This paper proposes to consider the methodology of application of modern approaches to the assessment of the amount of energy obtained from renewable energy sources based on artificial intelligence technologies, approaches used for data processing and for optimization of the control processes for operating energy systems with the integration of renewable energy sources. The relevance of the work lies in the formation of a general approach applied to the evaluation of renewable energy sources such as solar and wind energy based on the use of artificial intelligence technologies. As a verification of the approach considered by the authors, a number of models for predicting the amount of solar power generation using photovoltaic panels have been implemented, for which modern machine-learning methods have been used. As a result of testing for quality and accuracy, the best results were obtained using a hybrid forecasting model, which combines the joint use of a random forest model applied at the stage of the normalization of the input data, exponential smoothing model, and LSTM model. [ABSTRACT FROM AUTHOR]

Renewable energy sources are seen as a sustainable solution to the problem of global energy security. Among the renewable energy sources, wave energy has great prospects for development in a few countries, including South Africa. However, South Africa's wave energy projects are still underinvested in practice compared to wind energy and solar PV. This paper investigates several questions related to the influence of both quantitative and qualitative factors on the effectiveness of wave energy projects (WEPs) and the appropriate placement for WEP in South Africa. For this purpose, a novel two-phase framework novel two-phase data envelopment analysis (DEA) supporting integrated multiple criteria decision-making (MCDM) framework is proposed. The first phase aims to identify potential locations for WEPs and calculate the technical advantage of these locations using the DEA model. In the second phase, other qualitative criteria, which affect the sustainable development of WEPs, are identified. Based on expert surveys, potential locations are analyzed and ranked by a novel integrated MCDM approach called OPA-EDAS. In the proposed approach, the advantages of the Ordinal Priority Approach (OPA) are utilized to simultaneously determine the weight of the criteria and prioritize the alternatives. However, the results of OPA depend on the priorities of the experts participating in the assessment. Therefore, this study attempted to overcome that by integrating the EDAS technique to assess the expertise. Furthermore, the DEA model is applied to increase the objectivity of the results. In addition, the robustness of the study's findings is validated by comparing the location with upcoming WEPs in South Africa. The result shows that the coast of Cape Nature Walker Bay has the most effectiveness for South Africa's WEPs. [ABSTRACT FROM AUTHOR]

As flexible resources, cascaded hydropower stations can regulate the fluctuations caused by wind and photovoltaic power. Constructing pumped-storage units between two upstream and downstream reservoirs is an effective method to further expand the capacity of flexible resources. This method transforms cascaded hydropower stations into a cascaded pumped-hydro-energy storage system. In this paper, a flexibility reformation planning model of cascaded hydropower stations retrofitted with pumped-storage units under a hybrid system composed of thermal, wind, and photovoltaic power is established with the aim of investigating the optimal capacity of pumped-storage units. First, a generative adversarial network and a density peak clustering algorithm are utilized to generate typical scenarios to deal with the seasonal fluctuation of renewable energy generation, natural water inflow, and loads. Then, a full-scenario optimization method is proposed to optimize the operation costs of multiple scenarios considering the variable-speed operation characteristics of pumped storage and to obtain a scheme with better comprehensive economy. Meanwhile, the proposed model is retransformed into a mixed-integer linear programming problem to simplify the solution. Case studies in Sichuan province are used to demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Recently, the proportion of renewable energy (RE) sources in a power system has been increasing worldwide to reduce carbon emissions. To effectively accommodate renewable energy, there is a growing need to develop integrated planning strategies for both renewable energy sources and transmission lines in a power system, taking into account the location-specific characteristics of renewable energy. Economically viable and rapid system expansion plans are required to resolve the problem of delayed integration of renewable energy into existing power system, which arises due to inadequate transmission facilities. To address these problems, this paper presents an integrated economic evaluation method that considers the inherently uncertain output characteristics of renewable energy, contingent on location, the costs associated with installing transmission lines, and environmental benefits. The case study is conducted using a modified power system in Korea. In the case study, it is assumed that by integrating solar power generators in a low-demand area and wind power generators in a high-demand area, wind power plants have higher construction costs than solar power generators. However, the transmission costs for wind power plants are lower than those for solar power generators due to the regional characteristics of the power grid in the installation areas because renewable energy in high-demand areas typically requires less additional power infrastructure than in low-demand areas. The results of this study show that the net benefit for the wind power plant is estimated at USD 225.4 M, while the solar power plant yields a net benefit of USD 22.9 M in the example system. These results demonstrate the effectiveness of the proposed method, underscoring its potential to mitigate the challenges faced in the practical implementation of renewable energy projects. [ABSTRACT FROM AUTHOR]

This paper deals with improving the feed-in tariff policy for green energy advancement in Ukraine's households based on assessing the economic efficiency of investment project implementation under the current state support mechanisms. This study was conducted for solar and wind power plants with different installed capacities. The Levelized Cost of Electricity and the payback period for such power plants were calculated considering the ongoing feed-in tariffs and discount rates determined by various equity and debt capital ratios. The results showed that the state support provides attractive payback periods for solar and wind power plants with an installed capacity of ≥30 kW. In comparison, 5 kW solar power plants and wind power plants with a capacity of up to 10 kW are not paid off during the power plants' lifecycle. It confirmed that the ongoing energy policy in Ukraine's residential sector is still designed to obtain profits by the owners of generating facilities by selling the excess electricity. In the meantime, its main goal—providing households energy independence—has been levelled. To resolve the issues caused by such a state support model, a methodical approach to improve the feed-in tariff calculation is proposed. In addition, recommendations for reconsidering other policy measures to ensure effective renewable energy development in the residential sector have been made. [ABSTRACT FROM AUTHOR]

It is a known fact that fossil fuels will be depleted in the near future owing to the negative effects on the environment. The number of applications using renewable energy sources instead of fossil fuels to obtain energy has increased significantly. It is aimed to provide effective energy production with the proposed rotary energy system (RES) installation for regions with high wind energy and solar energy potential. In the paper, the design, manufacturing process, installation, and output power prediction of a novel RES are presented. In the proposed system, a hybrid system whose energy is derived from solar and wind energy is envisaged. The electrical characteristics of the solar panels with dimensions 140 × 60 × 2.5 mm mounted on the prototype are 6 V 100 mA. The prototype has been tested at different rotation speeds to evaluate the effect of wind energy. Moreover, the output power prediction based on Feedforward Neural Network (FFNN) and Particle Swarm Optimization trained Feedforward Neural Network (PSO-FFNN) has been performed with the data obtained from the prototype system. The three quantitative standard statistical performance evaluation measures, root mean square error (RMSE), mean absolute percentage error (MAPE) and Theil's inequality coefficient (TIC) are employed to compare the performances of these architectures. FFNN architecture, the RMSE, MAPE and TIC values are calculated as 0.0690, 0.0455 and 0.0278, respectively. For the PSO-FFNN architecture, RMSE, MAPE and TIC values are 0.0530, 0.0383, and 0.0213, respectively. It has been proved that it will be produced energy more effectively thanks to the hybrid RES in meeting energy demand. [ABSTRACT FROM AUTHOR]

In recent years, renewable energy has received extensive attention due to its advantages of sustainability, economy, and environmental protection. However, with the rapid development of renewable energy, the problem of curtailment is becoming increasingly serious. Studying the calculation method and establishing a quantitative evaluation system of renewable energy accommodation capacity are important means to solve this problem. This paper comprehensively considers the factors affecting the accommodation of renewable energy, establishes a accommodation calculation model with the maximum accommodation of renewable energy as the optimization target based on the time series production simulation method, and uses the hybrid particle swarm optimization (PSO) algorithm to solve it. The model is verified with historical data such as load, photovoltaic (PV), and wind power in a certain region throughout the year. The experimental results verify the rationality of the renewable-energy accommodation-capacity model proposed in this paper and the correctness of the theoretical analysis. The calculation results have important reference and guiding significance for the operation and control of power-grid planning and dispatching. [ABSTRACT FROM AUTHOR]

Owing to the various sources of complexity in the electrical power system, such as integrating intermittent renewable energy resources and widely spread nonlinear power system components, which result in sudden changes in the power system operating conditions, the conventional PID controller fails to track such dynamic challenges to mitigate the frequency deviation problem. Thus, in this paper, a fuzzy PI controller is proposed to enhance the automatic generation control system (AGC) against step disturbance, dynamic disturbance, and wind energy disturbance in a single area system. The proposed controller is initialized by using Equilibrium Optimization and proved its superiority through comparison with a classical PI optimized base. Results show that the fuzzy PI controller can reduce the peak-to-peak deviation in the frequency by 30–59% under wind disturbance, compared to a classical PI optimized base. Moreover, a fuzzy PID controller is also proposed and EO initialized in this paper to compare with the PIDA optimized by several techniques in the two-area system. Results show that the fuzzy PID controller can reduce the peak-to-peak deviation in the frequency of area 1 by 30–50% and the deviation of frequency in area 2 by 13–48% under wave disturbance, compared to the classical PIDA optimized base. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

A dependable and cost-effective energy distribution scheme is the need in the current scenario of distributed generation of electricity. In the recent past, different economic dispatch techniques are proposed to address this challenge of cost-effectiveness. The fossil fuels issue of pollutant emission and the limited stock has pushed the research community to focus on the direction of renewable energy generation. The aim of this paper is to present a multi-objective cost-emission-based dynamic economic dispatch (MOCEDED) algorithm, which includes thermal, solar, and wind-based power plants. Moreover, the uncertainty of solar and wind power in terms of curtailment is also included in the formulation of the algorithm. The formulated objective function is quadratic constrained programming, which is implemented in General Algebraic Modeling System software. Two paradigms, i.e. only cost-based DED and MOCEDED algorithm, have been analyzed. The outcome of the proposed MOCEDED algorithm shows more promising results than cost-based DED. [ABSTRACT FROM AUTHOR]

Following the "green" growth tradition, the construction of lower carbon energy (renewable energy) infrastructures, such as wind power, has gained prominence in Norway. This has led to indigenous Saami herders confronting pastureland dispossession, some citizens fearing the industrialization of nature, and municipal councils losing formal governance power in favor of national agencies and private-sector project developers—justified by the urgency of the climate crisis. The purpose of the paper is to explore how energy infrastructures aimed at decarbonization have led to social fragmentation and ecological degradation alongside claims of economic revitalization potential in Åfjord. The authors draw upon fieldwork conducted within Saepmie (or Sápmi), the cultural region traditionally inhabited by the Sámi, and investigate the Fosen Vind energy project in the Åfjord Municipality. They find that lower carbon energy infrastructures, such as "wind farms," have been normalized as unavoidable, and damage to habitat and encroachment on Saami livelihoods are positioned as necessary sacrifices for the greater good of fighting the climate crisis. The authors conclude that avoiding the creation of green sacrifice zones in making low-carbon places requires a more transformative vision than the visions offered by techno-solutionism, such as degrowth. [ABSTRACT FROM AUTHOR]

Expanding the renewable energy sources usage in power systems will help the government meet its energy policy goals of lowering emissions, ensuring high power supply reliability, and promoting spot markets with high competitivity. However, due to the intermittent nature of these sources, this will necessitate the mitigation of network vulnerabilities. High wind energy penetration in the grid could have an impact on the system frequency, voltage, real and reactive power response, and power quality of the system. The main objective of this paper is to investigate how the integration of wind farms in the Jalan Bani Bu Ali (JBBA) area will affect Oman's main interconnected system (MIS). Results show that the effect is minor on voltage and frequency stability by all disturbances taken into account. [ABSTRACT FROM AUTHOR]

The increasing penetration of wind energy in electric power systems leads to a great demand for flexible resources to regulate power fluctuations. This paper focuses on investigating the impacts of the operational flexibility of hydropower generation systems on reducing wind curtailment and load shedding in a hybrid hydro–wind power system. Considering timescale variabilities of wind power, the upward and downward regulation capabilities of hydro flexibility under sub-hour and hour dispatch scales are estimated. Based on developed flexible indicators, the ultimate access ratio of wind power penetration into the power system is obtained by using the estimated probability of insufficient regulation reserves. All these analyses are carried out under the wet and dry periods to better understand their differences with the hydro flexibility. The method and obtained results provide important guidance for the stable and high-efficiency operation of hybrid power systems. [ABSTRACT FROM AUTHOR]

With the strong advancement of the global carbon reduction strategy and the rapid development of renewable energy, compressed air energy storage (CAES) technology has received more and more attention for its key role in large-scale renewable energy access. This paper summarizes the coupling systems of CAES and wind, solar, and biomass energies from the perspective of system topology, and points out the advantages and limitations of each system. It is shown that the coupling of wind energy and CAES is mainly combined in series and in parallel, and sometimes part of the wind power can be converted into thermal energy when coupled to CAES. The coupling between solar heat and CAES is an important form of coupling between solar energy and CAES. Solar-heat-coupled CAES mainly uses solar energy to heat expander inlet air. The coupling forms of solar energy and CAES are based on various CAES forms, various heat heating sequences, reheating, bottom cycle, and other factors. The combination of biomass and CAES is generally based on biomass gasification power generation technology. In the future, a wind–solar–CAES multiple coupling system is expected to become a promising large-scale form for the utilization of renewable energy, and this integrated system has great potential as a system configuration, but has some technical challenges. [ABSTRACT FROM AUTHOR]

As the penetration rate of variable renewable energy such as wind power increases in the power system, the composition and balance of the system also change gradually. The intermittency of renewable energy poses great stability challenges to the traditional centralized generation and load-oriented transmission and distribution methods. Therefore, the Active Distribution Network Operator (ADNO) with distributed installation at the local level has a good application prospect in the new scenario. However, ADNO needs to improve its operational efficiency based on the types of local generation and storage devices and the nature of the market environment. To address this issue, this paper proposes a forecasting method that considers the coupling fluctuations of spot electricity prices and renewable energy, and a bi-level optimization operation method based on the Stackelberg game for optimizing the operation of small-scale ADNO under high wind power penetration rate. Simulation results show that the proposed methods achieve greater positive impact on the operational efficiency of ADNO than conventional methods. In addition, the proposed methods ensure the long-term profitability of ADNO, even with fluctuations in external factors. [ABSTRACT FROM AUTHOR]

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values are also discussed in this paper. Next, the voltage control methods for an HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a sudden reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aim to verify whether additional voltage control methods are effective to improve the performance of transient voltage. The voltage control method has been implemented in PSCAD/EMTDC, and the simulation results show that the QV control performs better than the droop control. In addition, when applying the voltage control technique during a three-phase fault, transient voltage nadir can be improved through either an HVDC transmission system or an AC transmission system. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources is one of the measures that have had a significant contribution in reducing greenhouse gas emissions while ensuring sustainable development. Hence, this necessitates the need to ensure a sustainable national socio-economic development pathway that supports low emissions through the development and use of renewable energy. This paper analyses data from a systematic review that was conducted to understand how research is approaching the state of public policies of renewable energy and climate change in Tanzania. The review screened more than 500 published papers and unpublished reports containing 120 unique studies related to renewable energy, climate change and sustainable development. Results indicate that renewable energy sources have the potential of contributing to the reduction of about two-thirds of the total global energy carbon dioxide emission. The results further indicate that renewable energy may save carbon dioxide for the range of global cumulative savings of about 220-560 GtCO2 in the period 2010-2050. The results also show that Tanzania has targeted to reduce greenhouse gas emissions by between 30% and 35% by 2030. Thus, more appropriate renewable energy policies would enable the country to further efficiently contribute to the global goal of reducing greenhouse gas emissions, while achieving its sustainable development. This underscores the need for Tanzania to adopt appropriate policies for the utilisation of renewable energy sources such as solar, wind, hydro and geothermal energy for the reduction of greenhouse gas emissions, while achieving its sustainable development goals. [ABSTRACT FROM AUTHOR]

This paper shows an increase in the robustness of a DFIG-based wind energy system when a predictive-repetitive controller in the d q reference frame is used for the control of the rotor current. This designing approach proposes a model predictive control with a receding horizon technique that uses the frequency decomposition of the reference signal as a filter. Furthermore, an augmented space-state model from the original plant model is obtained, and its implementation is addressed from the perspective of normal operating conditions of DFIG in wind energy systems. Additionally, this repetitive controller increases the robustness of the predictive control when a mismatch in machine parameters is considered. Experimental results presented in this paper endorse the advantages of this controller. [ABSTRACT FROM AUTHOR]

Global economy is developing rapidly and consequently energy requirements has been focused, particularly in developing countries. There are potentials of using renewable energies in the cities and Islands located in Iranian Seas. In this study, five locations in the Persian Gulf and the Gulf of Oman, combining of wind and solar energies have been considered. This paper evaluates the best locations for using different renewable energies in some important cities in the south of Iran. The paper presents a comparative study among different hybrid renewable energies (Wind and Solar) in five cities of Iran located in the coast of the Persian Gulf and the Gulf of Oman namely, Kish Island, Qeshm Island, Chabahar, Jask, and Genaveh. To evaluate the feasibility of using renewable energies in the above-mentioned locations, four types of building namely; hospital, large hotel, medium office, and strip mall have been analyzed. HOMER Software has been used to analyze and optimize different configurations. Considering the load profiles of chosen cases, the optimum solution for different configuration along with cost summary is obtained and analyzed. The simulation results presents that Kish Island owns the most load profile among other cities and PV-Diesel-Battery-Converter is the most suitable hybrid system, which possesses the optimum cost for the considered buildings. Moreover, Chabahar has mostly the most amount of carbon emission for the proposed case studies and owns the maximum lowest cost system among all considered cities except in the case of large hotel where Jask has the maximum initial capital cost. [ABSTRACT FROM AUTHOR]

The production of hydrogen is still a major challenge, due to the high costs and often also environmental burdens it generates. It is possible to produce hydrogen in emission-free way: e.g. using a process of electrolysis powered by renewable energy. The paper presents the concept of a research, experimental stand for the storage of renewable energy in the form of hydrogen chemical energy with the measurement methodology. The research involves the use of proton exchange membrane electrolysis technology, which is characterized by high efficiency and flexibility of energy extraction for the process of electrolysis from renewable sources. The system consist of PV panel, PEM electrolyzer, battery, programmable logic controller system and optional a wind turbine. Preliminary experimental tests results have shown that the electrolyzer can produce in average 158.1 cc/min of hydrogen with the average efficiency 69.87%. • Zero-emission hydrogen production is possible. • Hydrogen production using a proton exchange membrane (PEM) electrolyzer for Polish conditions. • Proposal for experimental studies on hydrogen production. [ABSTRACT FROM AUTHOR]

Renewable energy attracts increasing attention from both industry and academia under the context of carbon neutrality. For wind and solar energy, the strong dependence on natural processes results in the imbalance between energy production and real demands. Energy storage technologies, e.g., Compressed Air Energy Storage (CAES), are promising solutions to increase the renewable energy penetration. However, the CAES system is a multi-component structure with multiple energy forms involved in the process subject to high temperature and high-pressure working conditions. The CAES system is a complex process flowsheet consisting of charging and discharging process. The process should be optimized to achieve the best thermodynamic and economic performance. Under the optimal design conditions, it might lead to severe consequences once a failure occurs, e.g., harm to humans, the environment, and assets. Limited attention and scarce available information have been paid to the CAES system risk management yet. Hence, this paper applies the System-Theoretic Process Analysis (STPA), which is a top-down method based on system theory, to identify the CAES system safety hazards. The results are expected to provide a preliminary guideline for practitioners regarding the safety and reliability of the CAES system. As a result, a more reliable CAES system can contribute to a more flexible energy system with more efficient and economic utilization of fluctuating renewable energy. [ABSTRACT FROM AUTHOR]

Despite sustained interest in spatial planning approaches for steering renewable energy development, the effect of these practices remains poorly understood. This paper addresses this knowledge deficit through comparative analysis of the effects of spatial planning approaches on wind energy deployment in Italy and the UK. Our approach elucidates the different roles that spatial planning approaches can perform using a "modes of governing" framework that, innovatively, recognizes the unavoidable compromises involved in their construction. Several distinctive findings emerge. First, governments deploy spatial planning approaches with different governance purposes, thus explaining why the effects on RE outcomes can be ambiguous. Second, many of the challenges that beset spatial planning approaches arise not from technical-methodological issues but from difficult-to-resolve governance challenges of cross-scalar coordination. Third, we show that the efficacy of spatial planning approaches in shaping RE deployment is contextual in nature, reflecting how far their inherent compromises are accepted by key actors. [ABSTRACT FROM AUTHOR]

In order to deal with the increasingly severe energy shortage problem, to find new energy solutions and to alleviate the dual pressure of domestic energy and environment, building a new type of multi-energy complementary power system has become one of the hot issues in recent years. This paper presents an optimal scheduling model of building integrated energy system (BIES) based on the comprehensive utilization of electricity, heat and gas. Based on the traditional combined cooling, heating, and power (CCHP) system, this model adds wind power and photoelectric renewable energy power generation systems, ground source heat pump system and energy storage system. Then, taking the environmental cost and system operation and maintenance cost as the objective function, it is solved by using the improved multi-objective ant lion algorithm based on differential evolution. Finally, a building in Northeast China is taken as an example to verify the simulation. The simulation results show that the optimal scheduling model of building integrated energy system proposed in this paper can promote the consumption of renewable energy such as wind power and photoelectric, realize the peak cutting and valley filling of power load, effectively reduce the economic operation cost of the system, reduce carbon emissions and effectively solve the problem of environmental pollution to a certain extent. [ABSTRACT FROM AUTHOR]

In the present paper a techno-economic hydrogen production and transportation costs to export from Colombia to Europe and Asia were determined using the open-source Python tools, such as WindPowerLIB, PVLIB, ERA5 weather data, and the Hydrogen-2-Central (H2C) model. Calculations were performed as well for Chile, for comparison as a regional competitor. In addition, a detailed overview of Colombia's energy system and national efforts for a market ramp-up of renewable energy and hydrogen is provided. The application of the model in different scenarios shows Colombia's potential to produce green hydrogen using renewable energies. The prices estimated are 1.5 and 1.02 USD/kgH 2 for 2030 and 2050 with wind power, and 3.24 and 1.65 USD/kgH 2 for 2030 and 2050 using solar energy. Colombia can become one of the most promising hydrogen suppliers to Asian and European countries with one of the lowest prices in the production and transportation of green hydrogen. [Display omitted] • Open-source models were used to obtain costs of H 2 production and transportation. • LCOH of green H 2 using wind energy is 1.63 and 1.11 USD/kgH2 by 2030 and 2050. • LCOH of green H 2 using solar energy is 3.72 and 1.89 USD/kgH2 by 2030 and 2050. • Exporting H 2 to Asia by 2030 and 2050 costs 3.47 and 2.9 USD/kg, respectively. • Exporting H 2 to Europe by 2030 and 2050 costs 3.1 and 2.55 USD/kg, respectively. [ABSTRACT FROM AUTHOR]

Impact assessment can play an important role in global energy transition, delivering knowledge to identify and manage the impacts of renewable energy projects. Yet, there are enduring concerns about IA's efficacy for renewable energy development. Based on content analysis of IA applications for wind energy development in Canada, this paper examines the environmental and social impacts typically assessed across wind energy projects and the mitigation solutions proposed. Results indicate considerable imbalance between biophysical versus social impacts, including mitigation solutions. IAs include far more solutions for managing biophysical impacts than social ones, with impact-to-mitigation ratios of 1:4.3 and 1:1.3 respectively. Most mitigations focus on impact minimisation, followed by avoidance, and are often vague and imprecise regarding the timing, methods of implementation, and responsibility. Notwithstanding common impacts, mitigation actions that were common across projects were too vague or imprecise to support transferable practice to find efficiencies in assessment. Improved understanding the impacts of renewable energy projects and mitigation solutions, and learning from one project to the next, are foundational to advancing the role of IA the transition to renewable energy. [ABSTRACT FROM AUTHOR]

The construction and development of the Electricity Spot Market (ESM) are beneficial to the fair distribution of power resources and the improvement of power system regulation ability. The original ESM was not designed to include renewable energy. Since there is almost no marginal cost for renewable energy, the renewable energy can not copy the thermal power unit price model after participating in ESM. The prevalent Locational Marginal Price (LMP) mechanism within the extant ESM structure encounters limitations wherein optimal benefits accrue to buyers and sellers only under specific conditions. This paper thus introduces an innovative electricity pricing model and trading settlement strategy tailored to the characteristics of wind turbine-generated power. To begin, we devise a novel electricity pricing model grounded in the construction expenses and predictive precision intrinsic to renewable energy sources. Subsequently, in synergy with the ESM framework, we formulate a Bayesian game model to compute benefits contingent upon bid success probabilities. A pricing strategy based on Vickrey - Clarke - Groves (VCG) is selected, which pays the other generating strategy as an incremental cost by removing itself. Empirical evaluations affirm the efficacy and rationality of the proposed approach. The outcomes of our study not only validate its applicability but also lay the groundwork for a fresh theoretical paradigm underpinning energy trading modalities in future ESM contexts. [ABSTRACT FROM AUTHOR]

Green ammonia has potential as a zero-emissions energy vector in applications such as energy storage, transmission and distribution, and zero-emissions transportation. Renewable energy such as offshore wind energy has been proposed to power its production. This paper designed and analyzed an on-land small-scale power-to-ammonia (P2A) production system with a target nominal output of 15 tonnes of ammonia per day, which will use an 8 MW offshore turbine system off the coast of Nova Scotia, Canada as the main power source. The P2A system consists of a reverse osmosis system, a proton exchange membrane (PEM) electrolyser, a hydrogen storage tank, a nitrogen generator, a set of compressors and heat exchangers, an autothermal Haber-Bosch reactor, and an ammonia storage tank. The system uses an electrical grid as a back-up for when the wind energy is insufficient as the process assumes a steady state. Two scenarios were analyzed with Scenario 1 producing a steady state of 15 tonnes of ammonia per day, and Scenario 2 being one that switched production rates whenever wind speeds were low to 55% the nominal capacity. The results show that the grid connected P2A system has significant emissions for both scenarios, which is larger than the traditional fossil-fuel based ammonia production, when using the grid in provinces like Nova Scotia, even if it is just a back-up during low wind power generation. The levelized cost of ammonia (LCOA) was calculated to be at least 2323 CAD tonne−1 for both scenarios which is not cost competitive in this small production scale. Scaling up the whole system, reducing the reliance on the electricity grid, increasing service life, and decreasing windfarm costs could reduce the LCOA and make this P2A process more cost competitive. [ABSTRACT FROM AUTHOR]

In this paper, we consider spatially and technologically diversified portfolios of renewable energy resources (RES) on a European scale. These portfolios efficiently allocate wind and solar production capacity with a view on matching load and restricting conventional generation capacity in each country. We investigate the composition of optimal portfolios taking into account the existing cross-border transmission capacity as well as future expansion scenarios. For the purposes of our analysis, we develop several multi-criteria optimization models and apply them to a rich dataset of daily electricity load, RES capacity factors, and transmission capacity constraints for 32 European countries during the period 2010–2015. By exploring different scenarios for the composition of efficient portfolios and cross-border network connectivity, we quantify the effectiveness of the resource aggregation strategy in terms of reducing the energy production deficit or surplus in each country. Empirical evidence shows that the portfolio perspective provides a solid basis for strategic planning on the future expansion of the European grid. [ABSTRACT FROM AUTHOR]

In recent years, Taiwan has firmly committed itself to pursue the green energy transition and a nuclear-free homeland by 2025, with an increase in renewable energy from 5% in 2016 to 20% in 2025. Offshore wind power (OWP) has become a sustainable and scalable renewable energy source in Taiwan. Maritime Spatial Planning (MSP) is a fundamental tool to organize the use of the ocean space by different and often conflicting multi-users within ecologically sustainable boundaries in the marine environment. MSP is capable of definitively driving the use of offshore renewable energy. Lessons from Germany and the UK revealed that MSP was crucial to the development of OWP. This paper aims to evaluate how MSP is able to accommodate the exploitation of OWP in Taiwan and contribute to the achievement of marine policy by proposing a set of recommendations. It concludes that MSP is emerging as a solution to be considered by government institutions to optimize the multiple use of the ocean space, reduce conflicts and make use of the environmental and economic synergies generated by the joint deployment of OWP facilities and fishing or aquaculture activities for the conservation and protection of marine environments. [ABSTRACT FROM AUTHOR]

This work aims to find an optimal hybrid renewable system design using solar, wind energy, battery storage, thermal loads, thermal load controller (TLC), boiler, and a diesel generator (DG) for the considered site. The prefeasibility techno-economic analysis has been carried out using HOMER software to meet the load demand requirement of the village. For identifying winning system architecture, minimum net present cost (NPC), lowest cost of energy (COE), and the highest renewable fraction (RF) are used as the criteria. The obtained results show that the least cost-optimal hybrid system consists of 614kW-PV,850kW-WT,800kW-DG, 1212 no. of batteries and 591 kW converter along with TLC-2000kW, having minimum NPC: $5.48M, least COE: $0.272/kWh and highest RF:91.6% can provide 92% reliable power supply to onsite load demand of 4502.95kWh/day with 70% renewable sources in the considered site. This paper also presents a sensitivity analysis of the hybrid system with variations in load demand, diesel fuel price, project lifetime, and interest rate. [ABSTRACT FROM AUTHOR]

This paper provides a high-accuracy assessment of domestic demand-side management (DSM) approach in the context of distributed renewable energy sources (RES). To determine the potential of domestic DSM for households, a microgrid model of a typical UK residential estate was developed to simulate the impact of RES. The microgrid model comprises 15 UK households with appropriate allocation of washing machines, tumble dryers and dishwashers in accordance with the statistical data. In order to obtain a high-accuracy result, the power consumption of the microgrid model utilises real historical high-resolution data of household energy consumption and RES generation. Thereafter, 40% of distributed wind and solar energy is implemented in the model to produce two individual scenarios. The operation of the white appliances in the model is controlled using a domestic DSM based on a load shifting algorithm. The primary criterion of the DSM considered in this paper is the reduction in energy feedback to the grid in order to decrease the utilisation of the grid and to reduce the transmission losses. The results obtained from the model simulation are compared to the baseline model and discussed with respect to the possible benefits of implementation of domestic DSM under the impact of RES. It has been shown that the self-consumption ratio of the microgrid operating under the DSM is increased by 3% for both scenarios. The model analysis provides highly realistic results which can be used for efficiency assessment of various load shifting methods. [ABSTRACT FROM AUTHOR]

This paper uses the capability approach to analyse renewable energy developments on Aboriginal land in Australia's Pilbara and Kimberley regions. These regions in the north-west of Australia have very high rates of Indigenous land tenure, and are attractive for both solar and wind power generation, particularly as developing technology makes it economically feasible to transport power over large distances. They are also remote from Australia's electricity networks and often rely on expensive fossil fuels for electricity generation. Resident Aboriginal communities are among the most income-poor in Australia yet live in regions rich in renewable energy. Their ability to benefit from the opportunities offered by a transition to renewable sources of energy varies according to a number of factors. This paper examines the conditions under which Indigenous capabilities may be enhanced or inhibited, through examining three scales of energy generation: large-scale developments for export; remote utility-owned networks; and small-scale standalone off-grid applications. This paper will ask what capabilities can Indigenous people achieve from a just approach to a renewable energy transition in northern Australia, and what capabilities are required in order to gain maximum benefit from this current rapid energy transition? [ABSTRACT FROM AUTHOR]

The paper presents the general characteristics of the energy system of the Republic of Armenia, including the main existing challenges, development prospects, and directions. The shares of different types of renewable energy in the total energy resources, the possibilities of their use, and the factors promoting and hindering the development of this sector are presented in detail. The advantages of autonomous, multifunctional, hybrid systems and their development prospects are clarified. [ABSTRACT FROM AUTHOR]

Summary: The monitoring and control of renewable energy sources are extremely important to guarantee the operability of the system and the quality of the energy generated. Communication technologies play an important role in the success of these systems and, among them, power‐line communication (PLC) has shown itself to be a very promising and economically viable solution, as it uses the existing power infrastructure to transmit the monitoring and control information. In this context, this paper proposes a communication system based on the G3‐PLC standard associated with a median filter (MDF) to improve the robustness of the control operation of a wind power generation system (WPGS) composed of a doubly fed induction generator (DFIG) and a predictive controller. The MDF is employed to attenuate impulsive noise and distortions, caused by the degrading effects of the PLC channel, being possible to recover corrupted control information without the need to retransmit data packets. The complete system, that is, WPGS, G3‐PLC, and MDF, was modeled in a computational environment and analyzed over a realistic PLC channel model. Simulation results showed that the system is capable of operating with good quality, reducing latency, and enabling real‐time communication even under severe channel conditions. [ABSTRACT FROM AUTHOR]

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow problem, called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution operator in a single algorithmic framework. Additionally, an adaptive method is proposed to update the number of solutions evolved by each DE operator based on both the diversity of the population and the quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%. • Development of an adaptive method (AM) for optimizing diversity and solution quality. • Innovative constraint handling approach, progressively adding constraints for improved performance. • Incorporation of intermittent renewable energy models for realistic problem solving. • Extensive validation on IEEE 30-bus and IEEE 118-bus networks, outperforming state-of-the-art algorithms in cost, loss, and environmental impact reduction. [ABSTRACT FROM AUTHOR]

• A comprehensive operational cost function was established based on the deep peak shaving characteristics of thermal generators. • The impacts of different combinations of renewable energy penetration on the power system operation were analyzed. • The effect of energy storage deployment on improving flexibility in high penetration renewable energy systems were analyzed. Higher proportions of renewable energy are one of the most prominent features of future power systems. However, renewable energy, such as wind and PV power generation, is subject to inherent variability and uncertainty, which leads to fluctuations in electrical production and necessities flexibility enhancement to ensure sufficient adjustable resources responding to such fluctuations. This paper proposes to enhance the flexibility of renewable-penetrated power systems by coordinating energy storage deployment and deep peak regulation of existing thermal generators. First, the growing flexibility requirement in the presence of variable renewable energy is discussed and quantified using proposed indices. Then, we analyze the characteristics of thermal generators providing deep peak regulation, and establish a comprehensive operation cost function including coal consumption, wear-and-tear consumption, and oil consumption of thermal generators. On this basis, we propose a flexibility enhancement method coordinating battery energy storage capacity optimization and deep peak regulation of thermal generators, which aims at minimizing the total investment and operation costs while satisfying operating constraints on representative days. Extensive case studies on a modified IEEE-RST 24 system verified the proposed flexibility enhancement method under different scenarios. [ABSTRACT FROM AUTHOR]

The issue of large-scale retirements of renewable energy modules has attracted considerable attention from governments and the public worldwide. Using the Chinese wind and photovoltaic industries as examples, this paper, for the first time, employs a real options approach to explore the optimal time for energy firms to retire their power plants and to predict the future trend of renewable energy wastage from a bottom-up perspective. The results show that the optimal retirement time for the four subdivided categories ranges from 16 to 23 years. The later the investments are made, the earlier the decommissioning time comes and the lower the project returns. Furthermore, wind projects have been found to generate more revenue than PV projects for the same size, and the gap continues to widen. Offshore wind technology always has the longest optimal service life (18.62 years in 2022) and the greatest project returns (10.84 million CNY in 2022). Annual utilization hours, the renewable electricity price and the waste price can accelerate the retirement of plants and generate more revenue for energy companies, while the initial investment cost has a completely opposite effect. The first wave of PV retirements will occur in 2035 at 305.82 GW, while onshore wind will be in 2036 at 530.77 GW and offshore wind will not explode until 2040 at 65.84 GW. An assessment of potential policies suggests that for every 100 CNY increase in incentive strength, the retirement wave arrives 1 year earlier. In contrast, for every 100 CNY increase in the strength of penalties, the retirement wave is delayed by 1 year. In addition, we verify that the size of the plants does not affect the forecast of the retirement trend, indicating that the assumptions about installed capacity do not cause bias. [ABSTRACT FROM AUTHOR]

As an efficient tool for uncertainty quantification of renewable energy forecasting, prediction intervals (PIs) provide essential prognosis to power system operator. Merely improving the statistical quality of PIs with respect to calibration and sharpness cannot always contribute to the operational value for specific decision-making issue. In this paper, the cost-oriented prediction intervals are firstly proposed to achieve the joint improvement of forecasting quality and decision performance. In order to bridge the gap between forecasting and decision, a novel cost-oriented machine learning (COML) framework is established, which unifies nonparametric renewable power PI construction and decision-making. Formulated as a bilevel programming model, the COML minimizes the operational costs of decision-making process by adaptively adjusting the quantile proportion pair of PIs resulting from extreme learning machine based quantile regression. The hierarchical optimization model of the COML is equivalently simplified as a single level nonlinear programming problem. Then an enhanced branch-and-contract algorithm with innovative bounds contraction strategy is devised to efficiently capture the optimum of the single level problem with bilinear nonconvexity. Numerical experiments based on actual wind farm data simulate the online forecasting and decision process for wind power offering. Comprehensive comparisons verify the substantial superiority of the proposed COML methodology in terms of forecasting quality, operational value, as well as computational efficiency for practical application. [ABSTRACT FROM AUTHOR]