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In order to cope with the problems of energy shortage and environmental pollution, carbon emissions need to be reduced and so the structure of the power grid is constantly being optimized. Traditional centralized power networks are not as capable of controlling and distributing non-renewable energy as distributed power grids. Therefore, the optimal dispatch of microgrids faces increasing challenges. This paper proposes a multi-strategy fusion slime mould algorithm (MFSMA) to tackle the microgrid optimal dispatching problem. Traditional swarm intelligence algorithms suffer from slow convergence, low efficiency, and the risk of falling into local optima. The MFSMA employs reverse learning to enlarge the search space and avoid local optima to overcome these challenges. Furthermore, adaptive parameters ensure a thorough search during the algorithm iterations. The focus is on exploring the solution space in the early stages of the algorithm, while convergence is accelerated during the later stages to ensure efficiency and accuracy. The salp swarm algorithm's search mode is also incorporated to expedite convergence. MFSMA and other algorithms are compared on the benchmark functions, and the test showed that the effect of MFSMA is better. Simulation results demonstrate the superior performance of the MFSMA for function optimization, particularly in solving the 24 h microgrid optimal scheduling problem. This problem considers multiple energy sources such as wind turbines, photovoltaics, and energy storage. A microgrid model based on the MFSMA is established in this paper. Simulation of the proposed algorithm reveals its ability to enhance energy utilization efficiency, reduce total network costs, and minimize environmental pollution. The contributions of this paper are as follows: (1) A comprehensive microgrid dispatch model is proposed. (2) Environmental costs, operation and maintenance costs are taken into consideration. (3) Two modes of grid-tied operation and island operation are considered. (4) This paper uses a multi-strategy optimized slime mould algorithm to optimize scheduling, and the algorithm has excellent results. [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]

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]

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]

Guangxi is a typical developing region on the southern coast of China. The current issues encountered in the region's development are that fossil energy accounts for about 80% of the energy structure, fossil fuels are heavily dependent on imports, and the self-sufficiency rate of resources is only 32%. These challenges have created a disparity between the current regional development state and the country's dual carbon target. Under the premise of comprehensively considering the multi-sectors of electricity, industry, transportation, and heating, this paper presents a study on the energy system transition towards low-carbon development for Guangxi in four steps. Firstly, to demonstrate EnergyPLAN's capability in energy modeling, a reference scenario for Guangxi is created using official yearbook data from 2020. Then, a short-term scenario is formulated to analyze the development of Guangxi's energy system during the 14th Five-Year Plan. Furthermore, two mid-term scenarios are established, revealing that Guangxi is anticipated to reach its carbon emission peak between 2025 and 2030. Finally, three long-term scenarios are proposed for Guangxi's energy system for 2050. These scenarios encompass the expansion of photovoltaics, nuclear, and wind power in the electricity system and emission reduction policies in the industrial, transportation, and heating sectors. As a result, compared with the 2020REF scenario, Guangxi can achieve a carbon emission reduction exceeding 57% and the share of non-fossil energy consumption can reach about 70% in the 2050 scenarios, despite a substantial increase in energy consumption, which makes it possible to achieve carbon neutrality in 2060 and to establish an energy system with less than 20% of fossil energy consumption. [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]

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 aims to analyze the information about protection of technologies related to distributed generation (DG) of electric energy, available in the Brazilian patent bank, in the period between 2011 and 2020. Considering that the energy sector has strategic role for companies and countries, analyzing technological trends in the area can help management and decision making. As a methodological procedure, (1) data were collected from the national database of the Instituto Nacional de Propriedade Industrial - INPI (National Institute of Industrial Property) -- in July 2020, (2) associated with keywords and the Classificação Internacional de Patentes - IPC (International Patent Classification) for research and (3) treated with the aid of Microsoft Excel and IBM SPSS Statistics version 25 software. The variables found and analyzed were: nature of the patent; order status; international classification; year of filing; publication of request; countries of origin of depositors; main depositors; state of origin of depositors; electrical system structure; and types of energy sources. The results demonstrated that the number of patent filings fluctuated over the years; that there was a significant growth in the number of deposits in the years that normative resolution n° 482/2012, responsible for regularizing DG in Brazil, was published or revised and that most of the technologies deposited are intended for power generation, with emphasis on that use wind energy. [ABSTRACT FROM AUTHOR]

The utilization of renewable energy sources aids in the economic development of a country. Among the various renewable energy sources, wind energy is more effective for electricity production. The doubly fed induction generator is an extensively known wind turbine generator for its partially rated power converters and dynamic performance. The doubly fed induction generator assists the wind turbine to function with a wide speed range. Hence, the steady-state performance analysis of a doubly fed induction generator helps enable it to operate efficiently at a specific wind turbine speed. In this paper, a 2 MW variable speed pitch regulated doubly fed induction generator with a speed range of 900—2000 rpm was opted for steady-state analysis. This was followed by the design and modelling of a doubly fed induction generator in Matlab/Simulink environment, and the analyses were performed using mathematical equations computed via Matlab coding. The steady-state magnitudes were calculated with rotor magnetization idr = 0. The closed-loop stator flux-oriented vector control is applied to the rotor side converter for controlling the designed doubly fed induction generator model. The simulation results were compared with computational values to establish a workable model with less than 10% error. The simulation model can be used for predicting the performance of the machine, fault analysis, and validation of existing DFIG at a steady state. [ABSTRACT FROM AUTHOR]

Wind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could be estimated with high accuracy. The main objective of this paper is to propose a novel approach for calculating wind energy potential. For this purpose, the Efficient Global Optimization (EGO) technique was proposed for fitting a statistical distribution to WS data and the performance of the technique was compared with genetic algorithm (GA), simulated annealing (SA), and differential evolution (DE). Performance metrics showed that EGO is providing better estimations compared with GA, SA, and DE. Based on Weibull parameters obtained by using EGO, potential WE and potential annual revenue were estimated for Gdańsk, which is the capital of Pomerania Voivodeship in Poland, in the case of having city-type wind turbines in the city center. Estimations for Gdańsk showed that city-type wind turbines might be helpful for producing electricity from WE in the city without being limited by constraints such as having a long distance between wind turbines and buildings. If such wind turbines were erected on the roofs of residential buildings, malls, or office buildings, there is a possibility that part of the electric energy needed for such buildings could be generated using WE. However, this topic should be further investigated from technical and financial perspectives. [ABSTRACT FROM AUTHOR]

This paper proposes a holistic framework of data-driven distributionally robust joint chance constrained economic dispatch (ED) optimization, which seamlessly incorporates deep learning-based optimization for effective utilization of renewable energy in power systems. By leveraging a deep generative adversarial network (GAN), an f-divergence-based ambiguity set of wind power distributions is constructed as a ball centered around the probability distribution induced by a generator neural network. In particular, the GAN is well suited for capturing complicated spatial and temporal correlations of wind power. Based upon this ambiguity set, a distributionally robust joint chance constrained ED model is developed to hedge against distributional uncertainty present in multiple constraints, without assuming a perfectly known probability distribution. The proposed deep learning based ED optimization framework greatly mitigates the conservatism inflicting on distributionally robust individual chance constrained optimization. Theoretical a priori bound on the required number of synthetic wind power data generated by GAN is explicitly derived for the multi-period ED problem to guarantee a predefined risk level. The effectiveness and scalability of the proposed approach are demonstrated in the six-bus and IEEE 118-bus systems by comparing with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

Remote areas and islands isolated from the main electric power system ensure reliability and stability of power supply using diesel generation. Due to the high purchase and transportation costs of diesel fuel, isolated communities are exploring other options for efficient and reliable power supply. Renewable energy sources can reduce operating costs, although are unable to achieve high penetration without expensive and complex enabling technologies such as energy storage. Furthermore, the stochastic and intermittent nature of renewable sources (i.e., wind and solar) makes the control system complex, decreasing power system reliability and requiring highly qualified personnel in local control centres. The problem becomes particularly acute when diesel engines are forced to operate at partial load, resulting in poor combustion efficiency and potential engine damage. This paper suggests a fuel-efficient control strategy, adopting low load diesel application to reduce fuel consumption and improve renewable energy penetration without overcomplicating the control architecture. A mathematical model is initially developed, then validated against real data, to facilitate comparative assessment of various control approaches. Optimised control methodologies are shown to deliver fuel savings of 16.7%, with a 14% increase in renewable energy penetration, in comparison to conventional management. [ABSTRACT FROM AUTHOR]

• Imported green e-H 2 is more expensive than e-H 2 produced in Germany and Finland. • Local supply of e-H 2 found to be more economical across all scenarios and years. • Transportation costs constitute 29–63% of the total imported e-H 2 cost. • Pipeline transmission may be cheaper than shipping for distances of 2000–2500 km. Widely available and low-cost solar photovoltaics and wind power can enable production of renewable electricity-based hydrogen at many locations throughout the world. Hydrogen is expected to emerge as an important energy carrier constituting some of the final energy demand; however, its most important role will be as feedstock for further processing to e-fuels, e-chemicals, and e-steel. Apart from meeting their own hydrogen demand, countries may have opportunities to export hydrogen to countries with area limitations or higher production costs. This paper assesses the feasibility of e-hydrogen imports to Germany and Finland from two case regions with a high availability of low-cost renewable electricity, Chile and Morocco, in comparison to domestic supply. Special attention is paid to the transport infrastructure, which has a crucial impact on the economic viability of imports via two routes, shipping and pipelines. This study has found that despite lower e-hydrogen production costs in Morocco and Chile compared to Germany and Finland, additional transportation costs make imports of e-hydrogen economically unattractive. In early 2020s, imported fuel costs are 39–79% and 34–100% higher than e-hydrogen produced in Germany and Finland, respectively. In 2050, imported e-hydrogen is projected to be 39–70% more expensive than locally produced e-hydrogen in Germany and 43–54% in the case of Finland. e-Hydrogen may become a fuel that is mostly produced domestically and may be feasible for imports only in specific locations. Local e-hydrogen production may also lower dependence on imports, enhance energy security, and add jobs. [ABSTRACT FROM AUTHOR]

The rapidly growing state of energy consumption and the urgency of mitigating the harmful effects of climate change have accelerated our transition to renewable energy. This paper proposes a multi-level framework for exploring the global competition to develop renewable energy technologies. Through a combination of text mining techniques and by analyzing a corpus of patents covering six renewable energy technologies from 1970 to 2019, we reveal the lifecycle of these technologies, the original sources of these technologies, their potential markets, and the different supply and demand patterns of the major countries/regions involved. The results show that solar and wind energy are currently the most widely used renewable energy sources, yet biomass is the only energy source still in its growing stage. China's patents have seen a rapid upward trend, spurred on by strong policy promotion, which runs counter to the decrease in patent applications seen in most other major countries in this area. However, China's technology imports still far outweigh its exports, indicating that there is still a sizeable gap between China and some of the more developed countries like the United States, Germany, France, and the United Kingdom in terms of high-quality, high-value patents. Accordingly, China, the United States, and Japan are currently the leading in the world's renewable energy markets. That said, the market potential of Europe, Canada, and Australia should not be underestimated. These and more themes are discussed from a political, economic, environmental, and global governance perspective. This paper provides useful insights into the global renewable energy technology landscape, particularly the competitive dynamics at play. The aim is to guide policy makers or managers on the next steps in our progress toward applying and using renewable energy at scale. [ABSTRACT FROM AUTHOR]

This paper proposes a multisource multiproduct framework for coupled multicarrier energy supplies with a biogas–solar–wind hybrid renewable system. In this framework, the biogas–solar–wind complementarities are fully exploited based on digesting thermodynamic effects for the synergetic interactions of electricity, gas, and heating energy flows, and a coupling matrix is formulated for the modeling of production, conversion, storage, and consumption of different energy carriers. The multienergy complementarity of biogas–solar–wind renewable portfolio can be utilized to facilitate the mitigation of renewable intermittency and the efficient utilization of batteries, and a multicarrier generation scheduling scheme is further presented to dynamically optimize dispatch factors in the coupling matrix for energy-efficient conversion and storage, while different energy demands of end-users are satisfied. The proposed methodology has been fully tested and benchmarked on a stand-alone Microgrid over a 24-h scheduling horizon. Comparative results demonstrate that the proposed scheme can lower the battery charging/discharging actions as well as the degradation cost, and also confirm its capability to accommodate high penetration of variable renewables. [ABSTRACT FROM AUTHOR]

Wind power has become one of the cost-effective options for improving the energy mix, while the wind farm installations reach higher shares by new capacity additions in Turkey, similar to many other countries, in order to support the sustainable development targets. Various methodologies are implemented and applied for planning and optimizing energy systems of countries, taking into consideration the energy, economy, and ecology aspects as a whole. The objective of this paper is to demonstrate the implications of "2023 energy targets" policy in terms of wind power. A futuristic scenario was tailored and applied to a comprehensive energy model for the energy system of Turkey. The official wind energy vision and goal of Turkey were analyzed by applying a scenario based on 20,000 MW wind power capacity installation by the year 2023. The results indicated that, if applied, this action will increase the share of wind power utilization to the level of 16% in the total renewables while the installed wind capacity will reach 18%. Finally, the total cost of this strategic target which doubles the installed capacity and electricity generation by wind power, including the respective investment costs and subsidizations results, were calculated as $24.78 billion on the analysis horizon. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present an alternative supply of electricity to residential buildings and presented and analyzed methods to increase energy efficiency. The solution chosen and presented in this paper is the conversion of wind energy using a wind system consists of wind generator, inverter, batteries batteries, diesel generator.Efficient energy use is widespread concern regarding the efficient use of material resources of any kind. Efficient energy has become an economic necessity, condition expressed concentrated by reducing the share of energy costs in total production costs. [ABSTRACT FROM AUTHOR]

Energy is essential for socio-economic development and due to the increase in energy consumption it is necessary to look for renewable and clean energy over the coming decades. Wind energy has received more attention than other sources due to better economic conditions as well as lack of environmental pollution and unlimited wind resources. This paper describes a practical method for measuring the potential of wind resources with the ability to generate electricity, using the geographic information system and considering the selection criteria of wind farms. The present study analyzed a multi-criteria decision support system to define wind energy resources in western Iran. In the method of calculating wind potential in this paper, the desired items are considered with equal importance and these criteria include technical, environmental, economic and geographical factors. The aims of this research are measuring the potential of areas suitable for generating electricity from wind energy for large turbines according to international standards, stating the standards and criteria for measuring the potential of wind resources and finally implementing the items mentioned in regional electricity. The results show that assuming the use of Gamesa G58 turbine, a maximum of 1897 MW of wind power can be generated in the study area, which is 26% of the region's electricity supply in 2025 horizon. The method used in this study can be applied for future wind potential measurements and it is recommended to be integrated with fuzzy AHP method to enhance the accuracy of the results. • Describing a practical method for measuring the potential of wind resources with the ability to generate electricity, using the geographic information system and considering the selection criteria of wind farms. • Measuring the potential of areas suitable for generating electricity from wind energy for large turbines according to international standards. • Obtaining the necessary factors to select suitable locations for wind farms in Iran's Western Regional Electricity in order to provide criteria based on GIS and evaluating their impact. [ABSTRACT FROM AUTHOR]

Improving the efficiency of renewable energy and electricity utilization is an urgent problem for China under the objectives of carbon peaking and carbon neutralization. This paper proposes an optimization scheduling method of electric vehicles (EV) combined with wind and photovoltaic power based on the Frank-Copula-GlueCVaR. First, a joint output model based on copula theory was built to describe the correlation between wind and photovoltaic power output. Second, the Frank-Copula-GlueCVaR index was introduced in a novel way. Operators can now predetermine the future wind-photovoltaic joint output range based on this index and according to their risk preferences. Third, an optimal scheduling model aimed at reducing the group charging cost of EVs was proposed, thereby encouraging EV owners to participate in the demand response. Fourth, this paper: proposes the application of a Variant Roth–Serve algorithm; regards the EV group as a multi-intelligent group; and finds the Pareto optimal strategy of the EV group through continuous learning. Finally, case study results are shown to effectively absorb more renewable energy, reduce the consumption cost of the EV group, and suppress the load fluctuation of the whole EV group, which has a practical significance and theoretical value. [ABSTRACT FROM AUTHOR]

[Display omitted] • Classifications and strategies of NZEBs were reviewed. • Multi-criteria analysis supports NZEB designing. • Renewable energy supply options for NZEBs are summarized. • Cost-benefit analysis and life cycle assessment needed for criterion evaluation. Decarbonizing the building sector is extremely important to mitigating climate change as the sector contributes 40% of the overall energy consumption and 36% of the total greenhouse gas emissions in the world. Net-zero energy buildings are one of the promising decarbonization attempts due to their potential of decreasing the use of energy and increasing the total share of renewable energy. To achieve a net-zero energy building, it is necessary to decrease the energy demand by applying efficiency enhancement measures and using renewable energy sources. Net-zero energy buildings can be classified into four models (Net-Zero Site Energy buildings, Net-Zero Emissions buildings, Net-Zero Source Energy buildings, and Net-Zero Cost Energy buildings). A variety of technical, financial, and environmental factors should be considered during the decision-making process of net-zero energy building development, justifying the use of multi-criteria decision analysis methods for the design of net-zero energy buildings. This paper also discussed the contributions of renewable energy generation (hydropower, wind energy, solar, heat pumps, and bioenergy) to the development of net-zero energy buildings and reviewed its role in tackling the decarbonization challenge. Cost-benefit analysis and life cycle assessment of net-zero energy building designs and their challenges were reviewed to shape the priorities of future development. It is important to develop a universal decision instrument for optimum design and operation of net-zero energy buildings. [ABSTRACT FROM AUTHOR]

In light of the global effort to limit the temperature rise, many cities have undertaken initiatives to become climate-neutral, making decentralized urban energy production more relevant. This paper addresses the potential of urban wind energy production with small wind turbines, using Berlin as an example. A complete framework from data selection to economic feasibility is constructed to enable the empirical assessment of wind energy for individual buildings and Berlin as a whole. Based on a detailed dataset of all buildings and hourly wind speed on a 1 km2 grid, the results show that multiple turbines on suitable buildings can significantly contribute to households' energy consumption but fall short of covering the full demand. For individual households, our economic evaluation strongly recommends the self-consumption of the produced electricity. The findings suggest that while the use of small wind turbines should be continuously encouraged, exploring other renewable resources or combination of wind and photovoltaic energy in the urban environment remains important. [ABSTRACT FROM AUTHOR]

In 2015, Romania was the first country in Europe that achieved EU targets regarding the share of renewables in the generation mix, far ahead of the 2020 deadline. Starting with the energy structure in Romania, the paper: (1) analyses the evolution of the main indicators in the renewable energy sector, (2) discloses the perspectives of renewable energy in Romania synthesizing the main trends of development in the field, and (3) analyses the challenges facing with the development of renewable energy in Romania. Based on analyzing the exploratory data, the paper makes a preliminary prediction of the development of the sector for future decades and proposes targeted countermeasures and suggestions. Romania still has unexploited potential concerning renewable energy sources. Since Romania registered continuous economic growth, the demand for electricity is steadily growing, and this trend is expected to continue. Additionally, Romania could introduce a support mechanism for developing the potential of unexploited existing resources. The results of the present study may be useful for further research regarding public policies for the development of renewable energy. Furthermore, it can represent a useful analysis in order to identify future trends of renewable energy in Romania. [ABSTRACT FROM AUTHOR]

At present, renewable energy installations are expanding to solve both environmental problems and expensive energy fuel import prices in isolated areas. However, in a small-scale power system, rapid output fluctuations of renewable energy may cause power quality problems such as voltage and frequency fluctuations in the power system. To solve this problem, the local government of Jeju Island in South Korea implemented a megawatt (MW)-class pilot project to stabilize the output power of wind turbines using an energy storage system (ESS). In this project, a 0.5 MWh lithium-ion battery was connected to a 3 MW wind turbine via 1 MW power conversion system (PCS). In this paper, the field test results were divided into four categories as follows. First, the performance of stabilizing the output of the wind turbine using ESS was confirmed. Second, the control performance of the ESS was confirmed when the wind turbine suddenly stopped due to an accident. Third, it was confirmed that the ESS discharged energy into the power system after the stabilization of the wind turbine output. Fourth, the reasons for the failure of the ESS to control output stabilization of the wind turbine were analyzed through MATLAB simulation. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources, especially wind energy, has been on the rise throughout power systems worldwide. Due to this relatively new introduction, the integration of wind energy is often not optimized. Moreover, owing to the technical constraints and transmission congestions of the power network, most of the wind energy has to be curtailed. Due to various factors that influence the connectivity of wind energy, this paper proposes a well-organized posterior multi-objective (MO) optimization algorithm for maximizing the connections of wind energy. In this regard, the dynamic thermal rating (DTR) system and the static VAR compensator (SVC) have been identified as effective tools for improving the loadability of the network. The propose MO algorithm in this paper aims to minimize: (1) wind energy curtailment, (2) operation cost of the network considering all investments and operations, also known as the total social cost, and (3) SVC operation cost. The proposed MO problem was solved using the non-dominated sorting genetic algorithm (NSGA) II and it was tested on the modified IEEE reliability test system (IEEE-RTS). The results demonstrate the applicability of the proposed algorithm in aiding power system enhancement planning for integrating wind energy. [ABSTRACT FROM AUTHOR]

Renewable energy technological innovation is greatly influenced by renewable energy markets and policies. In this regard, the paper decomposes nine influencing factors of patents of a specific renewable energy technology using the extended logarithmic mean Divisia index (LMDI) method from 2001 to 2015. The differences in a specific renewable energy technological innovation and development during the three Five-Year Plan periods is prioritized at the national level. The contribution of the increase in patents of renewable energy technologies mainly lies in the patents of solar energy technology and wind energy technology, but during the 12th Five-year Plan period, the increments of their patent counts significantly decline. Due to priority given to the development of innovation in a specific renewable energy technology, the improvement in the efficiency of R&D spending, the increases in the share of R&D spending and the share of renewable energy, low carbon economy concept advocacy and carbon scale expansion, the patent counts of a specific renewable energy technology will increase. Additionally, the factors affecting innovation in a specific renewable energy technology at the different economic development levels, as well as different resource distribution levels are investigated. • The extended LMDI method is used to decompose nine factors. • Focusing on renewable energy innovation during the three Five-Year Plan periods. • Discussing the issue based on the economic development levels. • Discussing the issue based on resource distribution levels. [ABSTRACT FROM AUTHOR]

An optimal operation system is a potential solution to increase the energy efficiency of a power network equipped with stochastic Renewable Energy Sources (RES). In this article, an Optimal Power Flow (OPF) problem has been formulated as a single and multi-objective problems for a conventional power generation and renewable sources connected to a power network. The objective functions reflect the minimization of fuel cost, gas emission, power loss, voltage deviation and improving the system stability. Considering the volatile renewable generation behaviour and uncertainty in the power prediction of wind and solar power output as a nonlinear optimization problem, this paper uses a Weibull and lognormal probability distribution functions to estimate the power output of renewable generation. Then, a new Golden Ratio Optimization Method (GROM) algorithm has been developed to solve the OPF problem for a power network incorporating with stochastic RES. The proposed GROM algorithm aims to improve the reliability, environmental and energy performance of the power network system (IEEE 30-bus system). Three different scenarios, using different RES locations, are presented and the results of the proposed GROM algorithm is compared to six heuristic search methods from the literature. The comparisons indicate that the GROM algorithm successfully reduce fuel costs, gas emission and improve the voltage stability and outperforms each of the presented six heuristic search methods. [ABSTRACT FROM AUTHOR]

It is believed that renewable energy may become a dominant energy in the future. However, whether renewable energy can promote industry development like the use of fossil energy is still unknown. This paper uses social accounting matrix (SAM) multiplier model to analyze the economic effects of renewable and coal energy in China. The transmission mechanisms of renewable and coal energy on production factors are also compared from the perspective of sector industry chain based on the structural path analysis (SPA) analysis method. We found that; renewable energy plays a stronger role in promoting the national economy than coal energy. Meanwhile, renewable energy can better promote the upgrading of the industrial structure compared with coal energy. Additionally, renewable energy affects economic development, mainly through the intermediate industries such as electrical machinery manufacturing and transportation, warehousing and service industries. These findings provide further insights into the influence path of renewable energy, which yields important implications for reasonably designing and choosing new energy development planning. [ABSTRACT FROM AUTHOR]