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Optimal Design of Hybrid Microgrid in Isolated Communities of Ecuador

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Journal of Modern Power Systems and Clean energy 2024年第2期12卷 488-499页

作者： Luis A.Pesantes Ruben Hidalgo-León Johnny Rengifo Miguel Torres Jorge Aragundi JoséCordova-Garcia Luis F.Ugarte Facultad de Ingeniería en Electricidad y Computación of Escuela Superior Politécnica del Litoral(ESPOL)University GuayaquilEcuador Department of Electrical Engineering at Universidad Técnica Federico Santa María SantiagoChile IEEE

In rural territories, the communities use energy sources based on fossil fuels to supply themselves with electricity, which may address two main problems: greenhouse gas emissions and high fuel prices. Hence, there is an opportunity to include renewable resources in the energy mix. This paper develops an optimization model to determine the optimal sizing, the total annual investment cost in renewable generation, and other operating costs of the components of a hybrid microgrid. By running a k-means clustering algorithm on a meteorological dataset of the community under study, the hourly representative values become input parameters in the proposed optimization model. The method for the optimal design of hybrid microgrid is analyzed in six operating scenarios considering:(1) 24-hour continuous power supply;(2) load shedding percentage;(3) diesel power generator(genset) curtailment;(4) the worst meteorological conditions;(5) the use of renewable energy sources including battery energy storage systems(BESSs);and(6) the use of genset. A mathematical programming language(AMPL) tool is used to find solutions of the proposed optimization model. Results show that the total costs of microgrid in the scenarios that cover 100% of the load demand(without considering the scenario with 100% renewables) increase by over 16% compared with the scenario with genset operation limitation. For the designs with power supply restrictions, the total cost of microgrid in the scenario with load shedding is reduced by over 27% compared with that without load shedding.

关键词： Battery energy storage system(BESS) isolated community microgrid renewable energy optimization

Carbon efficiency modeling and optimization of solar-powered cellular networks

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Science China(Information Sciences) 2024年第5期67卷 228-243页

作者： Yuxi ZHAO Xiaohu GE Wen YAN Tao HAN Yi ZHONG School of Electronic Information and Communications Huazhong University of Science and Technology Huawei Technology Co. Ltd.

As wireless communication traffic experiences rapid growth, the carbon emissions caused by the communication industry are also on the rise. To achieve “carbon neutrality”, researchers are considering the use of renewable energy sources to power cellular networks, thereby reducing carbon emissions. However, a challenge arises when using renewable energy, specifically owing to the unpredictable nature of both the energy consumption of the cellular network and the power generation from renewable sources. This inconsistency results in low renewable energy utilization and reduced carbon efficiency. Herein, we construct a carbon efficiency model of solar-powered cellular networks using practical data from solar radiation. We propose a mechanism that alternately optimizes the performance of the renewable energy network and the cellular network. This approach is based on convex optimization theory and the Dinkelback algorithm, and it leads to the design of a carbon efficiency optimization algorithm. This algorithm aims to improve the carbon efficiency of cellular networks and reduce their carbon emissions. Simulation results demonstrate that our optimization scheme yields a maximum improvement of 2.56 × 108bps/g in the carbon efficiency of the cellular network as compared to conventional power allocation schemes such as the traditional water filling method and heuristic energy sharing and charge/discharge algorithms.

关键词： cellular networks renewable energy carbon efficiency convex optimization theory dinkelbach

Optimization of biofuel supply chain integrated with petroleum refineries under carbon trade policy

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Frontiers of Chemical Science and Engineering 2024年第3期18卷 113-122页

作者： Wenhui Zhang Yiqing Luo Xigang Yuan Chemical Engineering Research Center School of Chemical Engineering and TechnologyTianjin UniversityTianjin300350China State Key Laboratory of Chemical Engineering Tianjin UniversityTianjin300350China

The use of fossil fuels results in significant carbon dioxide emissions.Biofuels have been increasingly adopted as sustainable alternatives to fossil fuel to address this environmental issue.Integrating petroleum refineries into biofuel supply chains is an effective approach to mitigating greenhouse gas emissions and improving environmental sustainability.In this study,an integrated supply chain optimization framework was established,considering the carbon trade policy.In addition,a mixed-integer nonlinear programming model was developed to optimize the selection of biomass suppliers,construction of pretreatment plants and biorefineries,integration of petroleum refineries,and selection of transportation routes with the objective of minimizing the total annual cost.An example is presented to illustrate the applicability of the model.The optimization results show that integrating petroleum refineries into biofuel supply chains effectively mitigates carbon emissions.Carbon trade policies can have a direct impact on the total annual cost and carbon emissions of the supply chain.

关键词： renewable energy biofuel supply chain carbon trade policy

Detection Method for Cascading Failure of Power Systems Based on Epidemic Model

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CSEE Journal of Power and energy Systems 2024年第3期10卷 1356-1370页

作者： Jian Xu Zhonghao He Siyang Liao Yuanzhang Sun Liangzhong Yao Deping Ke Jun Yang School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China IEEE

The early detection of cascading failure plays an important role in the safe and stable operation of the power system with high penetration of renewable energy.This paper proposes a fault propagation dynamic model based on the epidemic model,and further puts forward a method to detect the development of cascading failures.Through the simulation of the IEEE 39-bus and 118-bus systems,this model is proven to be valid and capable of providing practical technical support for the prevention of cascading failures in power systems with high penetration of renewable energy.This paper also provides an analysis method for the choice of different protection and control measures at each stage of cascading failure,which has critical significance and follow-up value.

关键词： Cascading failure complex network epidemic model fault propagation renewable energy weight method of game theory

Application research of compressed-air energy storage under high proportion of renewable energy

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Clean energy 2022年第2期6卷 305-312页

作者： Bin Feng Bo Yu State Grid Ningxia Electric Power Co.ltd YinchuanNingxiaChina State Grid Ningxia Economic and Technological Research Institute YinchuanNingxiaChina

China will strive to achieve a‘dual carbon’target:‘carbon peak’by 2030 and‘carbon-neutral’by 2060.In this context,improving the efficiency of renewable energy and reducing the use of thermal power are important ways to achieve the target.Clean,efficient and large-capacity energy-storage technology is the key to improving the utilization rate of renewable energy.First,this paper proposes to use compressed-air energy-storage technology instead of the old energy-storage technology to build an economical and environmentally friendly comprehensive energy park capacity optimization configuration model.Second,this paper uses the newly proposed improved chicken swarm optimization algorithm to solve the model,which is more accurate and faster.Finally,this paper analyzes a comprehensive energy park in north-west China.Through case analysis,it can be seen that the average utilization rate of renewable energy can reach 73.87%through the model proposed in this paper,while the average power-abandonment rate is only 9.32%.

关键词： renewable energy compressed-air energy storage power-abandonment rate chicken swarm optimization

Bi-level optimization based two-stage market clearing model considering guaranteed accommodation of renewable energy generation

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Protection and Control of Modern Power Systems 2022年第1期7卷 433-445页

作者： Qianya He Zhenjia Lin Haoyong Chen Xinyun Dai Yirui Li Xin Zeng School of Electric Power South China University of TechnologyGuangzhouChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina

The existing electricity market mechanisms designed to promote the consumption of renewable energy generation complicate network participation in market transactions owing to an unfair market competition environment,where the low cost renewable energy generation is not reflected in the high bidding price of high cost conventional energy generation.This study addresses this issue by proposing a bi-level optimization based two-stage market clearing model that considers the bidding strategies of market players,and guarantees the accommodation of renewable energy generation.The first stage implements a dual-market clearing mechanism that includes a unified market for trading the power generations of both renewable energy and conventional energy units,and a subsidy market reserved exclusively for conventional generation units.A re-adjustment clearing mechanism is then proposed in the second stage to accommodate the power generation of remaining renewable energy units after first stage energy allocations.Each stage of the proposed model is further described as a bi-level market equilibrium problem and is solved using a co-evolutionary algorithm.Finally,numerical results involving an improved IEEE 39-bus system dem-onstrate that the proposed two-stage model meets the basic requirements of incentive compatibility and individual rationality.It can facilitate the rational allocation of resources,promote the economical operation of electric power grids,and enhance social welfare.

关键词： Market clearing renewable energy Bidding strategy Guaranteed accommodation Bi-level optimization Fair competition

Does green growth in E-7 countries depend on economic policy uncertainty,institutional quality,and renewable energy?Evidence from quantile-based regression

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Geoscience Frontiers 2023年第6期14卷 224-233页

作者： Yongzhong Jiang Arshian Sharif Ahsan Anwar Phan The Cong Bawani Lelchumanan Vu Thi Yen Nguyen Thi Thuy Vinh College of Management Science Chengdu University of TechnologyChengdu 610059China Department of Economics and Finance Sunway Business SchoolSunway UniversitySubang JayaMalaysia University of Economics and Human Sciences in Warsaw WarsawPoland Faculty of Management Sciences Department of Business AdministrationILMA UniversityKarachiPakistan Faculty of Economics Thuongmai UniversityHanoiViet Nam Foreign Trade University HanoiViet Nam

Environmental degradation is one of the most debatable topics at international forums and it is considered a prime concern for the entire world.Therefore,researchers and policymakers have turned their attention from conventional economic growth to green growth.Although the existing literature has discussed several determinants of green growth,the impact of economic policy uncertainty(EPU),renewable energy consumption(RENE),and institutional quality(IQ)on green growth(GGDP)is relatively unexplored.Hence,this study is the earliest attempt to investigate the impact of EPU,IQ,and RENE on GGDP for emerging seven(E-7)countries from 1996 to 2019.In doing so,we apply panel quantile regression(PQR).The empirical findings delineate that EPU has a negative impact on GGDP,whereas IQ and RENE enhance the GGDP in E-7 countries.Based on the outcomes,this study suggests policy implications for achieving targets of the SDG 07,SDG 08,SDG 13,and SDG 16.The governments of these countries can achieve higher GGDP by ensuring political stability and reliable macroeconomic policies and through making such flexible policies that can easily control or address unpredictable future economic issues.

关键词： Green growth Economic policy uncertainty Institutional quality renewable energy Sustainable development goals

Hybrid renewable energy Resources Management for Optimal energy Operation in Nano-Grid

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Computers, Materials & Continua 2022年第5期71卷 2091-2105页

作者： Faiza Qayyum Faisal Jamil Shabir Ahmad Do-Hyeun Kim Department of Computer Engineering Jeju National UniversityJeju-siJeju Special Self-Governing Province63243Korea Department of IT Convergence Engineering Gachon UniversitySujeong-GuSeongnam-SiGyeonggi-Do461-701Korea

renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment,unlike non-renewable energy resources.However,they often fail to meet energy requirements in unfavorable weather conditions.The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load.In this paper,an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure.An actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management system.The objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization(PSO)named recurrent PSO(rPSO).Firstly,rPSO algorithm minimizes the installation cost for nanogrid.Thereafter,the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable resources.State-of-the-art optimization models,including Genetic Algorithm(GA),bat and different Mathematical Programming Language(AMPL)solvers,are used to evaluate the model.The study’s outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment.

关键词： Smart grid nanogrid distributed generation(DG) renewable energy optimization machine learning

Assessing renewable-energy potential and feasibility in Tehran’s buildings

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Clean energy 2022年第6期6卷 944-958页

作者： Mehrab Hemmati Farahani Marjan Namazzadeh Azin Hemmati Farahani Faculty of Engineering Islamic Azad UniversityArak BranchIran Faculty of Geography and Urban planning University of Yadgar Emam Shahr Rey Islamic Azad University TehranIran Faculty of Engineering University of Eyvanekey Iran

This article examines the results of using renewable energy to reduce the energy consumption of buildings significantly.In particular,it looks at the results in a country such as Iran,which has a high potential for using solar energy.A comparison of the energy consumption of selected case samples based on the type of ownership of private,government and municipal buildings in 22 districts of Tehran has been analysed.Using data for energy consumption and Strengths,Weaknesses,Opportunities,Threats analysis includes open and usable spaces for installing renewable-energy systems in 10%of public buildings,4%of private facilities and 10%of municipal buildings.The results of this study show that the average energy consumption of buildings in Tehran is almost four times the global average.Iran has~300 days of sunlight for installing solar panels in any place where solar energy is in direct contact with the Sun.Thus,it allows the building to use the energy absorbed by the discussions in all seasons.In 2050,this country could play a decisive role in producing renewable energy.In addition,solar energy may reduce fossil-fuel consumption and production costs.

关键词： renewable energy 22 districts of Tehran environmental SWOT analysis building energy consumption