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1st IEEE International Conference on Energy Internet (ICEI)

作者： Yi, Yue Yuan, Zhichang Ji, Yirun Tsinghua Univ State Key Lab Secur Control & Simulat Power Syst Dept Elect Engn Beijing Peoples R China Southeast Univ Sch Elect Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509057597

As an important means to achieve energy internet, DC distribution network has great research significance. This paper focuses on the topology of DC distribution network. Considering the power quality and economy, a mathematical model of power flow optimization is proposed and solved in Matlab. The analysis of the results shows that the method is reasonable and effective. Based on the optimization results, voltage deviation and power loss are compared in different topologies, and the operation costs are also calculated. Taking the construction cost into account, the circle topology should be selected. The conclusion provides a reference for DC distribution network planning.

关键词： DC distribution network topology power flow optimization

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power flow optimization in a microgrid with two kinds of energy storage

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2016年第3期35卷 860-870页

作者： Rigo-Mariani, R. Roccuzzo, V. Sareni, B. Repetto, M. Robaum, X. Univ Toulouse LAPLACE UMR CNRS INPT UPS Site ENSEEIHT Toulouse France Politecn Torino Dipartimento Energia Turin Italy

Purpose - The purpose of this paper is to present the optimization of the power flows inside a microgrid with renewable sources and two kinds of storage. The considered microgrid consists in commercial buildings with maximum daily peak value of 50 kW, photovoltaic arrays with total capacity of 175 kW, a 50 kW/50 kWh high speed flywheel storage and a 50 kW/50 kWh set of Li-ion accumulators. Design/methodology/approach - The power flows in the microgrid are optimized the day ahead at one hour discretization in order to minimize the electric bill. Several scheduling strategies are proposed for solving the corresponding optimization problem including standard deterministic methods, stochastic algorithms and hybrid heuristics. Findings - All scheduling strategies investigated in the paper are compared with regard to their accuracy and computational time. Originality/value - Beyond the comparison of different algorithms devoted to the power flow optimization problem, the authors approach also addresses the integration of battery ageing in the scheduling strategy.

关键词： Battery ageing Mixed integer linear programming Niching evolutionary algorithms power flow optimization Smart grid

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Load Forecast of a University Building for Application in Microgrid power flow optimization

Load Forecast of a University Building for Application in Mi...

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IEEE International Energy Conference (ENERGYCON)

作者： Gulin, Marko Vasak, Mario Banjac, Goran Tomisa, Tomislav Univ Zagreb Fac Elect Engn & Comp Lab Renewable Energy Syst Zagreb 41000 Croatia

ISBN: (纸本)9781479924493

Microgrid is defined as a cluster of distributed generation sources, storages and loads that cooperate together in order to improve power supply reliability and overall power system stability. Short-term power production and load profile prediction is very important for power flow optimization in a microgrid, thus enhancing the management of distributed generation sources and storages in order to improve the microgrid reliability, as well as the economics of energy trade with electricity markets. However, short-term load prediction is a complex procedure, mainly because of the highly nonsmooth and nonlinear behaviour of the load time series. In this paper we develop and verify a neural-network-based short-term load profile prediction model. Neural network inputs are lagged load data, as well as meteorological and time data, while neural network output is load at the particular moment. Neural network training and validation is performed on load data recorded at University of Zagreb Faculty of Electrical Engineering and Computing, and on meteorological data obtained from Meteorological and Hydrological Service of Croatia, in period 2011-2013.

关键词： University Building Load Forecast Microgrids power flow optimization Neural Networks

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Load Forecast of a University Building for Application in Microgrid power flow optimization

Load Forecast of a University Building for Application in Mi...

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IEEE International Energy Conference

作者： Marko Gulin Mario Vasak Goran Banjac Tomislav Tomisa University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Renewable Energy Systems

ISBN: (纸本)9781479924509

关键词： University Building Load Forecast Microgrids power flow optimization Neural Networks

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Planning Model for Energy Routers Considering Peer-to-Peer Energy Transactions Among Multiple Distribution Networks

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CSEE Journal of power and Energy Systems 2024年第3期10卷 1026-1043页

作者： Meifu Chen Mingchao Xia Qifang Chen School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China IEEE

A high proportion of renewable energy affects the power quality of distribution networks,and surplus energy will be sold to the upstream grid at a low *** this paper,considering peer-to-peer energy transactions,the energy router-based multiple distribution networks are analyzed to solve the above problems and realize collaborative consumption of renewable ***,the investing cost of an energy router is high,and research on the economic operation of energy routers in distribution networks is ***,this paper establishes a planning model for energy routers considering peer-to-peer energy transactions among distribution networks,and explores the benefits of peer-to-peer energy transactions through energy router based multiple distribution networks.A structure of an energy router suitable for peer-to-peer energy transactions is selected,and a power flow calculation model based on a multilayer structure is *** energy router’s scheduling model is established,and unique functions of the energy router and revenue of each distribution network are considered.A power flow calculation model based on peer-to-peer interconnection of multiple distribution networks through energy routers is also ***,simulation results verify the effectiveness of the proposed planning *** show that peer-topeer energy transaction among distribution networks through energy routers can effectively reduce the comprehensive cost of distribution networks,significantly improve the power quality of the distribution networks,and reduce the impact of power fluctuation on the upstream grid incurred by the distribution network.

关键词： Capacity allocation energy router multiple distribution networks peer-to-peer energy transaction power flow optimization

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Shared energy storage configuration in distribution networks: A multi-agent tri-level programming approach

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APPLIED ENERGY 2024年 372卷

作者： Xie, Yulong Li, Lee Hou, Tianyu Luo, Kang Xu, Zhenyu Dai, Mingcheng Zhang, Lixiong Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Wuhan Natl High Magnet Field Ctr Wuhan 430074 Peoples R China

Shared energy storage has the potential to decrease the expenditure and operational costs of conventional energy storage devices. However, studies on shared energy storage configurations have primarily focused on the peer -to -peer competitive game relation among agents, neglecting the impact of network topology, power loss, and other practical factors on energy storage configuration. Additionally, they do not differentiate between various roles of agents, such as shared energy storage operators, electricity consumers, and distribution network operators. To address the challenges presented by the complex interest structures, diverse usage patterns, and potentially sensitive location associated with shared energy storage, we present a multi -agent model for shared energy storage services that takes into account the perspectives of different actors in distribution networks. We develop a tri-level programming model for the optimal allotment of shared energy storage and employ a combination of analytical and heuristic methods to solve it. A case study demonstrates that our model can attain effective allocation of shared energy storage, take into account the interests of multiple parties, and converge well. We examine the impacts of different energy storage service patterns on distribution network operation modes and compare the benefits of shared and non -shared energy storage patterns. By analyzing data on the cost of operating distribution networks, voltage stability, and distributed power consumption, we investigate the potential advantages of the multi -agent distributed shared energy storage service pattern in distribution networks. Our research provides valuable insights into implementing shared energy storage on a large scale in distribution networks.

关键词： Shared energy storage Distributed energy storage Tri-level programming Multi-agent decision power flow optimization Kkt conditions Heuristic algorithm

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A Q-learning-based Multi-timescale Resilience Enhancement Approach for power Grids with High Renewables 2

A Q-learning-based Multi-timescale Resilience Enhancement Ap...

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IEEE 2nd International Conference on power Science and Technology (ICPST)

作者： Huang, Yanting Zhong, Qing Wang, Akang Lin, Shunjiang Peng, Chaoyi Lei, Shunbo Chinese Univ Hong Kong Sch Sci & Engn Shenzhen Peoples R China Shenzhen Res Inst Big Data Shenzhen Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China China Southern Power Grid Power Dispatch & Control Ctr Guangzhou Peoples R China

ISBN: (纸本)9798350349047;9798350349030

power grid resilience is critically undermined by extreme weather events, especially when coupled with uncertain renewable energy generation, which can lead to a severe power outage. When facing such outages, it is essential for system operators to restore damaged lines in a sequence that maximizes the overall power supply. Identifying the optimal restoration sequence can be cast as a multi-stage problem where at each stage a single line is first restored in an hourly basis and then numerous power flow problems within the timescale of minutes are optimized under the resulting network topology. Evaluating the economic effect of restoring a specific line entails the optimization of power flow problems with time-varying renewables, lacking a closed-form expression. To address this, we employ the Q-learning algorithm, utilizing a well-designed Q-function to approximate the effect of restoring each line and embedding such a function into a training process. Simulations on the IEEE 33-Bus and IEEE 39-Bus Systems confirm the efficacy of the proposed approach, showcasing significant enhancements in resilience and recovery capabilities.

关键词： power Grid Resilience Q-learning Algorithm power flow optimization Renewable Energy Generation Multi-timescale

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Reactive-voltage coordinated control of offshore wind farm considering multiple optimization objectives

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY SYSTEMS 2022年 136卷 107602-107602页

作者： Tan, Hongtao Li, Hui Yao, Ran Zhou, Zhiting Liu, Renkuan Wang, Xiao Zheng, Jie Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400044 Peoples R China CSSC Haizhuang Windpower Co Ltd Chongqing 400021 Peoples R China

Reactive power-voltage (Q-V) control of wind turbine (WT) is an effective method to realize voltage control of a grid-connected wind farm system. However, the variation in the output reactive power of WTs would aggravate the system power loss and converter electro-thermal stress. That is, it would reduce the system economy and accelerate the aging failure process of wind power converters. Considering this, a multi-objective Q-V coordi-nated control strategy for wind farms considering voltage deviation, converter junction temperature, and power loss is proposed in this paper. In this method, the reactive power instruction matrix of the WTs is used as the decision variable, and the system voltage deviation, power loss, and converter junction temperature are used as the state variables. A linear reactive power flow optimization model for wind farms based on the sensitivity analysis method is proposed to map the coupling relationship between decision variables and state variables. It is aimed at enhancing the voltage control of the system while considering the junction temperature of the converter and active power loss of the system. In addition, two control modes are designed to achieve a trade-off among optimization objectives. A wind farm power-flow model and RT-Lab semi-physical simulation are used for verification. The results show that the proposed method can improve the overall performance of the system compared with other methods.

关键词： Offshore wind farms Voltage control Coordinated control Sensitivity analysis power flow optimization Junction temperature

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Multi-time Scale Optimal power flow Strategy for DC Distribution Network Based on Model-driven

Multi-time Scale Optimal Power Flow Strategy for DC Distribu...

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IEEE/IAS Industrial and Commercial power System Asia (IEEE I and CPS Asia)

作者： Song, Feng Zhang, Xueqing Kang, Kai Dong, Le Xiong, Dang Sun, Chenhao State Grid Shandong Elect Power Co Yantai Power Supply Co Yantai Peoples R China Shandong Univ Sci & Technol Sch Elect & Automat Engn Qingdao Peoples R China

ISBN: (纸本)9798350339345

In order to realize the optimal power flow under multiple time scales and multiple operation modes, the prediction results and power grid status are included in the optimization model simultaneously, and a power flow optimization strategy combining day-ahead and day-ahead optimization is proposed. According to the actual operation expectations, the objective function variable weight is adopted to adjust;The intra-day optimization combines the model predictive control system with super-short-term forecast, and plays the buffering role of energy storage to realize the tracking of scheduled distributed power output. In addition, give full play to the advantages of simplicity and high feasibility of knee search, and realize the global optimization of multi-objective optimization solution. The results show the practicability of this strategy.

关键词： DC distribution network power flow optimization Model driven Model prediction Knee search Multiple time scales

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Optimizing power flow with Hvdc Lines and Facts for Improved power System Stability

Optimizing Power Flow with Hvdc Lines and Facts for Improved...

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2023 International Conference on power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Karthikeyan, M.P. Nisha Garg, Raghav Department of Computer Bangalore India Noida Institute of Engineering and Technology Department of Electronics and Communication Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350357769

The increasing expenses incurred in the establishment of transmission networks, in conjunction with the essential function these networks serve in reorganized settings, highlight the need of using Flexible AC Transit System devices. The ideal placement and capacity distribution for Thyristor-Controlled State Capacitor in networks of transmission are important factors that are covered in this research. The suggested approach develops an objective function with the dual goals of reducing losses and increasing server capacity. Both technological and economic viewpoints are used in the inquiry, and the results are described appropriately. The results of the simulation demonstrated the effectiveness of the suggested approach in terms of both technical and financial factors. The infrastructure's load index significantly improved as a result of this compensation, rising by 23.02%. In addition, the economic method reduced power losses and improved network load ability by using the simulation to identify the best placement and capacity that produced the most profit. The thorough outcomes highlight how well the suggested methods worked in a variety of case studies. © 2023 IEEE.

关键词： economic analysis Flexible AC Transmission System (FACTS) HVDC lines multi-objective optimization and transmission networks power flow optimization Thyristor-Controlled Series Capacitor (TCSC)

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