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Optimal Trade-Off Between Regulation and wind curtailment in the Economic Dispatch Problem

CSEE Journal of Power and Energy Systems 2015年第4期1卷 52-60页

作者： Jinghua Li Jiakun Fang Jinyu Wen Yi Pan Qiang Ding State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and TechnologyWuhan 430074China the department of electrical engineering Guangxi UniversityNanning 530004China China Electric Power Research Institute Beijing 100192China

Generator regulation and wind power curtailment are two conflicting ways to deal with the inaccurate prediction and volatility of wind *** study focuses on planning the day-ahead schedule based on optimal trade-off between regulation of generators and wind *** to traditional economic dispatch methods,the proposed schedule is more robust and adaptive to multiple forecast scenarios instead of a single forecast *** works of this paper are as follows:First,an economic dispatch problem based on multiple scenarios is formulated with the objective of minimizing both generator regulation and wind ***,a forecast method for wind power scenarios is ***,the proposed model is verified by comparing with other dispatch models that are based on single forecast *** simulation results demonstrate the effectiveness of the proposed method with less wind curtailment,generator regulation,and operational *** addition,the penalty factors are set as parameters and the influences on the generators’regulation and wind curtailment are analyzed,providing the reference for system operators with different regulatory purposes.

关键词： Economic dispatch forecasting regulation uncertainty wind curtailment wind power scenarios

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Short-term Transmission Maintenance Scheduling Considering Network Topology Optimization

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Journal of Modern Power Systems and Clean Energy 2022年第4期10卷 883-893页

作者： Weixin Zhang Bo Hu Kaigui Xie Changzheng Shao Tao Niu Jiahao Yan Lvbin Peng Maosen Cao Yue Sun State Key Laboratory of Power Transmission Equipment&System Security and New Technology at Chongqing University Chongqing 400044China

With the increasing penetration of renewable energy sources,transmission maintenance scheduling(TMS)will have a larger impact on the accommodation of wind ***,the more flexible transmission network topology owing to the network topology optimization(NTO)technique can ensure the secure and economic operation of power *** paper proposes a TMS model considering NTO to decrease the wind curtailment without adding control *** problem is formulated as a two-stage stochastic mixed-integer programming *** first stage arranges the maintenance periods of transmission *** second stage optimizes the transmission network topology to minimize the maintenance cost and system operation in different wind speed *** proposed model cannot be solved efficiently with off-theshelf solvers due to the binary variables in both ***,the progressive hedging algorithm is *** results on the modified IEEE RTS-79 system show that the proposed method can reduce the negative impact of transmission maintenance on wind accommodation by 65.49%,which proves its effectiveness.

关键词： Mixed-integer linear programming network topology optimization progressive hedging algorithm stochastic optimization transmission maintenance scheduling wind curtailment

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Deep reinforcement learning for wind and energy storage coordination in wholesale energy and ancillary service markets

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Energy and AI 2023年第4期14卷 371-382页

作者： Jinhao Li Changlong Wang Hao Wang Department of Data Science and AI Faculty of Information TechnologyMonash UniversityMelbourneVictoriaAustralia Department of Civil Engineering Monash UniversityMelbourneVictoriaAustralia Monash Energy Institute Monash UniversityMelbourneVictoriaAustralia

wind energy has been increasingly adopted to mitigate climate ***,the variability of wind energy causes wind curtailment,resulting in considerable economic losses for wind farm *** curtailment can be reduced using battery energy storage systems(BESS)as onsite backup ***,this auxiliary role may significantly weaken the economic potential of BESS in energy *** BESS scheduling should balance onsite wind curtailment reduction and market bidding,but practical implementation is challenging due to coordination complexity and the stochastic nature of energy prices and wind *** investigate the joint-market bidding strategy of a co-located wind-battery system in the spot and Regulation Frequency Control Ancillary Service *** propose a novel deep reinforcement learning-based approach that decouples the system’s market participation into two related Markov decision processes for each facility,enabling the BESS to absorb onsite wind curtailment while performing joint-market bidding to maximize overall operational *** realistic wind farm data,we validated the coordinated bidding strategy,with outcomes surpassing the optimization-based benchmark in terms of higher revenue by approximately 25%and more wind curtailment reduction by 2.3 *** results show that joint-market bidding can significantly improve the financial performance of wind-battery systems compared to participating in each market *** also show that using curtailed wind generation as a power source for charging the BESS can lead to additional financial *** successful implementation of our algorithm would encourage co-location of generation and storage assets to unlock wider system benefits.

关键词： wind-battery system wind curtailment Electricity market Deep reinforcement learning

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Power to gas:addressing renewable curtailment by converting to hydrogen

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Frontiers in Energy 2018年第4期12卷 560-568页

作者： Xiaohe YAN Xin ZHANG Chenghong GU Furong LI Department of Electronic and Electrical Engineering University of BathClaverton DownBathBA27AYUK Electricity National Control Centre National GridWokinghamRG415BNUK

Renewable energy is the key to meeting increasing electricity demand and the decarburization targets in the generation mix. However, due to constrained power network capacity, a large volume of renewable generation is curtailed particularly from wind power, which is a huge waste of resources. There are typically three approaches to addressing excessive renewable: direct curtailment, the reinforcement of networks to expand transfer capacity, and the conversion of excessive renewable into other energy types, such as hydrogen, to transport. The costs and benefits of the three approaches could vary significantly across location, time, and penetration of renewable energy. This paper conducts a cost-benefit analysis and comparison of the three techniques to address wind curtailment. It uses a reduced 16-busbar UK transmission network to analyze the performance of the three approaches. The UK 2020 generation mix is used to quantify the saved renewable energy and incurred costs. The payback time and net present value of the two investment techniques are compared. From demonstration, it is reasonable to conclude that converting excessive wind power into hydrogen to transport is an environmentally friendly and cost-effective way to address wind curtailment.

关键词： blending hydrogen cost-benefit analysis electrolysis wind curtailment

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