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基于双层优化的灵活调节服务交易 被引量:1

Flexible Ramping Products Transaction Based on Bi-Level Optimization
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摘要 介绍了美国加州电网近期的灵活调节服务机制的基本概念,基于双层优化理论建立了灵活调节服务市场均衡模型,通过粒子群算法对模型进行求解。结合算例进行电力市场各发电主体收益分析,结果表明,引入灵活调解服务交易后,能够缓解电网短时间功率不平衡问题,同时在现行分时电价的背景下,提高了电力市场中各发电主体的收益。 In this paper we introduced,first of all,the basic concept of the flexible ramping product mechanism adopted by the California power grid in the USA recently.And then,we establisheda flexible ramping product trade equilibrium model based on bi-level optimization theory,and solved the model with quantum particle swarm algorithm.Based on the example,we analyzed the income of each generator in the electricity market.The results show that the introduction of flexible ramping product can alleviate short time power grid imbalance,and thus improve the revenue of each main power generator in the background of time-of-use electricity prices.
作者 赵文会 李阮 ZHAO Wenhui;LI Ruan(School of Economics and Management,Shanghai University of Electric Power,Shanghai 200090,China)
出处 《电网与清洁能源》 2018年第11期1-7,共7页 Power System and Clean Energy
基金 国家自然科学基金项目:基于节能减排的发电权与排污权组合交易模型(71403163) 上海市哲学社科规划基金项目:基于节能减排的发电权与排污权组合交易优化模型及其利益分配(2014BJB017) 中国博士后科学基金项目:跨省区发电权与排污权组合交易模式选择及其利益分配(2013M540910)~~
关键词 可再生能源 双层优化 收益分析 灵活调节服务 renewable energy bi-level optimization theory income analyze flexible ramping product
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  • 1MANWELL 1, ROGERS A, HAYMAN G, et al. Hybrid2- a hybrid system simulation model: theory manual[EB/OL], http://www.ecs.umass.edu/mie/lab- s/rerl/hy2/.
  • 2MORAIS H, KADAR P, FARIA P, et al. Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming[J]. Renew Energy, 2010, 35(1): 151-156.
  • 3HOMER V. 2.68beta National Renewable Energy Laboratory (NREL), 617 Cole Boulevard, Golden, CO 80401-3393[EB/OL]. http://www.homerenergy.com/.
  • 4GUO L, LIU W, CAI J, et al. A two-stage optimal planning and design method for combined cooling, heat and power microgrid system[J]. Energy Conversion and Management, 2013(74): 433-445.
  • 5DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.
  • 6XIE Le, CARVALHO P M S, FERREIRA L A F M, et al. Wind integration in power systems: operational challenges and possible solutions[J]. Proceedings of the IEEE, 2011, 99 (1) : 214-232.
  • 7HOLTTINEN H. Impact of hourly wind power variations on system operation in the Nordic countries [J]. Wind Energy, 2005, 8(2).. 197-218.
  • 8LUND H, HVELPLUND F, (OSTERGAARD P A, et al. System and market integration of wind power in Denmark[J]. Energy Strategy Reviews, 2013, 1(3): 143-156.
  • 9李俊峰,蔡丰波,乔黎明,等.中国风电发展报告[M].北京:中国环境科学出版社,2013.
  • 10WANG C, SHAHIDEHPOUR S M. A decomposition approach to nonlinear multi-area generation scheduling with tie-line constraints using expert systems [J]. IEEE Trans on Power Systems, 1992, 7(4) 1409-1418.

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