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计及需求响应的并网型微电网协同优化策略 被引量:15

Coordinated Optimization Strategy for Grid-connected Microgrid Considering Demand Response
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摘要 为提高微电网的经济效益,提出了计及需求响应的并网型微电网协同优化策略。首先建立微电网中可调控负荷和各发电单元模型。然后,构建了微电网双层协同优化模型,上层在满足用户舒适度的基础上,利用分时电价信息引导用户侧可调控负荷参与需求响应,并将优化后的负荷曲线输出到下层模型;下层在满足供需平衡和发电单元约束的基础上,优化分布式能源出力、储能充放电功率和并网功率,以降低微电网的日运行成本。最后,模型采用差异进化算法进行求解,通过算例仿真比较不同情况下微电网的优化结果,验证了该策略的有效性。 To improve the economic benefit of microgrid, a coordinated optimization strategy for grid-connected mi- crogrid is put forward considering demand response (DR). First, a model of controllable load (CL) and a model of gen- eration units of mierogrid are established. Then, a bi-level coordinated optimization model for microgrid is established. On the upper level, the CL on the user side can be guided by the time-of-use (TOU) electricity price to participate in the DR on the basis of satisfying the user's comfort degree, and the optimized load curve is output to the lower model ; on the lower level, the output power of distributed sources, discharging/charging power of battery energy storage system (BESS) , and grid-connected power are optimized on the basis of meeting the supply-demand balance and the con- straints of generation units to reduce the daily operation cost of microgrid. Finally, differential evolution (DE) algorithm is employed to solve the bi-level coordinated optimization model, and simulation results of an example in different modes verify the validity of the proposed strategy.
出处 《电力系统及其自动化学报》 CSCD 北大核心 2018年第1期30-37,共8页 Proceedings of the CSU-EPSA
基金 国家自然科学基金资助项目(51477099) 上海市自然科学基金资助项目(15ZR1417300 14ZR1417200) 上海市教委创新基金资助项目(14YZ157 15ZZ106)
关键词 微电网 需求响应 分布式能源 可调控负荷 双层优化 microgrid demand response (DR) distributed energy resource controllable load (CL) bi-level optimi-zation
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  • 1周泽远,苏大威,汪志成,朱卫平,李鹏.基于自适应变异粒子群算法的独立多元互补微网经济环保运行[J].电网与清洁能源,2015,31(4):8-14. 被引量:3
  • 2丁明,吴义纯,张立军.风电场风速概率分布参数计算方法的研究[J].中国电机工程学报,2005,25(10):107-110. 被引量:218
  • 3蒙文川,邱家驹,卞晓猛.电力系统经济负荷分配的人工免疫混沌优化算法[J].电网技术,2006,30(23):41-44. 被引量:22
  • 4Lasseter B. Microgrids (distributed power generation )[C]// IEEE Power Engineering Society Winter Meeting. Colum- bus, USA: 2001.
  • 5Moghaddam A A, Seifi A, Niknam T, et al. Multi-objective operation management of a renewable MG(micro-grid)with back-up micro-turbine/fuel cell/battery hybrid powersource[J]. Energy, 2011,36( 11 ) : 6490-6507.
  • 6Seon-Ju A, Seung-II M. Economic scheduling of distributed generators in a microgrid considering various constraints[C]// IEEE Power & Energy Society General Meeting. Calgary, Canada: 2009.
  • 7Mohamed F A,Koivo H N. System modeling and online optimal management of microgrid using mesh adaptive direct search[J]. International Journal of Electrical Power and Energy Systems, 2010,32(5 ) : 398-407.
  • 8Abido M A. Environmental/economic power dispatch using muhiobjective evolutionary algorithms[J]. !EEE Trans on Power Systems, 2003,18(4) : 1529-1537.
  • 9D'Arnaud K A D. Optimization of Renewable Energy Re- sources (RERs)for Enhancing Network Performance for Distribution Systems[D]. Washington D C, USA : Howard University, 2010.
  • 10Rahman Md H, Yamashiro S. Novel distributed power gen- erating system of PV-ECaSS using solar energy estimation [J]. IEEE Trans on Energy Conversion, 2007,22 (2) : 358 - 367.

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