基于信息间隙决策理论的微电网多目标鲁棒优化调度Multi-Objective Robust Optimal Scheduling of Micro Grid Based on IGDT
江南,朱双涛,孙志刚,蔡培倩,唐传旭
JIANG Nan,ZHU Shuangtao,SUN Zhigang,CAI Peiqian,TANG Chuanxu
摘要(Abstract):
针对预测技术难以准确获取实际的可再生能源出力和负荷大小,其随机性影响微电网控制策略及用户经济性的问题,基于含光伏系统、储能系统和负荷的并网型微电网,考虑分时电价和需量管理,以用户日电费成本最低为目标函数,建立一种需量管理捆绑峰谷套利的微电网日前优化调度模型。基于该模型,计及光伏出力和负荷的波动性,提出基于信息间隙决策理论(Information Gap Decision Theory,IGDT)的微电网多目标鲁棒优化调度模型,制订具有鲁棒性的调度方案,并研究预设目标成本与光伏出力及负荷波动区间的定量关系。利用ε-约束方法刻画多目标问题的Pareto有效前沿,运用模糊满意度理论确定Pareto解集中的折中解,为运行人员提供合理的鲁棒决策方案。通过对某工业微电网进行仿真,并与蒙特卡洛法对比分析,验证了所建模型的可行性和有效性。
It is difficult to accurately obtain the renewable energy output and load based on the prediction technology. The randomness has a profound impact on the control strategy of micro-grid and the economy of users. For the grid connected micro-grid with photovoltaic system, energy storage system and load, a micro-grid day-ahead optimal scheduling model with demand management and bundled with peak-valley arbitrage is established, the objective function of which is the lowest daily electricity payment. Based on this model, taking into account the fluctuation of photovoltaic output and load, a multiobjective robust optimal scheduling model of micro-grid based on information gap decision theory(IGDT) is proposed to provide robust strategies, and study the quantitative relationship between preset target cost and photovoltaic output and load fluctuation range. The ε-constraint method is proposed to depict Pareto efficient frontier of multi-objective problem. Besides,the fuzzy satisfaction theory is used to determine the compromise solution of Pareto solution set, which provides a reasonable decision-making basis for operators. Compared with Monte Carlo method, simulation results on the micro-grid in an industrial park verify that the proposed model is feasible and effective.
关键词(KeyWords):
信息间隙决策理论;微电网;光伏系统;储能系统;鲁棒优化
IGDT;micro power grid;photovoltaic system;energy storage system;robust optimization
基金项目(Foundation):
作者(Author):
江南,朱双涛,孙志刚,蔡培倩,唐传旭
JIANG Nan,ZHU Shuangtao,SUN Zhigang,CAI Peiqian,TANG Chuanxu
参考文献(References):
- [1]曹金声,曾君,刘俊峰,等.考虑极限场景的并网型微电网分布鲁棒优化方法[J].电力系统自动化,2022,46(7):50-59.CAO Jinsheng, ZENG Jun, LIU Junfeng, et al. Distributionally Robust Optimization Method for Grid-connected Microgrid Considering Extreme Scenarios[J]. Automation of Electric Power Systems, 2022, 46(7):50-59.
- [2]陈丽娟,吴甜恬,柳惠波,等.基于需量管理的两阶段大用户储能优化模型[J].电力系统自动化,2019,43(1):194-200.CHEN Lijuan, WU Tiantian, LIU Huibo, et al. Demand management based two-stage optimal storage model for large users[J]. Automation of Electric Power Systems,2019, 43(1):194-200.
- [3]马天祥,贾伯岩,张智远,等.基于二层规划的能源互联微电网能量优化调度方法[J].电力系统自动化,2019,43(16):34-43.MA Tianxiang, JIA Boyan, ZHANG Zhiyuan, et al.Energy Optimal Dispatching Method of Micro-energy Internet Based on Bi-level programming[J]. Automation of Electric Power Systems, 2019, 43(16):34-43.
- [4]侯慧,薛梦雅,陈国炎,等.计及电动汽车充放电的微电网多目标分级经济调度[J].电力系统自动化,2019,43(17):55-62.HOU Hui, XUE Mengya, CHEN Guoyan, el al. Multi-objective hierarchical economic dispatch for microgrid considering charging and discharging of electric vehicles[J]. Automation of Electric Power Systems, 2019, 43(17):55-62.
- [5]刘春晖,张政,牟辉龙,等.考虑不同场景的微电网短期经济调度分析[J].电子器件,2021,44(6):1491-1498.LIU Chunhui, ZHANG Zheng, MOU Huilong, et al.Analysis of Short-Term Economic Dispatch of Microgrid Considering Different Scenarios[J]. Chinese Journal of Electron Devices, 2021, 44(6):1491-1498.
- [6]晏开封,张靖,何宇,等.基于机会约束的微电网混合整数规划优化调度[J].电力科学与工程,2021,37(2):17-24.YAN Kaifeng, ZHANG Jing, HE Yu, et al. The Optimal Dispatching of Mixed Integer Programming Based on Opportunity Constraint of Microgrid[J]. Electric Power Science and Engineering, 2021, 37(2):17-24.
- [7] Ben-Haim Y. Information Gap decision theory[M]. San Di ego:Academic Press Inc, 2001:317-346.
- [8] AHMADI A, ESMAEEL NEZHAD A, HREDZAK B.Security-constrained unit commitment in presence of lithium-ion battery storage units using information-gap decision theory[J]. IEEE Transactions on Industrial Informatics, 2019, 15(1):148-157.
- [9]汪超群,韦化,吴思缘.基于信息间隙决策理论的多源联合优化机组组合[J].中国电机工程学报,2018,38(12):3431-3440.WANG Chaoqun, WEI Hua, WU Siyuan. Multi-power combined unit commitment based on information gap decision theory[J]. Proceedings of the CSEE, 2018, 38(12):3431-3440.
- [10]马欢,刘玉田.基于IGDT鲁棒模型的风电爬坡事件协调调度决策[J].中国电机工程学报,2016,36(17):4580-4588.MA Huan, LIU Yutian. IGDT robust model-based coordinated scheduling strategy for wind power ramp events[J]. Proceedings of the CSEE, 2016, 36(17):4580-4588.
- [11]赵奇,吕洋,王毅,等.考虑微电网灵活调节潜力的主动配电网鲁棒优化[J].浙江电力,2022,41(1):55-63.ZHAO Qi, LYU Yang, WANG Yi, et al. Robust Optimization of Active Distribution Networks Considering the Flexible Regulation Potential of Microgrids[J]. Zhejiang Electric Power, 2022, 41(1):55-63.
- [12]宋坤隆,谢云云,陈晞,等.基于信息间隙决策理论的电网负荷恢复鲁棒优化[J].电力系统自动化,2017,41(15):113-120.SONG Kunlong, XIE Yunyun, CHEN Xi, et al.Robust restoration method for power system load based on information gap decision theory[J]. Automation of Electric Power Systems, 2017, 41(15):113-120.
- [13]蔡紫婷,彭敏放,沈美娥.考虑需求侧资源的智能小区综合能源日前优化调度[J].电力自动化设备,2021,41(3):18-24,32.CAI Ziting, PENG Minfang, SHEN Mei'e.Day-ahead optimal scheduling of integrated energy in smart communities considering demand side resources[J]. Electric Power Automation Equipment, 2021, 41(3):18-24, 32.
- [14]冯其芝,喻洁,李扬,等.考虑分时电价的虚拟发电厂调度策略[J].电力需求侧管理,2014,16(4):1-5.FENG Qizhi, YU Jie, LI Yang, et al. Scheduling strategy of virtual power plant considering time-of-use power price[J]. Power Demand Side Management,2014, 16(4):1-5.
- [15] Deb K. Multi-objective, optimization using evolutionary algorithms[M]. New York:John Wiley&Sons, 2001.
- 信息间隙决策理论
- 微电网
- 光伏系统
- 储能系统
- 鲁棒优化
IGDT - micro power grid
- photovoltaic system
- energy storage system
- robust optimization