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1.山东科技大学电气与自动化工程学院,山东省青岛市 266590
2.电网智能化调度与控制教育部重点实验室(山东大学),山东省济南市 250061
3.智能电网教育部重点实验室(天津大学),天津市 300072
Received:28 June 2022,
Revised:2022-09-02,
Published Online:14 November 2022,
Published:25 February 2023
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张玉敏,孙鹏凯,吉兴全等.基于并行多维近似动态规划的综合能源系统动态经济调度[J].电力系统自动化,2023,47(4):60-68.
ZHANG Yumin,SUN Pengkai,JI Xingquan,et al.Dynamic Economic Dispatch for Integrated Energy System Based on Parallel Multi-dimensional Approximate Dynamic Programming[J].Automation of Electric Power Systems,2023,47(4):60-68.
张玉敏,孙鹏凯,吉兴全等.基于并行多维近似动态规划的综合能源系统动态经济调度[J].电力系统自动化,2023,47(4):60-68. DOI: 10.7500/AEPS20220628001.
ZHANG Yumin,SUN Pengkai,JI Xingquan,et al.Dynamic Economic Dispatch for Integrated Energy System Based on Parallel Multi-dimensional Approximate Dynamic Programming[J].Automation of Electric Power Systems,2023,47(4):60-68. DOI: 10.7500/AEPS20220628001.
针对随机动态经济调度模型难以高效求解的问题,提出一种用于快速求解电-气-热综合能源系统(IES)随机动态经济调度问题的并行多维近似动态规划算法。该算法将原有的高维状态空间中的状态变量聚合到IES的电储能系统(ESS)的可用容量和蓄热罐(HST)的可用热量中,实现了状态空间的降维,进而解决了动态规划中“维数灾”的问题。此外,利用ESS和HST的运行约束,将无效状态剔除,降低了问题的求解规模。在风电、电价和负荷等不确定场景充分训练后的值表模型中,通过近似值函数的迭代寻优,将含有经验知识的值表应用于在线测试中,实现应对不确定性的IES最优调度决策。以改进的2个系统为例,验证了所提模型和算法的有效性。
With respect to the problem that the stochastic dynamic economic dispatch model is difficult to solve efficiently
this paper proposes a parallel multi-dimensional approximate dynamic programming algorithm for solving the stochastic dynamic economic dispatch rapidly for electricity-gas-heat integrated energy system (IES). This algorithm can aggregate the state variables in the original high-dimensional state space into the available capacity of the electrical storage system (ESS)
and the available heat of the heat storage tank (HST) of the IES to achieve dimensionality reduction of the state space and solve the problem of “dimensional disaster” in the dynamic dispatch. In addition
this paper uses the operation constraints of ESS and HST to eliminate the invalid states and reduce the solving scale of the problem. In the fully trained value table model for uncertain scenarios such as wind power
electricity price and load
through the iterative optimization of the approximate value function
the value table containing empirical knowledge is employed to the online test to make the IES optimal dispatch decision deal with uncertainty. The effectiveness of the proposed model and algorithm is verified by taking the improved two power systems as examples.
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