Optimized Operation of an Integrated Energy System Based on Adaptive Probability Planning

Yanru Liu, K. Ding, Yi Xia, Haiving Dong
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Abstract

This paper proposes an optimized operation method based on adaptive probability planning for the uncertainty of renewable energy output in integrated energy systems. Firstly, by analyzing the architecture of the comprehensive energy system of the park, the corresponding equipment model and the probability model of renewable energy output are established, the lowest daily operation cost of the park is taken as the target function, and the optimal scheduling model of the park is established with the rated operating state of each equipment as the constraint condition, then the scheduling decision problem is expressed under the Markov decision process, defining the observation state, scheduling action and reward function of the system, and the adaptive probabilistic planning algorithm is adopted to obtain the optimization strategy of the Markov decision process, and optimize the integrated energy system. Finally, the effectiveness of the proposed model and algorithm is verified.
基于自适应概率规划的综合能源系统优化运行
针对综合能源系统中可再生能源输出的不确定性,提出了一种基于自适应概率规划的优化运行方法。首先,通过对园区综合能源系统体系结构的分析,建立了相应的设备模型和可再生能源输出概率模型,以园区最低日运行成本为目标函数,以各设备的额定运行状态为约束条件,建立了园区最优调度模型,并在马尔可夫决策过程下表达了调度决策问题;定义系统的观察状态、调度动作和奖励函数,采用自适应概率规划算法获得马尔可夫决策过程的优化策略,对综合能源系统进行优化。最后,验证了所提模型和算法的有效性。
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