基于机会约束规划的用户侧综合能源系统优化配置

Chenxia Jia, Muke Bai, Chao Zhang, Jing Zhou, Gongbo Liu, Sheng Xu, Wei Tang, Cong Wu, Chenjun Sun
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摘要

用户侧综合能源系统(USIES)可以根据用户需求提供能源,以充分利用终端能源条件,提高能源效率,促进当地可再生能源的消费。基于机会约束规划,建立了USIES多目标协调规划的双层规划模型。根据概率密度函数分别建立风电、光伏发电和负荷的多状态模型。在此基础上,提出了一种系统的多状态模型。考虑经济、能源、环保等因素,建立了基于双层规划的USIES配置模型,包括WT、PV、微型燃气轮机和燃气锅炉。在上层目标函数中以年成本最小为目标,实现分布式能源的配置。底层考虑了微型水轮机的最优调度问题,目标函数包括USIES损失成本。采用最优策略、遗传算法和粒子群算法求解规划模型。以华北某商住小区的USIES规划为例,验证了该模型和方法的有效性。仿真结果表明,多状态模型可以简化模型计算的难度。基于机会约束规划的USIES规划可以充分考虑USIES的不确定性。在一定置信水平下,得到与该置信水平对应概率的最优投资。
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Optimal configuration of user side integrated energy system based on chance constrained programming
A user side integrated energy system (USIES) can supply energy in accordance with user demand, in order to make full use of terminal energy conditions, improve energy efficiency, and promote consumption of local renewable energy. A bi-level programming model of USIES multi-objective coordinated planning is developed based on the chance constrained programming. Multi-state models of wind turbine (WT), photovoltaic (PV) generation and load are established respectively according to probability density functions. Then a multi-state model of the IES can be proposed. Considering economic, energy influences, environmental protection and other factors, a configuration model of USIES based on bi-level programming is established, including WT, PV, micro gas turbine and gas boiler. Annual costs is minimized in the upper level objective function in order to accomplish configuration of distributed energy sources. The optimal scheduling of micro turbine is considered in the lower level, in which objective functions include the cost of USIES losses. The elitist strategy genetic algorithm and particle swarm optimization are applied for solving the planning model. A case of USIES planning, which used is in a residential and commercial areas in the North China, verifies the effectiveness of the proposed model and method. The simulation results show that the multi-state model can simplify the difficulty of model calculation. The USIES planning based on the chance constrained programming can adequately consider the uncertainty of USIES. Under a certain confidence level, the optimal investment with the corresponding probability of the confidence level is obtained.
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