考虑可再生能源不确定性的热电联供型微网随机鲁棒经济调度

Stochastic Robust Economic Dispatch of Combined Heat and Power Microgrid Considering Renewable Energy Uncertainty

为应对可再生能源出力不确定性和传统微网供能形式单一造成经济性较低的问题,提出了多能源微网两阶段随机鲁棒优化模型。模型考虑了电网与热网的网架结构,目标函数旨在最小化最恶劣风电出力场景下的两阶段微网成本,其中包括第一阶段启停成本与第二阶段运行成本。由于第一阶段与第二阶段的决策与优化结果相互影响,因此两阶段优化问题难以直接求解,文章采用线性决策随机鲁棒优化框架对模型求解。首先,应用线性决策方式相关理论对第二阶段进行转化;其次,采用锥化模糊集刻画可再生能源出力的不确定性;最后,将第二阶段的sup-min问题推导为锥优化的min问题,进而与第一阶段的min问题合并,得到能够直接求解的单层锥优化问题,并采用求解器求得最优解。仿真结果验证了所提模型和方法的有效性。

In order to deal with the problem of low economy caused by the uncertainty of renewable energy output and the single energy supply form of traditional microgrid, this paper proposes a two-stage stochastic robust optimization model for multi-energy microgrid. The model considers the grid structure of the power grid and the heating network. The objective function is to minimize the two-stage microgrid cost in the worst wind power output scenario, which includes the start and stop costs of the first stage and the operating costs of the second stage. Because the decision-making and optimization results of the first stage and the second stage influence each other, the two-stage optimization problem is difficult to solve directly. This paper uses a stochastic robust optimization framework for linear decision-making to solve the model. Firstly, the related theories of linear decision-making methods are applied to transform the second stage. Secondly, the cone-shaped fuzzy set is used to describe the uncertainty of renewable energy output. Finally, the "sup-min" problem in the second stage is derived as the "min" problem of cone optimization, and then combined with the "min" problem in the first stage to obtain the single-layer cone optimization problem which can be solved directly, and the optimal solution is obtained by using the solver. The simulation results verify the effectiveness of the proposed model and method.