基于机会约束理论的微电网随机优化调度

Stochastic Optimization Dispatch of Micro-grid Based on the Chance Constraint Theory

近些年,风能、太阳能等可再生资源为主的分布式电源在微电网中得到广泛应用。为寻求微电网的随机经济优化,在满足系统功率平衡约束和运行约束的条件下,本文提出基于机会约束理论的微电网随机经济优化调度模型。该优化模型考虑了风能和太阳能的随机性和互补性,以及蓄电池中能量的不确定性;以微电网用电总费用最小为目标函数,利用抽样平均近似(SAA)法将机会约束条件转化为确定性条件,再采用粒子群算法进行寻优求解;同时研究了置信度水平和抽样次数对调度的影响。最后,对随机优化模型和确定性模型进行了对比,比较结果证明随机优化模型性能优于后者。算例结果表明了该随机优化模型的合理性和有效性。

In recent years, the distributed renewable resources such as wind power, solar power have been permeated in the micro-grid. To seek the random economic optimization scheduling of micro-grid, a stochastic economic optimization model of micro-grid based on the theory of chance constraint is established in this paper, this model is based on the condition of meeting the conditions of the system power balance constraints and operating constraints. And the randomness and complimentarily of wind, solar and uncertainty of storage battery are considered in this model. The model＇s objective function is the minimum electricity total cost of micro-grid and the sample average approximation（SAA） method is used to convert the opportunity constraints into deterministic conditions particle swarm optimization to obtain the optimal solution. At the same time, the impact of confidence level and sampling frequency on the dispatch is studied .Then, the stochastic optimization model and the deterministic model are compared, the comparison result proves stochastic optimization model outperforms the latter. The computation results show the effectiveness and feasibility of the stochastic optimization model.