Multi-Objective Optimization of a Microgrid Considering Load and Wind Generation Uncertainties

作者：Xue, Guiting^*; Zhang, Yan; Liu, Yujiao

来源：International Review of Electrical Engineering, 2012, 7(6): 6225-6234.

• Microgrid
• Chance Constrained Programming
• Uncertainty
• Probabilistic Load Flow
• Multi-Objective Optimization
• Clonal Selection Algorithm

This paper builds a multi-objective optimization model based on chance constrained programming (CCP) for microgrid (MG) operation. The model aims to minimize the economic costs, carbon emissions, and node voltage deviations by optimizing the outputs of controllable distributed generators (CDGs). Considering the uncertainties related to load and wind speed, deterministic constraints on node voltages and branch transfer powers are inaccurate, thus they are expressed as chance constraints. Cumulant-based probabilistic load flow (PLF) method is used to check the probability constraints. Clonal selection algorithm (CSA) is applied to solve the optimization model, and a fuzzy-based decision maker is employed to select the 'best' compromised solution among the calculated Pareto-optimal solutions. Simulation results on a 33-node hypothetical radial MG analyze the relationship between economics and confidence levels and discuss the impacts of uncertain factors on the outputs of CDGs, which show the validity of the methodology proposed.

• 出版日期2012-11
• 单位上海交通大学