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In this paper, the problem of optimal stochastic operation of thermal units, combined heat and power (CHP) units, wind turbines (WTs) and photovoltaic (PV) units with the objective of reducing total operating costs is defined as an optimization problem. In this problem, the uncertainties in load, photovoltaic and wind units are considered in terms of solving the two-point estimation method. The amount of power and heat output in different units, the position of the transformers tap and the reactive power injection by the parallel compensators are the control variables of the optimization problem. A particle swarm optimization algorithm with comprehensive learning is used to solve this optimization problem. In order to evaluate the performance of the proposed method, the IEEE 118-bus standard test system consisting of thermal, CHP, WT and PV units is selected. The simulation results in MATLAB software environment show the superiority of the comprehensive learning particle swarm optimization method compared to other optimization methods.
 

Keywords: Optimal Stochastic Operation, Comprehensive Learning Particle Swarm Optimization (CLPSO) Method, Two-point Estimation Method (PEM)

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