Stochastic Unit Generation Maintenance Scheduling Considering Renewable Energy and Network Constraints

Midterm preventive maintenance scheduling of generators is one of the important problems in the power system industry that is implemented in order to reduce breakdowns and damage of the power plants beside of reliability of power system and constraints satisfaction. Here, the affection of photovoltaic systems, as one of the most practical and significant renewable energies, beside maintenance scheduling is studied. The problem is associated with many uncertain parameters such as market clearing price (MCP), load and generation power of photovoltaic units. In this paper, a stochastic framework based on the scenario reduction technique, is utilized to model the uncertainties. Due to the nonlinearity and nonconvexity of the problem, a new optimization technique based on the modified Electro Search Optimization Algorithm (ESOA) is proposed. Moreover, in this paper, the network constraints have been considered to have a more realistic problem condition. Finally, the proposed problem is tested on the modified IEEE-RTS test system to prove the effectiveness and merit of the model.