Security Constrained Generation Scheduling Using Harmony Search Optimization Case Study: Day-ahead Heat and Power Scheduling

Security Constraint Generation Scheduling (SCGS) is one of the most important issues in modern power system shortterm operation. In the SCGS the optimal and secure operation of power system has been taken into account. SCGS includes the timing and production of available energy resources in order to maintaining customer demands. In this paper, we present a new approach for SCGS in Day-Ahead market considering both heat and power demands entire the system. Harmony Search Algorithm, (HSA) which is a recent meta-heuristic optimization algorithms is addressed in this paper to solve the SCGS problem which is a large-scale, non-convex, nonlinear with both continuous and discrete variables. It is shown that HSA, as a meta-heuristic optimization algorithm, may solve power system scheduling problem (Heat and Power) in a better fashion in comparison with the other evolutionary search algorithm that are implemented in such complicated issue. HSA was conceptualized using the musical process of searching for a perfect state of harmony. Compared to the earlier meta-heuristic optimization algorithms, HSA imposes fewer mathematical requirements that can be easily adopted for various types of engineering optimization problems, such as Combined Heat and Power SCGS (CHP-SCGS). An adopted case study is conducted to facilitate the effectiveness of the proposed method. This case study is recently presented in order to analysis the Day-Ahead power system studies with a 24-h scheduling horizon, which considers the Hydro-Thermal and conventional Unit Commitment (UC) problem. Simulation results show the effectiveness and fastness of the proposed method.