Optimal Sizing of Micro Energy grid Based on Multi-objective Particle Swarm Algorithm

The present paper aims to determine the optimal size of Micro energy grid (MEG) resources and energy storage units taking into consideration the thermal and electrical load curves. The MEG under study consists of wind turbines (WT), photovoltaic panels (PV), combined heat and power units (CHP). Further, the MEG includes a thermal storage (TS) units, boiler, and electrical heater to satisfy the electrical and heat load demand within MEG. The optimization objective is to define the optimal capacity of different types of the above distributed generators (DG) and TS units that guarantee the MEG can operate economically and reliably over a wide range of thermal and electrical load conditions. The objective function is to minimize the net present cost (NPC) including capital, operating and maintenance cost, and total CO2 emission simultaneously. In the present study, DG units put the priority on electricity production and the surplus/deficient electricity can be sold to/bought from the utility grid. The surplus/deficient heat can be storage/or supplied by TS, boiler and/or an electrical heater. This paper proposed multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal combination and optimal sizing of MEG components. The results show that integration of CHP and TS units to the MEG has a significant enhancement in the system performance by minimizing NPC and total CO2 emission. Simulation results proved the effectiveness of proposed MOPSO to find the optimal sizing in contrast with traditional single objective methods in terms of less computation time, fewer calculation steps.