Online Management and Balancing of Microgrid with CHP System Using Multi-objective Genetic Algorithms

This paper presents scheme of optimal management of microgrid (MG) using multi-objective genetic algorithms (MOGA) aimed at reduction of cost and emission with satisfying constraints, electrical and heat loads. Microgrid structure, system component models, optimization problem scenarios objective functions and problem solving method is described. Proposed MG consists of a diesel generator, a fuel cell, a micro turbine, a wind turbine, a photovoltaic array and batterystorage. Recovered heat by micro-turbine and generated heat by heater can be used to supply heat demand. Also heat penalty, hourly revenue and outgo from sold and purchased power was added to the cost function. The main goal of this paper is to demonstrate impacts of using CHP system and heat penalty on management and operation of microgrid. Therefore optimization problem solves as multi-objective for three scenarios to supply loads and satisfy constraints during twentyfour hour period. Simulation by MATLAB demonstrates the accuracy of results on proposed microgrid.

Keywords:

Microgrid , load management , multi-objective optimization , genetic algorithms , CHP