Optimal energy management of microgrids under environmental constraints using chaos enhanced differential evolution

Optimal energy management of microgrids is one of the challenging tasks in modern power systems. It helps to achieve maximum societal benefits in terms of economy and reduced environmental effects. Microgrid can be operated in grid connected as well as isolated mode. A novel hybrid optimization technique using differential evolution (DE) and chaos theory is presented in this paper for optimal operation of a microgrid comprising of both renewable and non-renewable energy sources. The reduction of pollutants is also considered because of integration of non-renewable energy sources with the microgrid. The motivation for the proposed hybrid algorithm is to avoid premature convergence and stagnation. The optimal operation is formulated as a bi-objective optimization problem considering minimization of operating cost and reduction of pollutants simultaneously over a 24-h scheduling horizon. It is a complex non-linear optimization problem under a set of equality as well as inequality constraints. A microgrid consisting of wind turbine (WT), photovoltaic (PV), micro turbine (MT) fuel cell (FC) and battery units as storage device is considered for the present study. The microgrid is assumed to be grid connected. The proposed algorithm is tested on two systems in order to verify its effectiveness and efficiency. Further, the results obtained by the proposed technique are validated by comparing the same obtained by other recent methods. It observed that the proposed technique is capable of producing superior results in terms of cost and pollution.