New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

Abstract

Microgrids can be assumed as a solution model for green energy sources, energy storage systems, and combined heat and power (CHP) systems. In this work, the cost and emission minimization based on a demand response (DR) program is considered an optimization problem. To solve the mentioned problem a new multiobjective optimization algorithm (improved particle swarm optimization) is proposed based on a fuzzy mechanism to select the optimal value. The microgrid system includes two CHP units, fuel cell and battery systems, and the heat buffer tank. In this problem, two different feasible operating regions have been assumed in CHPs. Accordingly, to decrease the operational cost, time‐of‐use, and real‐time pricing DR programs have been simulated, and the impacts of the mentioned models are evaluated overload profiles. The effectiveness of proposed models has been applied on different cases studies by different scenarios. The proposed model solved the DR program, time of use‐DR and real‐time pricing‐DR problems. The proposed model could reduce the cost about 10%.

Towards Optimal Management in Microgrids: An Overview

“…Regardless of whether the objective is to maximize the MG production, reduce the CO 2 emissions, increase the benefits of the MG, or any other, a good EMS can increase the stability and efficiency of the MG while being able to extend the service life of its components. Not only can one objective be optimized at a time, but several ones can be at the same time, as has been pointed out in several works of this review, as in [71,76,99]. In this case, the EMS has multiple objectives since it can simultaneously present a response to economic, environmental, and technical problems.…”

“…The EMS was aimed at minimizing both the operation and energy costs, and RegPSO presented better results than the GA. Finally, Zeng and Berti [71] proposed a new PSO multiobjective optimization algorithm, which was based on a fuzzy mechanism to minimize the operating and emission costs in demand response. The algorithm was used with a grid-connected MG composed of several production and storage systems containing CHPs, fuel cells, ESSs, energy-only units, and heat buffertanks.…”

A systematic review of energy management system based on various adaptive controllers with optimization algorithm on a smart microgrid

“…PSO 38,[44][45][46][47]56,57,65,70,71,73 Most widely used algorithm and easy to understand. Suitable for parallel computing, rapid convergence.…”

“…DR program and emission cost are not considered. According to Zeng and Berti, 57 a novel approach of solving EMS based improved PSO algorithm is implemented. This approach can be solved by adopting the DR programming paradigm, which considers optimum values as fuzzy mechanisms.…”

Developed Approach Based on Equilibrium Optimizer for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco

“…In [14], artificial intelligent (AI) controllers were employed to attain an efficient and optimized energy management operation for hybrid power system of (H2/WT/PV/GMT). In [15], an improved particle swarm optimization based on a fuzzy mechanism was proposed to minimize the cost and emission. In [16], an efficient metaheuristic technique based on artificial bee swarm was exploited for sizing optimization of wind/PV/hydrogen energy system.…”