Abstract
Recently, micro-grids (MGs) have had a great impact on power system issues due to their clear environmental and economic advantages. This paper proposes an equilibrium optimizer (EO) technique for solving the energy management problem of MGs incorporating energy storage devices concerning the emissions from renewable energy sources (RES) of MGs. Because of the imprecision and uncertainties related to the RESs, market prices, and forecast load demand, the optimization problem is described in a probabilistic manner using a 2m + 1 point estimation approach. Then, the EO approach is utilized for solving the probabilistic energy management (EM) problem. The EM problem is described according to the market policy on the basis of minimizing the total operating cost and emission from RESs through optimal settings of the power generated from distributed generators (DGs) and grids connected under the condition of satisfying the operational constraints of the system. The proposed EO is evaluated based on a grid-connected MG that includes energy storage devices. Moreover, to prove the effectiveness of the EO, it is compared with other recently meta-heuristic techniques. The simulation results show acceptable robustness of the EO for solving the EM problem as compared to other techniques.
Highlights
The results show that, during the light load periods, a large part of the load is supplied by the main grid and PEM-fuel cell (FC) because their bids are low
An efficient equilibrium optimizer (EO) algorithm was suggested in this paper with successful implementation to solve the energy management (EM) optimization problem for a typical MG system
Incorporating energy storage (ES) devices, considering the emissions of MG sources based on converting the multi-objective function using the penalty factor price to the single objective function to minimize the total operating costs
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The probabilistic technique based on the two-point-estimate method for solving the EM problem using GA was proposed in [22] for minimizing the operating cost of a system that includes ES devices and controllable loads. The EO is proposed for solving both deterministic and probabilistic EM problems by considering the pollutant emission of MG sources and including ES devices. The optimization of EM problem is formulated including two various objective functions for minimizing both the total operating cost of MG sources with ES devices and emission from RESs. the objective function is modeled as a single objective function by using a price penalty function and weighting factors instead of modeled as a multi-objective function. Investigate the effectiveness and applicability of the EO when compared with other recent optimization techniques through different scenarios
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