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Sayouti, Yassine
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Chemistry Energy

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Multi-Objective Optimization Dispatch Based Energy Management of A Microgrid Running Under Grid Connected and Standalone Operation Mode Lagouir, Marouane; Badri, Abdelmajid; Sayouti, Yassine
International Journal of Renewable Energy Development Vol 10, No 2 (2021): May 2021
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2021.34656

Abstract

This paper presents a novel optimization approach for a day-ahead power management and control of a DC microgrid (MG). The multi-objective optimization dispatch (MOOD) problem involves minimizing the overall operating cost, pollutant emission levels of (NOx, SO2 and CO2) and the power loss cost of the conversion devices. The weighted sum method is selected to convert the multi-objective optimization problem into a single optimization problem. Then, analytic hierarchy process (AHP) method is applied to determine the weight coefficients, according to the preference of each objective function. The system’s performance is evaluated under both grid connected and standalone operation mode, considering power balancing, high level penetration of renewable energy, optimal scheduling of charging/discharging of battery storage system, control of load curtailment and the system technical constraints. Ant lion optimizer (ALO) method is considered for handling MOOD, and the performance of the proposed algorithm is compared with other known heuristic optimization techniques.  The simulation results prove the effectiveness and the capability of the developed approach to deal better with the coordinated control and optimization dispatch problem.They also revealed that economically running the MG system under grid connected mode can reduce the overall cost by around 4.70% compared to when it is in standalone operation mode.
Solving Multi-Objective Energy Management of a DC Microgrid using Multi-Objective Multiverse Optimization Lagouir, Marouane; Badri, Abdelmajid; Sayouti, Yassine
International Journal of Renewable Energy Development Vol 10, No 4 (2021): November 2021
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2021.38909

Abstract

This paper deals with the multi-objective optimization dispatch (MOOD) problem in a DC microgrid. The aim is to formulate the MOOD to simultaneously minimize the operating cost, pollutant emission level of (NOx, SO2 and CO2) and the power loss of conversion devices.  Taking into account the equality and inequality constraints of the system. Two approaches have been adopted to solve the MOOD issue. The scalarization approach is first introduced, which combines the weighted sum method with price penalty factor to aggregate objective functions and obtain Pareto optimal solutions. Whilst, the Pareto approach is based on the implementation of evolutionary multi-objective optimization solution. Single and multi-objective versions of multi-verse optimizer algorithm are, respectively, employed in both approaches to handle the MOOD. For each time step, a fuzzy set theory is selected to find the best compromise solution in the Pareto optimal set. The simulation results reveal that the Pareto approach achieves the best performances with a considerable decrease of 28.96 $/day in the daily operating cost, a slight reduction in the power loss of conversion devices from 419.79 kWh to 419.29 kWh, and in less computational time. While, it is noticing a small increment in the pollutant emission level from 11.54 kg/day to 12.21 kg/day, for the daily microgrid operation. This deviation can be fully covered when comparing the cost related to the treatment of these pollutants, which is only 5.55 $/day, to the significant reduction in the operating cost obtained using the Pareto approach.
Co-Authors Badri, Abdelmajid Lagouir, Marouane