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Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach
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Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach
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Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach
Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach
Journal Article

Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach

2022
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Overview
In recent years, owing to the effect of fossil fuels on global warming, the exhaustion of oil fields, and the lucrative impacts of renewable energy resources (RESs), the penetration of RESs has been increasing significantly in power systems. An effective way to benefit from all RESs advantages is by applying them in microgrid systems (MGS). Furthermore, MGS can ease the way for utilizing a large amount of RESs, if its economic-environmental-technical aspects of it are taken into account. In this regard, this paper proposes an optimal solution for the energy management of a microgrid by considering a comprehensive study. In the proposed methodology, different distributed energy resources such as wind turbines generator (WTG), energy storage (ES), combined heat and power (CHP), rubbish burning agent (RBA), and diesel generators (DG) are modeled. In addition, electric vehicles (EVs) are considered a load with uncertainty. The objective function of the proposed method is to minimize the microgrid’s total cost by considering the microgrid’s emission cost and technical constraints. In this study, the microgrid’s technical, environmental, and economic aspects are investigated. In addition, the optimization problem is converted into a mixed-integer linear programming method by using the proper linearization method. In this paper, the increasing effect of wind energy penetration rate on the total price also has been studied. The simulation results show that by increasing the wind energy penetration rate by up to 30% of total power, the total cost will decrease by up to 30.9%.