Energy Management of Microgrid Considering Renewable Energy Sources and Electric Vehicles Using the Backtracking Search Optimization Algorithm

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Yong Li ◽  
Salim Qadir Mohammed ◽  
Goran Saman Nariman ◽  
Nahla Aljojo ◽  
Alireza Rezvani ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Energy Sources ◽  
Management Problem ◽  
Backtracking Search ◽  
Search Optimization ◽  
The Impact

Abstract Different distributed generation (DG) technologies, active loads, and storage devices create an independent microgrid (MG). Scheduling of an MG is an important issue in renewable energy sources (RESs) based systems. In this paper, MGs include RESs, plug-in hybrid electric vehicles (PHEVs), and electrical energy storage systems. The proposed scheduling framework utilizes the Monte Carlo simulation (MCS) to characterize the uncertain parameters of PHEVs and RESs. Three different charging strategies are investigated for modeling the impact of different behaviors of PHEVs in MGs. These schemes are smart, controlled, and uncontrolled charging. Due to the nonlinear feature of the suggested optimization problem, it needs an efficient optimization tool to tackle the problem appropriately. So, this paper uses the backtracking search optimization (BSO) algorithm for the short-term scheduling of an MG. The proper performance of the offered scheme is investigated in two scenarios with different time horizons. The BSO algorithm and other optimization algorithms are used for comparing the results to verify the presented method in solving the energy management problem of the MGs.

scholarly journals A New Solution to Profit Based Unit Commitment Problem Considering PEVs/BEVs and Renewable Energy Sources

2020 ◽  
Vol 184 ◽  
pp. 01070
Author(s):  
Ayani Nandi ◽  
Vikram Kumar Kamboj
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Production Cost ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Unit Commitment Problem ◽  
Load Demand ◽  
Commitment Problem ◽  
The Impact

Daily load demand for industrial, residential and commercial sectors are changing day by day. Also, inclusion of e-mobility has totally effected the operations of realistic power sector. Hence, to meet this time varying load demand with minimum production cost is very challenging. The proposed research work focuses on the mathematical formulation of profit based unit commitment problem of realistic power system considering the impact of battery electric vehicles, hybrid electric vehicles and plug in electric vehicles and its solution using Intensify Harris Hawks Optimizer (IHHO). The coordination of plants with each other is named as Unit commitment of plants in which the most economical patterns of the generating station is taken so as to gain low production cost with higher reliability. But with the increase in industrialization has affected the environment badly so to maintain the balance between the generation and environment a new thinking of generating low cost power with high reliability by causing less harm to environment i.e. less emission of flue gases is adopted by considering renewable energy sources.

scholarly journals Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4240 ◽  
Author(s):  
Khairy Sayed ◽  
Ahmed G. Abo-Khalil ◽  
Ali S. Alghamdi
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Dc Microgrid ◽  
Charging Station ◽  
And Control ◽  
Ev Charging

This paper introduces an energy management and control method for DC microgrid supplying electric vehicles (EV) charging station. An Energy Management System (EMS) is developed to manage and control power flow from renewable energy sources to EVs through DC microgrid. An integrated approach for controlling DC microgrid based charging station powered by intermittent renewable energies. A wind turbine (WT) and solar photovoltaic (PV) arrays are integrated into the studied DC microgrid to replace energy from fossil fuel and decrease pollution from carbon emissions. Due to the intermittency of solar and wind generation, the output powers of PV and WT are not guaranteed. For this reason, the capacities of WT, solar PV panels, and the battery system are considered decision parameters to be optimized. The optimized design of the renewable energy system is done to ensure sufficient electricity supply to the EV charging station. Moreover, various renewable energy technologies for supplying EV charging stations to improve their performance are investigated. To evaluate the performance of the used control strategies, simulation is carried out in MATLAB/SIMULINK.

scholarly journals Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization

2021 ◽  
Vol 11 (8) ◽  
pp. 3661
Author(s):  
Mohammad Ghiasi ◽  
Taher Niknam ◽  
Moslem Dehghani ◽  
Pierluigi Siano ◽  
Hassan Haes Alhelou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Environmental Pollutant ◽  
Optimal Operation ◽  
Energy Sources ◽  
Pollution Effects ◽  
Multi Objective ◽  
Operational Energy ◽  
The Impact

Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.

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