scholarly journals Energy management in smart grids for the integration of hybrid wind–PV–FC–battery renewable energy resources using multi-objective particle swarm optimisation (MOPSO)

2018 ◽  
Vol 2018 (11) ◽  
pp. 1806-1816 ◽  
Author(s):  
Adel Elgammal ◽  
Mohamed El-Naggar
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Smart Grids ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Multi Objective

scholarly journals Multi-Objective Energy Management of a Micro-Grid Considering Stochastic Nature of Load and Renewable Energy Resources

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Deyaa Ahmed ◽  
Mohamed Ebeed ◽  
Abdelfatah Ali ◽  
Ali S. Alghamdi ◽  
Salah Kamel
Keyword(s):  
Renewable Energy ◽  
Objective Function ◽  
Energy Management ◽  
Energy Resources ◽  
Management Problem ◽  
Renewable Energy Resources ◽  
Multi Objective ◽  
Stochastic Nature ◽  
Whale Optimization ◽  
Micro Grid

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.

Energy Optimization and Power Stack Shed Reduction of Oil Depots by using Renewable Energy Resources

2021 ◽  
Vol 4 (2) ◽  
pp. 125-130
Author(s):  
Muhammad Azhar Mahmood ◽  
Muhammad Kamran Liaqat Bhatti ◽  
S. Raza ◽  
M. Riaz
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Energy Management ◽  
Unit Cost ◽  
Research Work ◽  
Energy Resource ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Oil Sector ◽  
Continuous Power

Most of the industries including the oil sector are looking forward towards the renewable energy resources with proper energy management system (EMS) as it is the need of time. For this purpose, solar and wind energy are the renewable energy resources, which are obtained from natural resources and produce clean and environment -friendly electrical energy and can be used for oil depots. The proper utilization of solar and wind energy from natural resource may result in economical and cost-effective EMS. In the proposed research work, an effective energy management demonstration is delivered to ensure the ceaseless flexibility of power. Furthermore, reduction of production per unit cost to the oil sector industry by utilizing multiple objectives streamlining. In the proposed oil depot, connected loads are divided into Shiftable and Non-Shiftable loads and then apply Branch and Bound Algorithm (BnB) with binary integer linear programming (BILP). By using the BnB technique, selected shiftable loads are shifted to the low cost energy resource automatically and resultantly, we get the low price unit cost and continuous power supply. Simulation results for the above-mentioned research work are performed on MATLAB. The proposed technique helps to reduce the power stack shedding issue as well.

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