The Use of Grey Wolf Optimizer (GWO) for Solving the Economic Dispatch Problems based on Renewable Energy in Algeria A case study of "Naama Site"

2019 ◽  
Vol 1 (6) ◽  
pp. 34-41
Author(s):  
Mokhtar MAAMRI
Keyword(s):  
Renewable Energy ◽  
Economic Dispatch ◽  
Grey Wolf Optimizer ◽  
Grey Wolf

scholarly journals Penyelesaian Masalah Economic Dispatch Menggunakan Equilibrium Optimizer

2021 ◽  
Vol 13 (1) ◽  
pp. 10-17
Author(s):  
Osea Zebua ◽  
I Made Ginarsa ◽  
I Made Ari Nrartha
Keyword(s):  
Case Studies ◽  
Economic Dispatch ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Total Load ◽  
Load Demand ◽  
Whale Optimization ◽  
Operating Constraints ◽  
Fuel Costs

This paper presents a metaheuristic method, namely Equilibrium Optimizer (EO) to solve the economic dispatch (ED) problem. The main objective function to be achieved is to minimize the total fuel costs of all generating units to meet the total load demand and to satisfy various operating constraints. Three case studies are used to test the effectiveness of the EO method in solving ED problems, they are three generators case, six generators case, and fifteen generators case. The simulation of solving ED problems using the EO method is implemented using MATLAB software and is carried out 30 times for each case study. The results of EO method are compared with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) methods. The simulation results show that the EO method can solve the ED problem more optimal than all other comparison methods for all the case studies by producing the minimum total fuel costs.

scholarly journals Multi-Objective Sizing Optimization of Hybrid Renewable Energy Microgrid in a Stand-Alone Marine Context

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 174
Author(s):  
Wenqiang Zhu ◽  
Jiang Guo ◽  
Guo Zhao
Keyword(s):  
Renewable Energy ◽  
Optimization Problem ◽  
System Optimization ◽  
Economic Benefits ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Energy Management Strategy ◽  
Sizing Optimization ◽  
Multi Objective ◽  
Hybrid Renewable Energy

Islands are the main platforms for exploration and utilization of marine resources. In this paper, an island hybrid renewable energy microgrid devoted to a stand-alone marine application is established. The specific microgrid is composed of wind turbines, tidal current turbines, and battery storage systems considering the climate resources and precious land resources. A multi-objective sizing optimization method is proposed comprehensively considering the economy, reliability and energy utilization indexes. Three optimization objectives are presented: minimizing the Loss of Power Supply Probability, the Cost of Energy and the Dump Energy Probability. An improved multi-objective grey wolf optimizer based on Halton sequence and social motivation strategy (HSMGWO) is proposed to solve the proposed sizing optimization problem. MATLAB software is utilized to program and simulate the optimization problem of the hybrid energy system. Optimization results confirm that the proposed method and improved algorithm are feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. The proposed HSMGWO shows better convergence and coverage than standard multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO) in solving multi-objective sizing problems. Furthermore, the annual operation of the system is simulated, the power generation and economic benefits of each component are analyzed, as well as the sensitivity.

scholarly journals Optimal Power Flow Solutions Incorporating Stochastic Solar Power withthe Application Grey Wolf Optimize

2021 ◽  
Vol 03 (01) ◽  
pp. 74-84
Author(s):  
Nadir Taleb ◽  
◽  
Bachir Bentouati ◽  
Saliha Chettih ◽  
◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Solution ◽  
Electrical Network ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Renewable Energy Resources ◽  
Network Constraints ◽  
Optimal Power

The present paper aims to validate an electrical network study in consisting of conventional fossil fuel generators with the integration of intermittent generation technologies based on renewable energy resources like wind power or solar photovoltaic (PV) are the stochastic power output. By using an optimal power flow (OPF) problem different frameworks are developed for solving that represent various operating requirements, such as minimization of production fuel cost, and preserving generation emission at the lowest levels... etc. The OPF analysis aims to find the optimal solution and is very important for power system operation with satisfying operational constraints, planning and energy management. However, the intermittent combination of solar exacerbates the complexity of the problem. Within the framework of these criteria, this paper is an overview of the application Grey Wolf Optimizer (GWO) algorithm which solves the OPF problem with renewable energy. The algorithm thus combined and constructed gives optimum results satisfying all network constraints. Give an explanation for findings are based thus need to be with the optimum to effectuate of network constraints.

Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer

2015 ◽  
Vol 785 ◽  
pp. 511-515 ◽  
Author(s):  
Lo Ing Wong ◽  
Mohd Herwan Sulaiman ◽  
Mohd Rusllim Mohamed
Keyword(s):  
Canis Lupus ◽  
Economic Dispatch ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Ramp Rate ◽  
Nonlinear Characteristics ◽  
Simulation Results ◽  
Alpha Beta ◽  
Ramp Rate Limits ◽  
Practical Constraints

This paper presents the application of a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus) for solving economic dispatch (ED) problems. The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting: searching for prey, encircling prey and attacking prey are implemented. In this paper, GWO was demonstrated and tested on two well-known test systems with practical constraints. A comparison of simulation results is carried out with those published in the recent literatures. The results show that the GWO algorithm is able to provide very competitive results for nonlinear characteristics of the generators such as ramp rate limits, prohibited zone and non-smooth cost functions compared to the other well-known meta-heuristics techniques.

Economic dispatch using hybrid grey wolf optimizer

Energy ◽  
2016 ◽  
Vol 111 ◽  
pp. 630-641 ◽  
Author(s):  
T. Jayabarathi ◽  
T. Raghunathan ◽  
B.R. Adarsh ◽  
Ponnuthurai Nagaratnam Suganthan
Keyword(s):  
Economic Dispatch ◽  
Grey Wolf Optimizer ◽  
Grey Wolf

Enhanced whale optimization algorithm for sizing of hybrid wind/photovoltaic/diesel with battery storage in Algeria desert

2021 ◽  
pp. 0309524X2110565
Author(s):  
Adel Yahiaoui ◽  
Abdelhalim Tlemçani
Keyword(s):  
Renewable Energy ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Energy System ◽  
Whale Optimization Algorithm ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Hybrid Renewable Energy System ◽  
Whale Optimization ◽  
Hybrid Renewable Energy

This paper focuses on the optimization and operation of the renewable energy power sources for electrification of isolated rural city in Algeria desert. For this purpose, a system composed by photovoltaic (PV), wind turbine (WT), diesel generator (DG), and battery bank (BB) as well as for storing the energy in the electrical form to meet the load. In the present paper we are interested in evolutionary algorithms for solving optimization problem of hybrid renewable energy system. A new meta-heuristic algorithm namely whale optimization algorithm (WOA) is used to solve optimization problem of cost of energy (COE) and total net present cost (TNPC) including reliability evaluation by using basic probabilistic concept in order to find Loss of Power Supply Probability (LPSP). The WOA mimics the social behavior of humpback whales. This algorithm is inspired by the bubble-net hunting strategy. Three recent algorithms, particle swarm optimization (PSO), grey wolf optimizer (GWO), and modified grey wolf optimizer (M-GWO) are also implemented in this work. For examining the accuracy, stability, and robustness of proposed optimization technique two case studies have been tested. The results of simulations and comparison with other methods exhibit high accuracy and validity of the proposed whale optimization algorithm to solve optimization problem of hybrid renewable energy system.

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