scholarly journals Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm

2021 ◽  
Vol 13 (14) ◽  
pp. 7710
Author(s):  
Mehrdad Tahmasebi ◽  
Jagadeesh Pasupuleti ◽  
Fatemeh Mohamadian ◽  
Mohammad Shakeri ◽  
Josep M. Guerrero ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Optimization Algorithm ◽  
New Technologies ◽  
Renewable Energy Sources ◽  
Optimization Methods ◽  
Optimal Operation ◽  
Whale Optimization Algorithm ◽  
Whale Optimization ◽  
Demand Response Program

Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the developing efficient optimization methods and algorithms in line with the increasing needs of microgrids, the focus of this study is on using the whale meta-heuristic algorithm for operation management of microgrids. The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization. Furthermore, the results show that the use of DRPS has a significant impact on the costs of operation and emissions.

scholarly journals Power system voltage instability risk mitigation via emergency demand response-based whale optimization algorithm

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Mohammed Amroune ◽  
Tarek Bouktir ◽  
Ismail Musirin
Keyword(s):  
Power Systems ◽  
Power System ◽  
Demand Response ◽  
Optimization Algorithm ◽  
Voltage Stability ◽  
Risk Mitigation ◽  
Stability Margin ◽  
Whale Optimization Algorithm ◽  
Voltage Instability ◽  
Whale Optimization

AbstractIn recent years, due to the economic and environmental issues, modern power systems often operate proximately to the technical restraints enlarging the probable level of instability risks. Hence, efficient methods for voltage instability prevention are of great importance to power system companies to avoid the risk of large blackouts. In this paper, an event-driven emergency demand response (EEDR) strategy based on whale optimization algorithm (WOA) is proposed to effectively improve system voltage stability. The main objective of the proposed EEDR approach is to maintain voltage stability margin (VSM) in an acceptable range during emergency situations by driving the operating condition of the power system away from the insecure points. The optimal locations and amounts of load reductions have been determined using WOA algorithm. To test the feasibility and the efficiency of the proposed method, simulation studies are carried out on the IEEE 14-bus and real Algerian 114-bus power systems.

Optimum utilization of grid connected hybrid renewable energy sources using hybrid algorithm

2020 ◽  
pp. 014233122091374
Author(s):  
M. Suresh ◽  
R. Meenakumari
Keyword(s):  
Renewable Energy ◽  
Tabu Search ◽  
Smart Grid ◽  
Optimization Algorithm ◽  
Renewable Energy Sources ◽  
Whale Optimization Algorithm ◽  
Computational Time ◽  
Energy Sources ◽  
Whale Optimization ◽  
Hybrid Renewable Energy

An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale optimization algorithm plus tabu search, called AWOTS. The main objective is the RES optimum operation for decreasing the electricity production cost by hourly day-ahead and real time scheduling. Here, the load demands are predicted using AWOTS to develop the correct control signals based on power difference between source and load side. Adaptive whale optimization algorithm searching behaviour is adjusted by tabu search. The proposed technique is executed in the MATLAB/Simulink working platform. To test the performance of the proposed method, the load demand for the 24-hour time period is demonstrated. By then the power generated in the sources, such as photovoltaic, wind turbine, micro turbine and battery by the proposed technique, is analyzed and compared with existing techniques, such as genetic algorithm, particle swarm optimization and whale optimization algorithm. Furthermore, the state of charge of the battery for the 24-hour period is compared with existing techniques. Likewise, the cost of the system is compared and error in the sources also compared. The comparison results affirm that the proposed technique has less computational time (35.001703) than the existing techniques. Moreover, the proposed method is cost-effective power production of smart grid and effective utilization of renewable energy sources without wasting the available energy.

scholarly journals Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2297 ◽  
Author(s):  
Wadood ◽  
Khurshaid ◽  
Farkoush ◽  
Yu ◽  
Kim ◽  
...  
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Operating Time ◽  
Whale Optimization Algorithm ◽  
Humpback Whales ◽  
Test Systems ◽  
Whale Optimization ◽  
Overcurrent Relays ◽  
Optimal Coordination ◽  
Hunting Strategy

In power systems protection, the optimal coordination of directional overcurrent relays (DOCRs) is of paramount importance. The coordination of DOCRs in a multi-loop power system is formulated as an optimization problem. The main objective of this paper is to develop the whale optimization algorithm (WOA) for the optimal coordination of DOCRs and minimize the sum of the operating times of all primary relays. The WOA is inspired by the bubble-net hunting strategy of humpback whales which leads toward global minima. The proposed algorithm has been applied to six IEEE test systems including the IEEE three-bus, eight-bus, nine-bus, 14-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed WOA are compared with those obtained by other up-to-date algorithms. The obtained results show the effectiveness of the proposed WOA to minimize the relay operating time for the optimal coordination of DOCRs.

scholarly journals An Improved Nonlinear Grey Bernoulli Model Based on the Whale Optimization Algorithm and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jianming Jiang ◽  
Ting Feng ◽  
Caixia Liu
Keyword(s):  
Optimization Algorithm ◽  
Structural Parameters ◽  
Optimization Methods ◽  
Whale Optimization Algorithm ◽  
Bernoulli Model ◽  
Proposed Model ◽  
Whale Optimization ◽  
Inherent Error ◽  
Applicable Range ◽  
The Difference

In order to improve the prediction performance of the existing nonlinear grey Bernoulli model and extend its applicable range, an improved nonlinear grey Bernoulli model is presented by using a grey modeling technique and optimization methods. First, the traditional whitening equation of nonlinear grey Bernoulli model is transformed into its linear formulae. Second, improved structural parameters of the model are proposed to eliminate the inherent error caused by the leap jumping from the differential equation to the difference one. As a result, an improved nonlinear grey Bernoulli model is obtained. Finally, the structural parameters of the model are calculated by the whale optimization algorithm. The numerical results of several examples show that the presented model’s prediction accuracy is higher than that of the existing models, and the proposed model is more suitable for these practical cases.

State Estimation of Power Using the Whale Optimization Algorithm

2020 ◽  
Vol 11 (4) ◽  
pp. 194-213
Author(s):  
Suvabrata Mukherjee ◽  
Provas Kumar Roy
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Optimization Algorithm ◽  
Measurement Errors ◽  
Population Based ◽  
Whale Optimization Algorithm ◽  
State Variables ◽  
Optimal Point ◽  
Whale Optimization ◽  
Population Based Algorithm

In power systems, the process of attaining a better prediction from a set of variables from state variables is called state estimation (SE). These variables consist of magnitudes of bus voltage and the corresponding angles of all the buses. Because of the non-linearity and intricacy of ever-developing power systems, it has become important to apply upgraded techniques for the dissolution and supervision in practical environments. The discussed analysis evaluates the appositeness of a new metaheuristic technique called the whale optimization algorithm (WOA) which is a population-based algorithm, to reduce the measurement errors so as to gauge the optimal point of the power system when some susceptible values are inadequate. WOA displays admirable attainment in global optimization. It employs a bubble-net hunting approach and it mimics the social behaviour of humpback whales to get the best candidate solution. The approach is tested on IEEE-14, IEEE-30, and IEEE-57 bus test systems and the potency is validated by comparison with the biogeography based optimization algorithm (BBO).

scholarly journals Whale Optimization Algorithm-Based DG Allotment for Loss Minimization of Distribution Networks

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Power Systems ◽  
Radial Distribution ◽  
Optimization Algorithm ◽  
Distribution Networks ◽  
Whale Optimization Algorithm ◽  
Humpback Whales ◽  
Loss Minimization ◽  
Optimum Placement ◽  
Suggested Technique ◽  
Whale Optimization

For optimum placement of distributed generation (DG) units in balanced radial distribution network for loss minimization, implementation of whale optimization algorithm (WOA), a state-of-the-art meta-heuristic optimization algorithm is proposed in this paper. Encouraged by bubble-net hunting strategy of whales, WOA mimes the collective practice of humpback whales. For validating performance in solving the mentioned problem, the suggested technique is implemented on IEEE 33-bus and IEEE 69-bus balanced radial distribution test networks. The obtained results demonstrate that feasible and effective solutions are obtained using the proposed approach and can be used as a propitious substitute in practical power systems to overcome the optimum DG siting and sizing issue. Also concerning the best knowledge of the authors, it is the first report on the application of WOA in solving optimum DG siting and sizing issue.

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