Economic Load Dispatch Incorporating Wind Power Using Hybrid Biogeography-Based Optimization

2021 ◽  
Vol 12 (3) ◽  
pp. 54-80
Author(s):  
Bikram Saha ◽  
Provas Kumar Roy ◽  
Barun Mandal
Keyword(s):  
Wind Power ◽  
Optimization Algorithm ◽  
Special Kind ◽  
Economic Load Dispatch ◽  
Operational Cost ◽  
Renewable Sources ◽  
Salp Swarm Algorithm ◽  
Test Systems ◽  
Recommended Algorithm ◽  
Swarming Behaviour

This article represents salp swarm algorithm (SSA) for the most favourable operating solution of economic load dispatch (ELD). For making the convergence first along with SSA, another optimization algorithm (i.e., BBO [biogeography;based optimization]) is also used. For lowering the operational cost, wind power is employed with thermal units. SSA is inspired by swarming behaviour of salp, which belongs to salpiside family. Salp possess a special kind of swarm while hunting for food and navigating. The recommended algorithm is executed on two systems of SIX units and 40 units. In both of the cases, load dispatch problem is carried out with renewable sources and also without renewable sources. Individually, BBO, SSA, and hybrid BBO-SSA are applied to all the test systems to justify effectiveness of hybrid BBO-SSA. Obtained results assure the prospective and advantages of recommended algorithm in contrast to algorithms mentioned in the article. Results come out to be very satisfying and reveal that hybrid BBO-SSA is a powerful algorithm to solve ELD problems.

Co-Optimization of Output and Reserve with Significant Penetration of Renewables

2013 ◽  
Vol 427-429 ◽  
pp. 341-345
Author(s):  
Xue Fei Chang ◽  
Zhe Yong Piao ◽  
Xiang Yu Lv ◽  
De Xin Li
Keyword(s):  
Quadratic Programming ◽  
Wind Power ◽  
Sequential Quadratic Programming ◽  
Renewable Generation ◽  
Renewable Sources ◽  
Reliability Level ◽  
Maximum Benefit ◽  
Proposed Model ◽  
Programming Techniques

Co-optimization of output and reserve is necessary in order to provide maximum benefit to both consumers and producers. Once renewable generation sources like wind or solar begin to make up a large proportion of the generation mix, this co-optimization becomes much more difficult since the output of renewable sources is not well-known in advance. In this paper, a uniform reliability level is used as a constraint in the process of output and reserve. The proposed model is tested on the modified 5-bus PJM system. The co-optimization is performed by sequential quadratic programming techniques. The results show that the co-optimization results are strongly related to the uncertainties of wind power, the reliability level of the system, and the reliability of generators when wind makes up a significant portion of the generation mix.

scholarly journals Frequency Support Markets and Wind Power Integration

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7450
Author(s):  
Anzhelika Ivanova ◽  
José Luis Domínguez-García ◽  
Cristina Corchero
Keyword(s):  
Wind Power ◽  
Electricity Markets ◽  
Power Plants ◽  
Economic Benefits ◽  
Ancillary Services ◽  
Renewable Sources ◽  
Wind Generators ◽  
Wind Power Plants ◽  
Market Practices ◽  
System Benefit

Europe’s initiative to reduce the emissions of harmful gases has significantly increased the integration of renewable sources into power networks, particularly wind power. Variable renewable sources pose challenges to sustain the balance between generation and demand. Thus, the need for ancillary services to cope with this problem has increased. In this regard, the integration of larger shares of wind generation would have a clear system benefit when wind generators are able to provide these ancillary services. This would also have implications for electricity markets, enabling these services from wind power plants. This article gives an overview of several European markets for frequency support (FS) services, also referred to as FS markets. It identifies the changes in national regulations of 10 European countries to standardize these services based on the ENTSO-E guidelines. However, most of the countries still use their national service definitions, which presents a problem for researchers to understand the national regulations in relation to the ENTSO-E guidelines. This article provides a classification of the national FS services under the definitions of the ENTSO-E guidelines to facilitate research on this topic. Furthermore, it highlights the main requirements for the market practices that would encourage the participation of wind power generation in the provision of these services. An estimation of the economic benefits for wind producers from the provision of FS services is provided as well to show a possible outcome if changes are not made in national policies.

scholarly journals Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology that Combines the Salp Swarm Algorithm and the Successive Approximation Method

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2837
Author(s):  
Andrés Alfonso Rosales Muñoz ◽  
Luis Fernando Grisales-Noreña ◽  
Jhon Montano ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Distributed Generation ◽  
Direct Current ◽  
Mathematical Formulation ◽  
Average Power ◽  
Power Losses ◽  
Salp Swarm Algorithm ◽  
Test Systems ◽  
Distributed Generators ◽  
Optimal Power ◽  
Solution Methodology

This paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks by considering the integration of Distributed Generators (DGs). In order to model said problem, this study employs a mathematical formulation that has, as the objective function, the reduction in power losses associated with energy transport and that considers the set of constraints that compose DC networks in an environment of distributed generation. To solve this mathematical formulation, a master–slave methodology that combines the Salp Swarm Algorithm (SSA) and the Successive Approximations (SA) method was used here. The effectiveness, repeatability, and robustness of the proposed solution methodology was validated using two test systems (the 21- and 69-node systems), five other optimization methods reported in the specialized literature, and three different penetration levels of distributed generation: 20%, 40%, and 60% of the power provided by the slack node in the test systems in an environment with no DGs (base case). All simulations were executed 100 times for each solution methodology in the different test scenarios. The purpose of this was to evaluate the repeatability of the solutions provided by each technique by analyzing their minimum and average power losses and required processing times. The results show that the proposed solution methodology achieved the best trade-off between (minimum and average) power loss reduction and processing time for networks of any size.

A new Hybrid Taguchi-salp swarm optimization algorithm for the robust design of real-world engineering problems

2021 ◽  
Vol 63 (2) ◽  
pp. 157-162
Author(s):  
Ali Rıza Yıldız ◽  
Mehmet Umut Erdaş
Keyword(s):  
Objective Function ◽  
Optimization Algorithm ◽  
Structural Design ◽  
Design Problem ◽  
Optimization Techniques ◽  
Stress Constraint ◽  
Element Analysis ◽  
Salp Swarm Algorithm ◽  
Grasshopper Optimization Algorithm ◽  
Swarm Algorithm

Abstract In this paper, a new hybrid Taguchi salp swarm algorithm (HTSSA) has been developed to speed up the optimization processes of structural design problems in industry and to approach a global optimum solution. The design problem is posed for the shape optimization of a seat bracket with a mass objective function and a stress constraint. Objective function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations necessary for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm and, Harris hawks optimization algorithm are used to compare the performance of the HTSSA in solving the structural design problem. The results show the hybrid Taguchi salp swarm algorithm’s ability and the superiority of the method developed for optimum product design processes.

A New Heuristic Algorithm for Economic Load Dispatch Incorporating Wind Power

2021 ◽  
pp. 47-65
Author(s):  
N. Karthik ◽  
A. K. Parvathy ◽  
R. Arul ◽  
K. Padmanathan
Keyword(s):  
Wind Power ◽  
Heuristic Algorithm ◽  
Economic Load Dispatch

Scope of Biogeography Based Optimization for Economic Load Dispatch and Multi-Objective Unit Commitment Problem

2014 ◽  
Vol 3 (4) ◽  
pp. 34-54 ◽  
Author(s):  
Vikram Kumar Kamboj ◽  
S.K. Bath
Keyword(s):  
Optimization Algorithm ◽  
Unit Commitment ◽  
Optimization Problems ◽  
Simple Procedure ◽  
Mathematical Formulation ◽  
Economic Load Dispatch ◽  
Unit Commitment Problem ◽  
Multi Objective ◽  
Commitment Problem ◽  
Population Based Algorithm

Biogeography Based Optimization (BBO) algorithm is a population-based algorithm based on biogeography concept, which uses the idea of the migration strategy of animals or other spices for solving optimization problems. Biogeography Based Optimization algorithm has a simple procedure to find the optimal solution for the non-smooth and non-convex problems through the steps of migration and mutation. This research paper presents the solution to Economic Load Dispatch Problem for IEEE 3, 4, 6 and 10-unit generating model using Biogeography Based Optimization algorithm. It also presents the mathematical formulation of scalar and multi-objective unit commitment problem, which is a further extension of economic load dispatch problem.

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