A Modified Hybrid Particle Swarm Optimization With Bat Algorithm Parameter Inspired Acceleration Coefficients for Solving Eco-Friendly and Economic Dispatch Problems

Abbas, Ghulam; Satrya, Gandeva Bayu; Usman, Muhammad Rehan

doi:10.1109/access.2021.3085819

Cited by 34 publications

(36 citation statements)

References 69 publications

(87 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An improved hybrid particle swarm optimization algorithm based on PSO and HPSOBA is proposed to solve economic dispatch problems containing conventional as well as hybrid and renewable energy sources. The results demonstrate the superior performance of the developed algorithm in terms of fuel cost reduction, faster convergence and computation time (Ellahi et al, 2021). Ref.…”

Section: Introductionmentioning

confidence: 77%

Economic dispatch using modified bat algorithm

Yang

Yuan

et al. 2022

Front. Energy Res.

View full text Add to dashboard Cite

Due to the frequent opening and shutting of turbine valves in the power system, valve point effect (VPE) that makes the economic dispatching (ED) problem non-linear, non-smooth and non-convex may be generated. Moreover, various constraints appear in the operation process, such as network transmission loss, and power balance during unit operation, which make it more difficult to find the global optimum through traditional mathematical methods. Nowadays, intelligent algorithms have successfully become a useful optimization tool to deal with nonlinear problems. In this paper, an improved bat algorithm (IBA), into which random black hole strategy and Gaussian mutation are introduced, is proposed to solve the ED problem. Furthermore, the random black hole strategy can enhance the diversity of the population and improve the convergence speed of IBA. Gaussian mutation is adopted to help jumping out of the local optimum. IBA is tested in 50 and 100 dimensions on 10 sets of well-known benchmark functions respectively, and compared with the methods in literature to verify its feasibility. Then, three different scales economic dispatching problems (3 units, 13 units, 40 units) are solved by this method, which further proves its effectiveness. The results show that IBA has obvious advantages and practical application value compared with other optimization methods.

show abstract

Section: Introductionmentioning

confidence: 77%

Economic dispatch using modified bat algorithm

Yang

Yuan

et al. 2022

Front. Energy Res.

View full text Add to dashboard Cite

show abstract

“…Taken 2 cases data 10 generators 13 generator system. Authors of [7] proposed hybrid particle swarm optimization and bat algorithm to find the optimal solution of the economic dispatch with renewable energy sources. Article [8] invented a new PSO technique that is very effective to find out the optimum solution for the random data set.…”

Section: Introductionmentioning

confidence: 99%

Minimization of Environmental Emission and cost of generation by using economic load dispatch

Singh

Tiwari

Chakrabarti

et al. 2022

Preprint

View full text Add to dashboard Cite

CONTEXT most of the electrical power is generated by thermal power plants. When a thermal plant is operated it can induce carbon dioxide and other toxic gases which can pollute the environment and reduce the life of living nature. Also, the cost of electrical power generation increases if the demand increases. OBJECTIVE This work proposed the economic load dispatch, which can help to generate the electrical power as per the load demand and save coal as well as reduce the emission of toxic gases. METHODS This work considers the latest variant of particle swarm optimization techniques, which can help to optimize the economic load dispatch. The help of case study shows the effectiveness of ELD and PSO techniques. RESULTS AND CONCLUSIONS This article discussed the above-mentioned problem and gave solutions. Taking different case studies and calculating the cost and environmental emission using ELD and optimization techniques. So following the economic load dispatch method for the generation of power in thermal power plants and using suitable optimization techniques, it is possible to reduce the cost as well as emission. If using the green energy system with a thermal power plant system is also economical and free from environmental emissions.

show abstract

“…Moreover, the rapid increase in the size and power demand of power systems resulted in reduced operating costs while maintaining the thermal limitations of voltage security and transmission line branching. Many mathematical programming and artificial intelligence techniques, such as GA-based ELD, Particle Swarm Optimization (PSO)-based ELD [7,8], ELD based on dynamic programming and evolutionary programming, and hybrid GA-PSO-based ELD, are applied to solve the aforementioned problem. In the most common formulation, the ELD problem is modeled as a large-scale, non-convex, nonlinear, static optimization problem in both discrete and continuous control variables [9].…”

Section: Introductionmentioning

confidence: 99%

“…In the most common formulation, the ELD problem is modeled as a large-scale, non-convex, nonlinear, static optimization problem in both discrete and continuous control variables [9]. Many researchers [6][7][8][9] have modeled the nonlinear, convex nature of ELD problems using pure quadratic functions, with the quadratic coefficients (a, b, and c) defined at the start of the solution search process. Meanwhile, research work [10] developed realistic models to incorporate the effect of multiple fuel cost functions and valve-point loading into the formulation of the ELD problem.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, research work [10] developed realistic models to incorporate the effect of multiple fuel cost functions and valve-point loading into the formulation of the ELD problem. For example, the authors in [8] employed PSO with the BAT algorithm for solving ELD problems considering inspired acceleration coefficients. In [9], the authors analyzed the generating unit profiles of various distributed generation systems of different technologies.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimized Economic Load Dispatch with Multiple Fuels and Valve-Point Effects Using Hybrid Genetic–Artificial Fish Swarm Algorithm

et al. 2021

View full text Add to dashboard Cite

Economic Load Dispatch (ELD) plays a pivotal role in sustainable operation planning in a smart power system by reducing the fuel cost and by fulfilling the load demand in an efficient manner. In this work, the ELD problem is solved by using hybridized robust techniques that combine the Genetic Algorithm and Artificial Fish Swarm Algorithm, termed the Hybrid Genetic–Artificial Fish Swarm Algorithm (HGAFSA). The objective of this paper is threefold. First, the multi-objective ELD problem incorporating the effects of multiple fuels and valve-point loading and involving higher-order cost functions is optimally solved by HGAFSA. Secondly, the efficacy of HGAFSA is demonstrated using five standard generating unit test systems (13, 40, 110, 140, and 160). Finally, an extra-large system is formed by combining the five test systems, which result in a 463 generating unit system. The performance of the developed HGAFSA-based ELD algorithm is then tested on the six systems including the 463-unit system. Annual savings in fuel costs of $3.254 m, $0.38235 m, $2135.7, $9.5563 m, and $1.1588 m are achieved for the 13, 40, 110, 140, and 160 standard generating units, respectively, compared to costs mentioned in the available literature. The HGAFSA-based ELD optimization curves obtained during the optimization process are also presented.

show abstract

A Modified Hybrid Particle Swarm Optimization With Bat Algorithm Parameter Inspired Acceleration Coefficients for Solving Eco-Friendly and Economic Dispatch Problems

Cited by 34 publications

References 69 publications

Economic dispatch using modified bat algorithm

Economic dispatch using modified bat algorithm

Minimization of Environmental Emission and cost of generation by using economic load dispatch

Optimized Economic Load Dispatch with Multiple Fuels and Valve-Point Effects Using Hybrid Genetic–Artificial Fish Swarm Algorithm

Contact Info

Product

Resources

About