CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm

Ara, Afshin Lashkar; Shahi, Nastaran Mohammad; Nasir, Mohammad

doi:10.1007/s40998-019-00293-5

Cited by 15 publications

(10 citation statements)

References 30 publications

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“…The SRPSO algorithm was used in a comparison to solve the problem of CHPED by taking into account fuel costs and power losses, and thereafter to obtain sustainable energy [59]. The SRPSO algorithm is an improved form of PSO.…”

Section: Optimization and Sustainable Buildingsmentioning

confidence: 99%

“…With respect to the number of research papers, Asia has 54% of publications in the current research regarding the sustainable energy resources. This development mostly takes place in India [50,59,62] and China [53,69] publications in the current research regarding the sustainable energy resources. This development mostly takes place in India [50,59,62] and China [53,69] for understandable reasons.…”

Section: Distribution Of Papers To Different Continentsmentioning

confidence: 99%

“…Various improved versions of the HS approach are implemented in the present study, and a comprehensive review in the field of HS implementation for energy system issues is conducted. The SRPSO algorithm was used in a comparison to solve the problem of CHPED by taking into account fuel costs and power losses, and thereafter to obtain sustainable energy [59]. The SRPSO algorithm is an improved form of PSO.…”

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confidence: 99%

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Sustainability and Optimization: From Conceptual Fundamentals to Applications

2020

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In recent years, both sustainability and optimization concepts have become inseparable developing topics with diverse concepts, elements, and aspects. The principal goal of optimization is to improve the overall sustainability including the environmental sustainability, social sustainability, economic sustainability, and energy resources sustainability through satisfying the objective functions. Therefore, applying optimization algorithms and methods to achieve the sustainable development have significant importance. This paper represents a considerable review on the employed optimization methodologies to sustainability and the sustainable development including sustainable energy, sustainable buildings, and sustainable environment. Since energy optimization is one of the major necessities of sustainability, sustainable development is investigated from the energy perspective. In addition, the concept, definitions, and elements of the sustainability and optimization have been presented, and the review of the optimization metaheuristic algorithms used in recent published articles related to sustainability and sustainable development was carried out. Thus, it is believed that this paper can be appropriate, beneficial, and practical for students, academic researchers, engineers, and other professionals.

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Section: Optimization and Sustainable Buildingsmentioning

confidence: 99%

Section: Distribution Of Papers To Different Continentsmentioning

confidence: 99%

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confidence: 99%

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Sustainability and Optimization: From Conceptual Fundamentals to Applications

2020

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“…Aiming at the problem of energy dispatching route cost, Ara et al [18] proposed a self-regulating PSO algorithm to reduce energy costs in energy dispatching under the premise of ensuring time. Li et al [19] proposed an improved new mayfy algorithm to reduce operating costs on the basis of ensuring the stability and balance of grid energy dispatch.…”

Section: Introductionmentioning

confidence: 99%

Energy Dispatching Based on an Improved PSO-ACO Algorithm

Song

et al. 2023

International Journal of Intelligent Systems

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In order to improve the comprehensive performance of energy dispatching between different sites, the optimization research of particle swarm optimization (PSO) algorithm and ant colony optimization (ACO) algorithm is carried out. We proposed a new improved PSO-ACO algorithm based on the idea of hybrid algorithm to solve the problem of poor energy dispatching efficiency between sites. First, the multiobjective performance indicators were introduced to transform the sites’ energy dispatching problem into a multiobjective optimization problem. Second, the vitality factor was introduced into the PSO strategy to solve the local optimal problem, and in the PSO-ACO fusion strategy, the PSO routes were transformed into the ant colony enhancement pheromone to accelerate the accumulation speed of the ACO initial pheromone. Then, the angle guidance function was introduced into the state transition probability of the ACO strategy to improve the global search capability, and a high-quality pheromone update rule was proposed to improve the convergence speed of the algorithm. Finally, simulation experiments were carried out on the improved PSO-ACO algorithm, Min–Max Ant System (MMAS) algorithm, ACO algorithm, PSO algorithm, and PSO update algorithm in a variety of complex site scenarios. The simulation results show that the improved PSO-ACO algorithm can plan a site energy dispatching route with shorter route, less time-consuming, and higher security and realize the comprehensive and global optimization of energy dispatching.

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“…The combined heat and power dispatch (CHPED) problem has been realized using a real coded genetic algorithm [3], improved group search algorithm [4], oppositional teaching-learning based optimization [5], modified particle swarm optimization (PSO) [6], self-regulating PSO [7], cuckoo search algorithm (CSA) [8], gravitational search algorithm [9], exchange market algorithm [10], group search algorithm [11], and grey wolf optimization (GWO) [12] using different test cases. The demand-side management and the optimal operational problem of the MG were studied using a hybrid genetic algorithm (GA) and artificial bee colony (ABC) algorithm.…”

Section: Introductionmentioning

confidence: 99%

CHP-Based Economic Emission Dispatch of Microgrid Using Harris Hawks Optimization

Tiwari¹,

Dubey²,

Pandit³

et al. 2022

Fluids

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In this paper, the economically self-sufficient microgrid is planned to provide electric power and heat demand. The combined heat and power-based microgrid needs strategic placement of distributed generators concerning optimal size, location, and type. As fossil fuel cost and emission depend mainly on the types of distributed generator units used in the microgrid, economic emission dispatch is performed for an hour with a static load demand and multiple load demands over 24 h of a day. The TOPSIS ranking approach is used as a tool to obtain the best compromise solution. Harris Hawks Optimization (HHO) is used to solve the problem. For validation, the obtained results in terms of cost, emission, and heat are compared with the reported results by DE and PSO, which shows the superiority of HHO over them. The impact of renewable integration in terms of cost and emission is also investigated. With renewable energy integration, fuel cost is reduced by 18% and emission is reduced by 3.4% for analysis under static load demand, whereas for the multiple load demands over 24 h, fuel cost is reduced by 14.95% and emission is reduced by 5.58%.

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CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm

Cited by 15 publications

References 30 publications

Sustainability and Optimization: From Conceptual Fundamentals to Applications

Sustainability and Optimization: From Conceptual Fundamentals to Applications

Energy Dispatching Based on an Improved PSO-ACO Algorithm

CHP-Based Economic Emission Dispatch of Microgrid Using Harris Hawks Optimization

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