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

Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power ener...

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Bibliographic Details
Published in:Iranian journal of science and technology. Transactions of electrical engineering 2020-09, Vol.44 (3), p.1147-1164
Main Authors: Lashkar Ara, Afshin, Mohammad Shahi, Nastaran, Nasir, Mohammad
Format: Article
Language:English
Subjects:
Algorithms
Climate change
Cogeneration
Cost function
Economics
Electric power
Electric power generation
Electric power loss
Electrical Engineering
Electricity consumption
Energy
Energy conservation
Energy consumption
Energy costs
Energy efficiency
Energy usage
Engineering
Green buildings
Green development
Heat
Inertia
Iterative methods
Optimization
Particle swarm optimization
Power dispatch
Renewable energy
Research Paper
Supply & demand
Sustainability
Sustainable energy
Weight reduction
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Summary:Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power energy to balance energy supply and demand, mitigate climate change and improve energy efficiency of sustainable cities and green buildings. In this paper for the first time, self-regulating particle swarm optimization (SRPSO) algorithm is utilized for solving the CHPED problem by considering valve point effects and prohibited zones on fuel cost function of pure generation units and electrical power losses in transmission systems. The main advantage of SRPSO algorithm to PSO algorithm is the inertia weight flexibility with respect to search conditions. In this algorithm, unlike PSO algorithm that inertia weight reduces in each iteration, this value increases or reduces proportional to particles’ positions, which will lead particles to achieve optimal value with higher speed. The capability and effectiveness of the proposed algorithm are evaluated on a large-scale energy system using MATLAB environment. The results obtained by SRPSO algorithm are outperformed by other optimization methods from the economic, sustainable energy and time consumption point of view.
ISSN:2228-6179
2364-1827
DOI:10.1007/s40998-019-00293-5