Multi-objective Optimal Dispatch of Multi-energy Complementary Systems Considering Environmental Factors

In this paper, a day-ahead economic and environmental dispatching model for multi-energy complementary system composed of thermal power, wind and photovoltaic power, and pumped storage is established. The objective functions are the smallest net load fluctuation and the lowest comprehensive cost. In...

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Published in:Chinese Control Conference pp. 1771 - 1775
Main Authors: Chen, Rui, Yao, Yubin, Du, Jianwei, Yang, Fan
Format: Conference Proceeding
Language:English
Published: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2024
Subjects:
Carbon Trading
Costs
Desulfurization and Denitrification
Dispatching
Fluctuations
Multi-objective Particle Swarm Algorithm
Optimal Dispatch
Particle swarm optimization
Photovoltaic systems
Power systems
Simulation
ISSN:1934-1768
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Abstract In this paper, a day-ahead economic and environmental dispatching model for multi-energy complementary system composed of thermal power, wind and photovoltaic power, and pumped storage is established. The objective functions are the smallest net load fluctuation and the lowest comprehensive cost. In this model, the environmental cost is considered in comprehensive cost which includes the cost of \mathrm{SO}_{2}, \mathrm{NO}_{x} emission, the operation cost of desulfurization and denitrification, and carbon trading. An improved multi-objective particle swarm algorithm which can accelerate the convergence speed and also avoid the emergence of local optimums is presented to solve the dispatch model, and finally, by analyzing the dispatching results, it can effectively reduce the comprehensive cost of the system and decrease the net load fluctuation while reducing the pollutant emission, which verifies the effectiveness of the dispatch strategy and the improved algorithm.
AbstractList In this paper, a day-ahead economic and environmental dispatching model for multi-energy complementary system composed of thermal power, wind and photovoltaic power, and pumped storage is established. The objective functions are the smallest net load fluctuation and the lowest comprehensive cost. In this model, the environmental cost is considered in comprehensive cost which includes the cost of \mathrm{SO}_{2}, \mathrm{NO}_{x} emission, the operation cost of desulfurization and denitrification, and carbon trading. An improved multi-objective particle swarm algorithm which can accelerate the convergence speed and also avoid the emergence of local optimums is presented to solve the dispatch model, and finally, by analyzing the dispatching results, it can effectively reduce the comprehensive cost of the system and decrease the net load fluctuation while reducing the pollutant emission, which verifies the effectiveness of the dispatch strategy and the improved algorithm.
Author Yao, Yubin
Chen, Rui
Yang, Fan
Du, Jianwei
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  organization: Dalian Maritime University,School of Marine Electrical Engineering,Dalian,116026
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  givenname: Fan
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Snippet In this paper, a day-ahead economic and environmental dispatching model for multi-energy complementary system composed of thermal power, wind and photovoltaic...
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StartPage 1771
SubjectTerms Carbon Trading
Costs
Desulfurization and Denitrification
Dispatching
Fluctuations
Multi-objective Particle Swarm Algorithm
Optimal Dispatch
Particle swarm optimization
Photovoltaic systems
Power systems
Simulation
Title Multi-objective Optimal Dispatch of Multi-energy Complementary Systems Considering Environmental Factors
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