The Optimal Energy Dispatch of Cogeneration Systems in a Liberty Market

This paper proposes a novel approach toward solving the optimal energy dispatch of cogeneration systems under a liberty market in consideration of power transfer, cost of exhausted carbon, and the operation condition restrictions required to attain maximal profit. This paper investigates the cogener...

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Bibliographic Details
Published in:Energies (Basel) 2019-07, Vol.12 (15), p.2868
Main Authors: Lin, Whei-Min, Yang, Chung-Yuen, Tu, Chia-Sheng, Huang, Hsi-Shan, Tsai, Ming-Tang
Format: Article
Language:English
Subjects:
Algorithms
Ant Colony Optimization
Artificial intelligence
Boilers
Capacitors
CO2 emission
Cogeneration
cogeneration systems
Cooperative learning
Efficiency
Electric rates
Electrical engineering
Electricity
Electricity distribution
Emissions
Energy
Genetic algorithms
Linear programming
Optimization
Radial basis function
Steam
Time of use electricity pricing
Time-of-Use (TOU)
Turbines
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Summary:This paper proposes a novel approach toward solving the optimal energy dispatch of cogeneration systems under a liberty market in consideration of power transfer, cost of exhausted carbon, and the operation condition restrictions required to attain maximal profit. This paper investigates the cogeneration systems of industrial users and collects fuel consumption data and data concerning the steam output of boilers. On the basis of the relation between the fuel enthalpy and steam output, the Least Squares Support Vector Machine (LSSVM) is used to derive boiler and turbine Input/Output (I/O) operation models to provide fuel cost functions. The CO2 emission of pollutants generated by various types of units is also calculated. The objective function is formulated as a maximal profit model that includes profit from steam sold, profit from electricity sold, fuel costs, costs of exhausting carbon, wheeling costs, and water costs. By considering Time-of-Use (TOU) and carbon trading prices, the profits of a cogeneration system in different scenarios are evaluated. By integrating the Ant Colony Optimization (ACO) and Genetic Algorithm (GA), an Enhanced ACO (EACO) is proposed to come up with the most efficient model. The EACO uses a crossover and mutation mechanism to alleviate the local optimal solution problem, and to seek a system that offers an overall global solution using competition and selection procedures. Results show that these mechanisms provide a good direction for the energy trading operations of a cogeneration system. This approach also provides a better guide for operation dispatch to use in determining the benefits accounting for both cost and the environment in a liberty market.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12152868