A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Stochastic multi-objective scheduling of a combined cooling, heating and power microgrid containing a fuel cell
Combined cooling, heating and power (CCHP) microgrids that use fuel cells have a promising future, because they are energy efficient, have low emissions, and consume less energy. This study investigates the optimal energy management of a CCHP microgrid that includes a photovoltaic, a battery, a fuel cell, a gas boiler, a thermal storage tank, an absorption chiller, and an electric chiller, with a cooling, heating and power load. A multi-objective chance-constrained programming model is proposed, which aims to minimize the total running costs, and SO2 and NOx emissions. A Monte-Carlo stochastic simulation technique is applied to deal with the stochastic characteristics of the PV cells, and the cooling, heating and power loads. An improved multi-objective particle swarm optimization with Pareto set is proposed to solve the model. Simulation results of a hotel building show that the proposed approach can reduce the emissions of the pollutants, and effectively improve the system's efficiency.
Stochastic multi-objective scheduling of a combined cooling, heating and power microgrid containing a fuel cell
Combined cooling, heating and power (CCHP) microgrids that use fuel cells have a promising future, because they are energy efficient, have low emissions, and consume less energy. This study investigates the optimal energy management of a CCHP microgrid that includes a photovoltaic, a battery, a fuel cell, a gas boiler, a thermal storage tank, an absorption chiller, and an electric chiller, with a cooling, heating and power load. A multi-objective chance-constrained programming model is proposed, which aims to minimize the total running costs, and SO2 and NOx emissions. A Monte-Carlo stochastic simulation technique is applied to deal with the stochastic characteristics of the PV cells, and the cooling, heating and power loads. An improved multi-objective particle swarm optimization with Pareto set is proposed to solve the model. Simulation results of a hotel building show that the proposed approach can reduce the emissions of the pollutants, and effectively improve the system's efficiency.
Stochastic multi-objective scheduling of a combined cooling, heating and power microgrid containing a fuel cell
Sheng, Wanxing (author) / Peng, Shuyong (author) / Tang, Yiyuan (author) / Meng, Xiaoli (author) / Wang, Delin (author) / Wu, Zhi (author) / Gu, Wei (author)
2015-11-01
16 pages
Article (Journal)
Electronic Resource
English
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