| Combined cooling, heating and power system(CCHP)has attracted much attentions to provide an efficient, reliable, economic and sustainable energy supply all around the world. As compared to central power plants, CCHPs can be used to meet the environmental commitments and increase energy efficiency of energy systems. Recently CCHPs have drawn considerable research attentions. A lot of CCHPs have established all over the world as well as in china.Many researches of CCHP focus on the operation strategies, such as following the electric load(FEL) and following the thermal load(FTL). Other researches concentrate on optimal energy management of CCHP and microgrid, such as mining the energy cost. In addition, the sizing of the CCHP system has also been researched by using the optimization method.In the paper, an optimization method considering both the consumer and factory is proposed.The method works as an energy management system. The method first analyze the power load, heating load and cooling load of the consumer and get some results, which are used to optimize operation strategies of CCHP system.In detail, the first part of the method is the load forecasting. More precisely, it is short-term load forecasting. The part get the load of next cycle using a data mining technology from the historical data as well as the other factors which have an impact on the load,such as the environment and calendar factors. There are three kinds of load: power load, heating load and cooling load. The second part is to optimize the operation strategy in a cost-effective way. It is a multi-objective problem, the one objective is mining the energy cost, the other is mining the reduction of greenhouse gas. The Pareto optimality is the solution to the multi-objective problem. In the work, a trade-off frontier between minimization of energy and minimization of GHG emissions is found to provide advice to operate the machines. At last, we work out how to adjust our equipment to achieve the different goals. |
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