Optimal Dispatch Schedule For Combined Cooling, Heating And Power Microgrids

With the continuous development of economic society, the depletion of fossil resource, the escalation of air pollutant and the deterioration environment problem, it is inevitable to develop the clean, low carbon energy. Distributed renewable energy source has been paid more attention by many countries, and thus has gotten rapid development. An interesting candidate for domestic power generation is the combined cooling, heating and power (CCHP) system, which as name states, can provide cooling, heating and power energy at the same time. CCHP system is also referred as the tri-generation system, and it has been widely applied in hospitals, supermarkets, schools.At present, researches on CCHP microgrid mainly focus on day-ahead economic dispatch. Ln most of the research, the optimal operation of a CCHP microgrid assumes an accurate forecast for RES power and load. However, the forecasts for RES and load are often different from the actual conditions, which affect efficient and stable operation of the CCHP microgrid. The main work of this paper is how to deal with the uncertainties of renewable generations and load demands (thermal energy, cooling energy and electricity), and how to reduce the impact of the fluctuation of RES and load on the optimization operation of the system.The main work of this paper:(1)Modeling of the CCHP microgridFirstly, the mathematical models of photovoltaic power and wind power are set up. The key research of chapter is to study the operation characteristics of the micro gas turbines and fuel cells and establish the corresponding mathematical model. Models of battery, boiler electric chiller, absorption chiller, heat exchanger and thermal storage tank are also studied. The optimization operation of CCHP microgrid is based on the characteristics of each distributed unit, establishing accurate mathematical model. Establishing accurate mathematical model has a positive direct impact on energy management and optimization operation of the system.(2)The day-ahead and real-time dispatch modelThe dispatch model includes two parts:day-ahead scheduling dispatch and real-time adjusting dispatch. The day-ahead scheduling dispatch is an economic dispatch model to minimize the operating cost and provides the operation plans including commitment or output power of each unit, which is solved by a revised particle swarm optimization. The real-time adjusting dispatch deals with the fluctuations of power by adjusting the output power of the central air conditioning considering housing characteristics, and the batteries and other controllable units based on heuristic rules. In real-time adjusting dispatch model, the outdoor temperature of the house is taken into account in temperature dependent house modeling and the indoor temperature allows changes to some extent under the consideration of not affecting the residents' comfort. Real-time adjusting dispatch is utilized to maintain the exchange power between the main grids and the CCHP microgrid constant.(3) Optimal dispatch schedule for CCHP microgrid based on model predictive controlThe proposed approach includes two hierarchies—rolling optimization and feedback correction—both of which can handle the uncertainties. In the rolling part, prediction and optimization are conducted in each time interval. The optimal dispatch schedule is based on the latest forecast and the forecast is repeated in the next time interval, which may improve forecasting accuracy and decrease uncertainty. Only the first interval scheduling plan is implemented. Feedback correction is applied to modify the dispatch schedule and eliminate the impact of prediction error.