Optimal Predictive Control Strategies for Polygeneration Systems

The optimal energy control and management for smart grids as per virtual power plant concepts is of great importance for the coming future of the electricity grid and the energy market. The optimal energy management for housing applications necessitates the combined use of heat and electricity by the way of technologies like cogeneration engines, heat pumps and thermal storage which can be used to dephase the electricity and heat demand of the building of the district concerned. A major factor that will play a role in the effective usage of these technologies is the proper and optimal sizing of each of the conversion and storage units as per the demands of the occupants. Another factor, that may affect the optimal energy management of domestic applications is the pricing of electricity done through the energy exchanges around Europe. Energy management is especially important for Switzerland as it is seen as a major transit and exchange country in the European energy market owing to its position and the trade of energy between France, Germany, Italy and itself. Here, a study has been conducted that tries to link two of the above mentioned factors in the design of a polygeneration system design. This study aims to show the effect of implementation of cogeneration system (cogeneration engine with or without a back-up boiler) coupled with a heat pump to satisfy the needs of a building considering the use of an optimal predictive control strategy that is used to optimize the use of the storage tanks. The study aims to identify the differences in the demand with and without heat pump. Also, the study aims to show the potential for thermal/electric storage in a single family house for better management of demand from the grid. The effect of the implementation of thermal storage with cogeneration engine coupled with heat pump on the grid electricity is explored. The effect of change in the electricity prices and as well as of constraints imposed on the electricity variations through the day on the buildiing requirements with cogeneration engine coupled with heat pump and thermal storage over a day is studied and the different strategies are identified. The study is then extended to include different buildings with different energy demand profiles. The objective is to study any possible changes in the strategy of one building due to the presence of another building in the grid which can also buy and sell using the control strategies mentioned above. As a result, this also reveals the effect of the use of optimal control of multiple buildings connected to a micro grid on the sale or purchase of electricity from or to grid as well.