Dynamic energy. exergy and market modeling of a High Temperature Heat and Power Storage System

The novel and simple yet efficient system of HTHPSS (High Temperature Heat and Power Storage System) suitable for the locations with high heating demand as well as electricity demand was previously proposed and investigated in terms of economic justification by the authors [9]. In the present work. a detailed dynamic energy and exergy modeling of this energy storage unit in combination with wind turbines is presented to evaluate to what extend it is efficient enough for long term storage with dynamic power supply and energy output. For this objective. an efficient operational (charging and discharging) strategy algorithm was developed for an energy storage system with 100 MW capacity supporting a wind turbine farm with maximum power production capacity of 100 MWp in Denmark-West as the case study of this work. The investigations showed that both energy and exergy ef- ficiencies are in very good levels. In addition. the most important sources of energy loss and exergy destructions are identified to guide optimization and practical efforts to enhance the levels of obtainable efficiencies. For example. in the heat exchangers. higher temperature difference between the inlet and outlet conditions make considerable amount of irreversibility in the system. thus optimizing the heat exchange methodology may increase the effi- ciency of the system significantly. Also. energy losses from the cavern are extremely high due to the very high temperature of storage and minimizing heat losses by employing better insulation materials may help to achieve better efficiency. Another important point is that the algorithm developed for defining the operational strategy of the system is not the optimal case and it is expected that a more accurate algorithm. for specifying the system charging (low electricity price) and discharge (high electricity and electricity price) periods. makes the system more efficient technically and economically. This would be a multi-optimization algorithm as all of the effective parameters of the system operation. i.e. wind power. electricity price and heat price. fluctuate sharply.

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