Flexibility and Economic Dispatch of Island Power Systems with Integrated Thermal Energy Storage in Smart Grids

orc2019 Tracking Number 208

The operation of combined cycle and steam-turbine power stations must meet the requirements for the high penetration of renewable energy sources under the EU framework of 2050 commitments. A modular, expandable, generalised adaptable configuration is investigated with the integration of Thermal Energy Storage (TES) systems. The efficiency of combined-cycle and steam-turbine power plants varies with the load demand. During off-peak demand, steam is extracted from the output of the boiler for charging an array of thermal tanks which are the evaporators of organic Rankine cycle (ORC) units and contain suitable phase-change materials (PCM). The outlet steam from the tank-ORC arrangement is returned to the inlet of the boiler. An Energy Management System (EMS) regulates the system such as to optimize the charging of the thermal tanks-evaporators during the off-peak demand. In the case that excess electrical energy from renewable energy sources is available on the grid, the ORC units also charge the thermal tanks operating inversely. Furthermore, due to the constraints for the minimum temperatures of PCMs related to the condenser minimum temperatures of the conventional power cycles, the EMS controls the ORCs units so that these constraint requirements are satisfied. At a later time when this is required and/or economically favourable, these thermal energy storage (TES) tanks can act as the heat sources of organic Rankine cycle (ORC) plants that are suitable for power generation at reduced temperatures and smaller scales. This type of solution offers greater flexibility than TES-only solutions that store thermal energy and then release this back to the original power station. This paper investigates the integration of such a Thermal Energy Storage System in the power System of Crete, Greece. The power system of Crete is currently an autonomous power system which is going to be interconnected to the Greek mainland System in the next few years. It operates with high levels of wind power penetration which is curtailed to avoid violation of technical constraints of compatible units and to ensure dynamic security of the system. It also comprises a lot of units with high fuel cost which operate during peak hours. Thus a storage system would provide both necessary flexibility and reduce cost during peak hours. In a case study where a 50-MW rated oil-fired power unit is considered, it is found through a thermodynamic analysis that a maximum combined power of 70 MW can be delivered during peak demand, which is 40% higher than the oil-fired plant’s full-load rating. The scenario also allows the reduction of the unit’s minimum power output from 27 MW to 16 MW, enhancing thus its flexibility. In order to perform a cost-benefit analysis of the TES of the above case study, a realistic model of the generation system of Crete projected to the year 2020 is considered as well as annual time series of load demand and Renewable Energy Sources generation. A Unit Commitment and Economic Dispatch algorithm is implemented in order to simulate the operation of TES over the long term. The algorithm is based on fuel cost and start-up/shut down cost minimization, subject to the technical constraints imposed by the generating units and TES. A stochastic algorithm is also used to simulate the generation outages incidents. Two cases are examined and compared to each other; the first represents the operation of the power system with the integration of TES, while the second is the system operation without TES installed. The benefit of the TES would be the difference in the annual cost of operation of the power system for the two cases. In addition, the contribution of TES to the generation adequacy of the System is estimated and the possible revenue from a capacity remuneration mechanism is taken into account in the cost benefit analysis. The above analysis is performed for various storage capacities in order to provide the optimal dimensioning of TES. The above analysis is also performed both for the case of autonomous and interconnected operation of the power system in Smart Grids.