Abstract

More and more operational flexibility is required from conventional power plants due to the increasing share of weather-dependent renewable energy sources (RES) generation in the power system. One way to increase power plant’s flexibility is integrating it with energy storage. The energy storage facility can be used to minimize ramping or shutdowns and therefore should lower overall generating costs and CO2 emissions. In this article, we examined the effects of a combined cycle gas turbine (CCGT) power plan and a compressed air energy storage (CAES) system integration. The main feature of the CCGT-CAES integration concept is using the CCGT installation as a heat recipient and provider for the CAES installation. This approach was applied to a real-life case study of the PGE Gorz´ow CCGT power plant. First, technical feasibility of itegrating a CCGT plant with a CAES system was verified and the restrictions on the operating conditions were identified. Next, the improvement in flexibility was quantified by the additional profits gained from the integration. Polish day-ahead electricity prices were used as a measure for remunerating flexibility. Two models were developed in the Python computer programming language: a thermodynamic one and an economic one. The former was buit without the use of flowsheeting software or purpose-built industry specific tool. The latter was implemented within the frame of the PuLP library and solved using its default solver (CBC). By means of mixed integer linear programming (MILP) optimal generation schedules and maximum profits were found for three cases: an independent operation of the CCGT, an integrated CCGT-CAES plant and an integrated CCGT-ES plant with 81% storage efficiency. The results of the computational simulations contradict the supposition that the integration is economically viable, even if mechanical energy storage efficiency of 81% is assumed. Regarding the impact of the integration on the optimal schedule, although it is negligible for the 56% mechanical energy storage efficiency case, a significant change in operation profiles is observed for the 81% case. The model developed here can be used either when making decisions about investment in flexibility improvements or for planning daily operation of a generating unit.

Citations

Authors (5)