Stochastic dynamic solution for off-design operation optimization of combined cooling, heating, and power systems with energy storage

摘要

Combined cooling, heating, and power (CCHP) systems are generally considered as a viable solution to meeting both the electric and thermal demands of buildings in metropolises. To ensure that CCHP systems operate at the optimal schedule, operation optimization is crucial. The nonlinearity of off-design performance, randomness of renewables and loads, and relationship between adjacent stages stemming from energy storage are three challenges that should be simultaneously addressed. In this paper, we propose a stochastic dynamic solution to perform the above-mentioned operation optimization, which is resolved into a dynamic optimization problem consisting of many small static optimization problems. By applying the proposed method, the expected most economical operating schedule of a CCHP system with storage units can be obtained. As demonstrated through a case study, the proposed method reduces the operation cost by 13.4 RMB compared with a linear model used to describe the off-design performance. Moreover, a CCHP system with strong randomness shows operation cost reduction worth 10.4 RMB (1.66%) compared with that of the deterministic optimization. Hence, the stochastic dynamic solution can address off-design performance efficiently and is especially practical for use in CCHP systems with stochastic renewables.