A dynamic interactive optimization model of CCHP system involving demand-side and supply-side impacts of climate change. Part I: Methodology development

The climate change exerts the influence on user-side demand and supply-side output. It is vital important to formulate a dynamic interaction model under climate change, which incorporates user-demand prediction, power output calculation and synergetic operational optimization into a general framework. This figure describes the general procedure of the dynamic interaction model under climate change. [Display omitted] •The regional climate simulation model based on PRECIS software was established.•The building demand prediction under TRNSYS software environment was accomplished.•The power output of gas turbine was calculated based on mechanism simulation model.•The operation optimization model with precise supply–demand estimation was proposed.•It is expected to strengthen theoretical study of CCHP system operation management. Combined cooling, heating and power (CCHP) system, as a superior energy-provision form of public building, is capable of achieving flexible and stable energy provision with high energy-utilization efficiency and low pollutant emission. However, some difficulties exist in operating such a system, due to its intrinsic multi-period, multi-factor and multi-layer features. In addition, the fluctuation in weather elements under climate change exacerbates the inaccuracy of energy demand prediction and facilities’ power output calculation, leading to imbalanced energy supply and demand. To tackle this issue, a dynamic interactive model combining user-demand prediction, energy-provision calculation and operational collaborative optimization was developed. It attempts to combine the regional climate simulation (PRECIS), demand prediction (TRNSYS), equipment output calculation (mechanism modeling) and collaborative optimization (LINGO) into a general framework. The specific operation processes include: (i) utilize PRECIS model to identify the variations in temperature and radiation under climate change; (ii) exploit TRNSYS software to predict the users’ demand of targeted hospital in the future; (iii) establish a mechanism simulation model for gas turbine and estimate power output under extreme meteorological condition; (iv) incorporate the results generated by processes (ii) and (iii) into formulated operation optimization model of CCHP system; (v) generate optimal energy provision scheme adapted to climate change. This dynamic interactive model comprehensively considers the interactions at all aspects involved into operation management of CCHP