A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China

Abstract

Urban energy systems comprise various supply side technologies, by which heating, cooling and electricity energy are produced, converted and consumed in a given urban area. The number of alternative arrangements of technologies introduces many degrees of freedom, particularly where large numbers of buildings and networks are in play. The problem being modeled in the present study is to determine the best combination of technologies to meet the energy demand of district buildings subject to practical constraints. This district planning aims to establish a smart micro-grid for the application of renewable and clean energy. A range of technologies including gas turbine, absorption chiller, electrical chiller, condensing boiler, ground source heat pump, PV, electrochemical storage, heat storage, ice storage air-conditioning system etc., have been considered as alternative supply side technologies. A MINLP model is developed to solve the multi-objective optimization problem. Results are described by four scenarios, namely baseline scenario, low energy bill scenario, low CO2 emissions scenario and integrated scenario, showing that a significant reduction is achievable in net present value, primary energy saving and CO2 emissions by the installation of roof-top PV, ground source heat pump, natural gas-based CCHP and storage systems.