Optimization and trading of district multi-energy system in university community considering carbon emission

Abstract

With the increasing deployment of distributed energy resources (DERs) and operation of diverse energy devices, different types of multi-energy systems (MESs) emerge. Constrained by physical networks, when economic and environmental benefits are considered, how to stimulate the potential of energy shifting and conversion across temporal and spatial dimensions becomes a significant issue. This requires an innovative multi-energy trading mechanism. Due to the diversity of building types and energy categories, as well as the loads complementarity, the university community is an applicable user cluster for the investigation of multi-energy trading. The district energy operator (DEO) contributes to making deals via the interactive information of prices and quantities, besides protecting the prosumers' privacy. This paper treats carbon as a direct trading object and proposes an internal multi-energy trading mechanism, which adopts an auction based on the demands for cooling, heating, electricity and carbon, and is formed as a nonlinear equilibrium program with equilibrium constraints (EPEC) problem. The nonlinear EPEC problem is then solved by particle swarm optimization (PSO) algorithm. It is a novel mechanism in which the prosumers submit prices and quantities simultaneously, instead of utilizing traditional linear supply functions. A hypothetical university community in the U.K. is studied to discover the internal price signals. Simulation results show that, the proposed trading mechanism benefits from exploiting the energy sharing potential of the community MES, as well as improving the players' revenues. Meanwhile this mechanism presents good performances when tackling the infrequent load growth, and facing the change of exterior market prices or rules.