Scenario-based Co-Optimization of neighboring multi carrier smart buildings under demand response exchange

摘要

Nowadays energy management of smart buildings with environmentally oriented intentions has become as one of the most critical challenges in human societies. To address this issue, this paper proposes an unprecedented cost-emission based scheme for energy management of interconnected multi energy hubs (MEH) aimed at minimizing the procurement costs as well as reducing carbon emission. These two incompatible objectives are optimized by means of epsilon-constraint technique and max-min fuzzy decision making to create an impartial compromise between cost saving and environmental obligations. The proposed MEH consists of three networked energy hubs with different distributed renewable and dispatch-able energy resources along with electrical/thermal energy storages and plug-in electric vehicles, which are connected to each other and exchange electricity and heat between themselves in such a way that minimize the operating costs of whole system. Meanwhile, an impressive price-based demand response program is included in the scheme to optimize the operating costs of MEH. The demands of MEH include electrical and thermal loads that have priced in time-of-use tariff to investigate the impact of energy carrier prices on the operation costs of MEH. Furthermore, an efficient scenario-based stochastic programming has been employed to tackle the uncertainty induced by renewable productions. Finally, the problem is solved by CPLEX solver under GAMS software and comparison numerical results are duly depicted to acknowledge sufficiency of the proposed approach. The results evidenced that the proposed MEH structure not only reduces the procurement costs of whole system, but also increases system independence from upstream network by exchanging power and heat between networked energy hubs. (C) 2019 Elsevier Ltd. All rights reserved.