Multi-objective optimisation of an interactive buildings-vehicles energy sharing network with high energy flexibility using the Pareto archive NSGA-II algorithm - Zhou, Yuekuan; Cao, Sunliang; Kosonen, Risto; Hamdy, Mohamed (Energy conversion and management, 2020)
Multi-objective optimisation of interactive buildings-vehicles energy sharing network. [Display omitted] •A synergic buildings-vehicles energy sharing network with multiple interactions.•Energy flexibility exploitation with the advanced grid-responsive control strategy.•Techno-economic and multiple criteria with cost, emission and energy flexibility.•Multi-objective optimization using the Pareto archive NSGA-II algorithm.•Optimal solutions to energy-related conflicts for multi-criteria decision-makers. Systematic interactions between buildings, vehicles, and renewables can increase eco-economic viability on a neighbourhood scale. In this study, an interactive buildings-vehicles energy sharing network with multidirectional energy interactions was formulated for energy interactions and integrations together with a grid-responsive strategy for the management of off-peak renewable energy and grid electricity. Energy flexibility indicators (e.g., off-peak surplus renewable shifted ratio and off-peak grid shifted ratio) were introduced, developed, and implemented in an interactive buildings-vehicles energy sharing network for the energy flexibility assessment. Several energy-related conflicts, such as energy congestion contradiction and energy-related economic and environmental conflicts, were presented and discussed together with effective solutions provided to decision-makers for optimal design and robust operation. To reach a trade-off between energy-related conflicts, multi-objective optimisation was conducted, and implemented with an advanced multi-objective optimisation algorithm (called Pareto archive NSGA-II). The research results show that the formulated interactive buildings-vehicles energy sharing network demonstrates greater robustness and competitiveness than the conventional isolated system in terms of cost, emissions, and energy flexibility. Regarding multiple energy-related conflicts in the formulated interactive energy sharing network, the results show that multi-objective optimisation is able to decrease the equivalent CO2 emissions of the buildings-vehicles energy system by 7.5%, from 147.4 to 136.4 kg/m2.a, and reduce the import cost from the electric grid by 8.5%, from 212.7 to 194.6 HK$/m2.a, together with a high energy flexibility: a maximum of 11.03% (1.5% in a conventional isolated system) of the off-peak grid electricity can be stored by the electrical storages and a maximum of 52.48% (33.6% in the conventional isolated system) of the off-peak surplus renewable electricity can be shifted to peak period. This study formulates an interactive energy sharing network between buildings and vehicles, together with quantifiable energy flexibility assessment criteria and effective solutions for dealing with multiple energy-related conflicts, which are critical for interactive buildings-vehicles energy sharing networks with high energy flexibilities in smart cities.