Multitasking multi-objective operation optimization of integrated energy system considering biogas-solar-wind renewables

Abstract

The optimal operation of integrated energy systems (IESs) is of great significance to facilitate the penetration of distributed generators and improve its overall efficiency. A grid-connected IES is proposed in this paper for the synergetic interactions of electricity, thermal and gas energy flows, in which the biogas-solar-wind complementarities are fully considered and the digester heating is applied to provide an appropriate temperature for biogas production from anaerobic digestion. Its multi-objective optimization (MOO) model is constructed to optimize the operational cost, carbon dioxide emission and energy loss while considering digesting thermodynamic effects for anaerobic digester and uncertainty of wind and solar power, which is then compared to that of a natural gas-solar-wind IES. Thereafter, we develop an improved realization of multitasking paradigm within the domain of MOO to simultaneously solve the multi-objective operation optimization of the two IESs. In the associated multitasking algorithm, the underlying similarities of distinct optimization tasks are learned online to mitigate the harmful inter-task interactions and thereby facilitate improved convergence characteristics. The efficacy of the proposed multitasking algorithm has been comprehensively assessed on a novel biogas-solar-wind IES and a natural gas-solar-wind IES. Simulation results validated that the proposed IES can be operated in a more cost-efficient and environmentally friendly manner by comparing to the natural gas-solar-wind IES; the developed multitasking MOO algorithm can provide a better performance than other state-of-art multitask and single-task optimization algorithms.