A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system

Abstract

In this study, a nonlinear model-based dynamic optimal coordinated scheduling strategy was developed for a grid-connected integrated energy microgrid on a university campus. This integrated energy system (IES) consists of power grid, photovoltaic/wind power generator, buildings, electric batteries, and heat pumps with thermal energy storages (HPTES). Peak load shifting index, a new indicator, is proposed for evaluating the capability of energy storages for peak-shaving and valley-filling of the grid power and thermal load, and the stability of the power grid with renewables. Comparison of the performances of IES under three scenarios shows that through adopting high-efficient HPTES together with an optimal coordinated scheduling strategy, the penetration rate of renewable energy and the stability of IES can be enhanced significantly; while the operation cost, peak power, grid interactive power, peak load shifting index and CO2 emissions can be reduced significantly. Moreover, compared with the optimal scheduling strategy previously developed based on a linear model, the optimal scheduling strategy developed based on a dynamic nonlinear model can help to reduce the grid-connected time of the IES containing HPTES. This study would be useful for increasing the penetration rate of renewables and the stability of grid, as well as reducing the grid-disconnected time of an IES at a low operation cost in practice.