基于能量与信息耦合的分布式能源系统配置优化方法

In the distributed energy system (DES) that incorporates a high proportion of renewable energy, the uncertainties caused by the volatility of renewable energy and randomness of demand limit the improvement of the supply-and-demand matching. The information can be used as a means to eliminate uncertainty. In this paper, a unified scale of energy and information based on entropy was proposed, and the entropy theory was used to quantify both the energy unavailability caused by the energy grade decrease and the energy unavailability caused by the uncertainty, so as to describe the mechanism of information on the energy process quantitatively. Then, a case study was conducted using a data center DES to demonstrate the success of the proposed configuration optimization method based on the energy and information coupled. Under the consideration of the uncertainties of the meteorological parameters and the computational load in data center, the probability of the failing to meet the design yearly on-site energy fraction (OEF) is 15% at the optimization configuration, while it reaches to 54% under the configuration with minimum initial investment as the objective. In conclusion, the uncertainties could be effectively reduced by applied the configuration optimization method proposed in this paper, so as to improve the supply and demand matching of the DES.