MINLP Probabilistic Scheduling Model for Demand Response Programs Integrated Energy Hubs

Abstract

In this paper, an optimal probabilistic scheduling model of energy hubs operations is presented. The scheduling of energy hub determines the energy carriers to be purchased as input and converted or stored, in order to meet the energy requests, while minimizing the total hub's cost. However, as many other engineering endeavors, future operating criteria of energy hubs could not be forecasted with certainty. Load and price uncertainties are the most unclear parameters that hub operators deal with. In this regard, this paper proposes a 2 $m$ + 1 point estimation probabilistic scheduling scheme for energy hubs with multiple energy inputs and outputs. One of the applicable tools of energy hubs to have an efficient participation in the liberalized power market with volatile prices is demand response programs (DRPs). While there is plenty of experience in investigating the effect of DRP, it is electricity DRP that receives increasing attention by research and industry. Therefore, the proposed DRP investigates the effect of both responsive thermal and electric loads in reducing the total cost and participation of different facilities in supplying multiple loads. The proposed model envisages the most technical constraints of converters and storages. Several test systems have been investigated in order to confirm the effectiveness of the proposed model. The results verify the capability of the proposed model in covering the energy hub time-varying output demands as well as the economic advantages of implementing the suggested strategy. In addition, the results are compared with 2 $m$ point estimate method and Monte Carlo simulation.