Information gap-based scheduling strategy of a multi-energy retailer with integrated demand response program

Abstract

• Modeling a multi-energy retailer in the framework of multi-carrier energy systems. • Developing a multi-energy retailer based on gas/cooling/heating/power carriers. • Presenting an IGDT method to cope with uncertainties in the optimization model. • Integrating flexible options, e.g. hybrid energy storage in the optimization model. • Proposing integrated DR to control multiple energy demands simultaneously. Multi-energy systems (MESs) were introduced to enhance the flexibility and efficiency of conventional energy distribution systems. In this new trend, it is possible to supply different energy carriers simultaneously by the multi-energy retailer (MER), under which, without the need to transfer all of them to different locations, the loads are fed centrally, and the customers can purchase all the carriers they need from the desired MER. Motivated by these descriptions, this paper focuses on the optimal scheduling of MER in the integrated energy system, including natural gas, electricity, cooling, and heating, under the information gap decision theory (IGDT) framework. The MER's goal is to maximize profits by considering the uncertainty of the day-ahead power market. The proposed IGDT approach without a probabilistic distribution function analyzes the risk-aversion strategy associated with electricity price uncertainty. In this paper, integrated demand response (IDR) for natural gas, electrical, heating, and cooling loads are developed simultaneously as a flexible demand-side management resource. The proposed model contains multiple technologies owned by MER, including hybrid energy storage technology, combined heat and power, chiller, boiler units, and renewable resources. Numerical results from different cases illustrate the effectiveness of IDR installation in terms of profitability. Besides, the MER can serve multiple demands more efficiently. Under the IGDT approach, the purchasing power cost is reduced up to 24.23%.