Opportunistic Info-Gap Approach for Optimization of Electrical and Heating Loads in Multi-Energy Systems in the Presence of a Demand Response Program

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Vahid-Ghavidel, M (Author) Other; Javadi, MS (Author) Other; Santos, SF (Author) Other; Gough, M (Author) Other; Shafie-khah, M (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)

21st IEEE International Conference on Environment and Electrical Engineering / 5th IEEE Industrial and Commercial Power Systems Europe (EEEIC/I and CPS Europe)

Politecnico Bari, Bari, ITALY, SEP 07-10, 2021

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: P-00W-BCT

DOI: 10.1109/eeeic/icpseurope51590.2021.9584597

Abstract (EN): There are significant changes occurring both in the electricity system and the natural gas system. These two energy carries can be combined to form what is known as an energy hub. These energy hubs can play a significant role in the energy system and thus understanding of their optimization, especially their costs, is important. This paper proposes a risk management framework for an energy-hub through the utilization of the information-gap decision theory (IGDT). The uncertainties introduced from the various load profiles, such as the electric and heating loads, are considered in this risk management framework. The modeled energy-hub consists of several distributed generation systems such as a microcombined heat and power (mu CHP), electric heat pump (EHP), electric heater (EH), absorption chiller (AC) and an energy storage system (ESS). A demand response (DR) program is also considered to shift a percentage of electric load away from the peak period to minimize the operational cost of the hub. A feasible test system is also applied to demonstrate the proposed model's effectiveness.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6