Integration of Smart Energy Hubs in Distribution Networks Under Uncertainties and Demand Response Concept

• Published in: IEEE transactions on power systems Vol. 34; no. 1; pp. 566 - 574
• Main Authors: Majidi, Majid, Zare, Kazem
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biological system modeling; Boilers; Cogeneration; Computer simulation; Decision theory; demand side management programs (DSMPs); Distribution management; Distribution network; Economics; Electric power systems; Energy distribution; Energy industry; Energy management; Energy sources; epsilon-constrained method; fuzzy decision making approach; Hubs; hybrid scenario-based/interval/information gap decision theory (IGDT) method; Load modeling; Networks; Optimization; Parameter uncertainty; Priorities; smart energy hubs (S. E. Hubs); Uncertainty
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2018.2867648

Multienergy systems are flexible energy systems that can benefit from energy resources to supply different energy demands. Due to the capabilities of multienergy systems in generating different energy carriers, these systems have been rapidly expanded in power systems. After restructuring in power system in recent years and appearance of competent energy markets, energy systems operated within such environments have been usually exposed to uncertainties of various parameters, such as price, demand, etc. In this paper, a novel optimization framework based on hybrid scenario-based/interval/information gap decision theory method is developed to investigate the optimal operation of smart energy hubs (S. E. Hubs) subject to economic priorities, technical constraints of the distribution network and uncertainties. Considering energy hubs equipped to smart facilities, demand-side management programs including price response and load response services have been available to motivate electrical consumers to revise their consumption pattern in order to satisfy economic priorities of energy hubs. By using the results of employed hybrid uncertainty modeling approach, the operator of S. E. Hubs can decide either to take risk-averse or risk-seeking strategy against the uncertainties. Uncertainty based integration of S. E. Hubs into distribution network is evaluated regarding the IEEE 33-bus test system and the results obtained from simulations are presented for comparison.