Journal article Open Access

A Novel Stochastic Reserve Cost Allocation Approach of Electricity Market Agents in the Restructured Power Systems

Amin Shokri Gazafroudi; Miadreza Shafie-khah; Mehrdad Abedi; S. Hossein Hosseinian; Gholam Hossein Riahy Dehkordi; Lalit Goel; Peyman Karimyan; Francisco Prieto-Castrillo; Juan Manuel Corchado; João P.S.Catalão

In this paper, a new mechanism is proposed to apportion expected reserve costs between
electricity market agents in the power system. The uncertainties of generation units, transmission lines, wind
power generation and electrical loads are considered in this model. Hence, a Stochastic Unit Commitment

(SUC) is used to apply the uncertainty of stochastic variables in the simultaneous energy and reserve market-
clearing problem. Moreover, electrical customers can participate in the electricity market based on their

desired strategies. In this paper, a novel method is proposed to allocate reserve costs between GenCos,
TransCos, electrical customers and wind farm owners. Consequently, market agents are responsible for
paying a portion of the allocated expected reserve costs based on the economic metrics that are defined for
the first time in this paper. Finally, two cases including a 3-bus test system and IEEE-RTS are utilized to
illustrate the performance of the proposed mechanism to share the expected reserve costs.

Amin Shokri Gazafroudi, Francisco Prieto-Castrillo, and Juan Manuel Corchado acknowledge the support by the European Commission H2020 MSCA-RISE-2014: Marie Sklodowska-Curie project DREAM-GO Enabling Demand Response for short and real-time Efficient And Market Based Smart Grid Operation - An intelligent and real-time simulation approach ref. 641794. Moreover, Miadreza Shafie-khah and João P. S. Catalão acknowledge the support by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under Projects SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, and UID/EMS/00151/2013, and funding from the EU 7th Framework Programme FP7/2007-2013 under GA no. 309048.
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