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275 results on '"A. Rezaee Jordehi"'

1. A two-stage optimal mechanism for managing energy and ancillary services markets in renewable-based transmission and distribution networks by participating electric vehicle and demand response aggregators

Author

XiaoPei Nie, Seyed Amir Mansouri, Ahmad Rezaee Jordehi, and Marcos Tostado-Véliz

Subjects
Electricity grids, Electricity markets, Renewable energy sources, Electric vehicles, Demand response programs, Uncertainty, Production of electric energy or power. Powerplants. Central stations, TK1001-1841
Abstract

The growing uncertainties in power operations due to the integration of renewable generations (RGs) and electric vehicles (EVs) into electricity grids have amplified the significance of ancillary services (AS). These services have become essential to ensure the sustainable functioning of the grid. In light of this, we introduce a two-stage optimization framework to manage competitive energy and AS markets at the interface of the transmission system (TS) and distribution system (DS). Our approach takes into account a comprehensive set of economic, technical, and security factors. This mechanism is structured in two stages: the first stage encompasses the energy market, while the second stage encompasses AS markets. Spinning reserve (SR) is supplied by conventional thermal units (TUs), whereas regulation capacity is provided by energy storage systems (ESSs), fast-response generators, electric vehicles (EVs), and demand response (DR) aggregators. We applied this mechanism to a 30-bus transmission network connected to four 10-node DSs and utilized the GUROBI solver in GAMS for solving. The simulation results demonstrate that the engagement of DSs in the SR market reduces the reliance on costly TUs, thereby decreasing system costs by approximately 10%. Furthermore, involving ESSs, EVs, and DR aggregators in the regulation market enhances technical performance and results in a 6.91% reduction in total system costs. This approach provides a robust solution to the evolving challenges posed by RGs and EVs in modern electricity grids.

Published
2024
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46. Optimal placement of hydrogen fuel stations in power systems with high photovoltaic penetration and responsive electric demands in presence of local hydrogen markets

Author

Rezaee Jordehi, A, Mansouri, SA, Tostado-Véliz, M, Hossain, MJ, Nasir, M, Jurado, F, Rezaee Jordehi, A, Mansouri, SA, Tostado-Véliz, M, Hossain, MJ, Nasir, M, and Jurado, F

Abstract

In this research, a computationally-inexpensive stochastic MILP model is proposed for the optimal placement of hydrogen fuel stations (HFSs) in power systems with high penetration of renewables, while power system operator sells its extra hydrogen in a day-ahead local hydrogen market. In the developed model, a linearisation strategy is proposed to transform the nonlinear binary terms into linear terms and the uncertainties of electricity and hydrogen demands, photovoltaic (PV) generation and hydrogen market prices are modeled as scenarios. Any available HFS includes an electrolyzer and a hydrogen storage system. As the penetration of renewables in the studied power system is high, most of the produced hydrogen is green. According to the results, system operator uses the potential of hydrogen storage systems and responsive electricity demands to sell more hydrogen to the local hydrogen market and increase its profit. In times with higher hydrogen prices, system operator commands both shift-down in electricity demands and discharge mode for batteries to be able to sell more electricity and make more profit; on the other hand, in times with lower hydrogen prices, system operator commands shift-up in electricity demands and charge mode for batteries. The results show that demand response program increases expected profit of system by 4.7%. The results confirm that addition of HFSs strongly decreases PV curtailment. The impact of the participation in hydrogen market on system profit is assessed. The sensitivity of HFS profit to the number of HFSs, size of electrolyzers and demand response participation factor is assessed.

Published
2024

47. A risk-averse two-stage stochastic model for optimal participation of hydrogen fuel stations in electricity markets

Author

Rezaee Jordehi, A, Mansouri, SA, Tostado-Véliz, M, Carrión, M, Hossain, MJ, Jurado, F, Rezaee Jordehi, A, Mansouri, SA, Tostado-Véliz, M, Carrión, M, Hossain, MJ, and Jurado, F

Abstract

In this paper, a novel stochastic risk-averse mixed-integer linear programming (MILP) model is developed for optimal electricity procurement of hydrogen fuel stations (HFSs) with responsive hydrogen demands. In the developed model, HFS operator may procure its required electricity through day-ahead (DA) market, bilateral contracts, a contract with withdrawal penalty (CWP) and balancing market. The HFS is committed to inject a pre-specified volume of hydrogen into a natural gas network. In the developed stochastic model, the uncertainties in hydrogen demand and DA market prices are characterized as random variables and modeled as scenarios. The developed model is a two-stage model in which the decisions on transactions with bilateral contracts are the first-stage decision variables and the other decision variables belong to the second stage. The risk of suffering from high procurement costs is modeled using the Conditional Value at Risk (CVaR). The results confirm the efficiency of the proposed model both in terms of reduction in HFS expected cost and risk alleviation. The results show that the transaction through bilateral contracts decreases the expected cost and CVaR respectively by 6% and 3%. The results also indicate that the participation in the balancing market decreases the expected cost and CVaR respectively by 6% and 1.6%. As per results, in scenarios in which DA market prices are lower than CWP prices, HFS operator prefers to pay a penalty fee and withdraw from CWP. The sensitivity of HFS profit to the weight factor of risk metric and the participation factor of responsive demands are assessed.

Published
2024

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