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17 results on '"Kohansal, Mahdi"'

1. A Data-Driven Convergence Bidding Strategy Based on Reverse Engineering of Market Participants' Performance: A Case of California ISO

Author

Samani, Ehsan, Kohansal, Mahdi, and Mohsenian-Rad, Hamed

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Economics - General Economics
Abstract

Convergence bidding, a.k.a., virtual bidding, has been widely adopted in wholesale electricity markets in recent years. It provides opportunities for market participants to arbitrage on the difference between the day-ahead market locational marginal prices and the real-time market locational marginal prices. Given the fact that convergence bids (CBs) have a significant impact on the operation of electricity markets, it is important to understand how market participants strategically select their CBs in real-world. We address this open problem with focus on the electricity market that is operated by the California ISO. In this regard, we use the publicly available electricity market data to learn, characterize, and evaluate different types of convergence bidding strategies that are currently used by market participants. Our analysis includes developing a data-driven reverse engineering method that we apply to three years of real-world data. Our analysis involves feature selection and density-based data clustering. It results in identifying three main clusters of CB strategies in the California ISO market. Different characteristics and the performance of each cluster of strategies are analyzed. Interestingly, we unmask a common real-world strategy that does not match any of the existing strategic convergence bidding methods in the literature. Next, we build upon the lessons learned from the existing real-world strategies to propose a new CB strategy that can significantly outperform them. Our analysis includes developing a new strategy for convergence bidding. The new strategy has three steps: net profit maximization by capturing price spikes, dynamic node labeling, and strategy selection algorithm. We show through case studies that the annual net profit for the most lucrative market participants can increase by over 40% if the proposed convergence bidding strategy is used., Comment: IEEE Transactions on Power Systems

Published
2021
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4. Building an Analytical Foundation to Study and Enhance the Bids in Wholesale Electricity Market

Author

Kohansal, Mahdi

Subjects
Engineering
Abstract

An efficient electricity market determines the operational mechanisms to maintain long-term and short-term power system reliability in a least-cost manner. The performance of the market not only depends on the market structure, but also the bidding mechanisms of the market participants including various generation resources, smart consumers and financial players. Our goal is to study and improve the bids in electricity market with focus on the California energy market. Therefore, in this thesis, a comprehensive analysis on the real bidding data from California electricity market has been done. It is concluded that compared to the supply side, the demand side in the California market is currently highly inelastic, leading to many undesirable consequences such as price spikes and exercising market power by generation companies. To address such issues, a new demand bidding framework has been proposed that recognizes the special characteristics of smart loads. The bids in this framework are called extended-time demand bids. The new framework resolves the problems of accommodating smart loads in the electricity market such as market instability and lack of equilibrium. Moreover, a novel strategy for large smart loads to procure their required energy in electricity market has been introduced. The proposed strategy is general and can be applied to both basic and complex smart load types.Finally, the performance of financial players bids known as Convergence Bids (CBs) have been studied. While CBs are designed to improve the market efficiency and decrease the price gap between day-ahead and real-time markets, there are recently serious concerns where CBs do not act as intended and their performance even result in decreasing market efficiency. Accordingly, we built an analytical foundation to explain under what conditions placing a CB at a bus in a nodal electricity market can decrease (increase) market efficiency. Specifically, it is shown that transmission line congestion can highly influence the performance of CBs. In particular, under certain transmission line congestion configurations, placing a CB at a bus can result in divergence (instead of convergence) between day-ahead and real-time markets prices.

Published
2018

16. An approach to improve dynamic response of VSIs in off-grid Microgrids.

Author

Kohansal, Mahdi, Moghani, Javad S., Rahmatian, Matin, and Gharehpetian, Gevorg B.

Abstract

Recently, voltage source inverters have been applied in a wide range in order to stabilize Microgrids (MGs). These inverters are controlled based on conventional droop method. This method satisfies power sharing between the inverters in steady state. Besides, it enrolls as the frequency controller in inverter-based systems such as MG. In this paper, a modified droop controller is proposed to improve the response speed of VSI during transient time while the power sharing between them is kept satisfied in steady state. This improvement is very useful to stabilize the frequency of independent MG after events leading to power imbalance. The effectiveness of the proposed method is validated after comparison with the conventional droop method through simulations. [ABSTRACT FROM PUBLISHER]

Published
2011
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17. Multi-objective optimization to improve transient performance of VSI in an off-grid micro-gird using imperialist competitive algorithm.

Author

Kohansal, Mahdi, Moghani, Javad S., Rahmatian, Matin, and Gharehpetian, Gevorg B.

Abstract

Micro-grids (MGs) are active networks known as an effective solution for the control of grids including high levels of Distributed Generation (DG). In off-grid MGs, DGs connected to Voltage Source Inverters (VSIs) enroll as controllers of voltage and frequency. These VSIs should share power between the DGs fairly. A precise power sharing may increase frequency drop. In this paper, a trade-off is obtained between power sharing and frequency behavior. A multi-objective function is defined including the aforementioned parameters. Imperialism Competitive Algorithm (ICA) is used for optimization process. The obtained parameters lead to the best performance of VSI controllers considering frequency behavior and power sharing. [ABSTRACT FROM PUBLISHER]

Published
2011
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