Two-stage stochastic optimization frameworks to aid in decision-making under uncertainty for variable resource generators participating in a sequential energy market

H., Al-Lawati, Razan A.; Crespo-Vazquez, Jose L.; Faiz, Tasnim Ibn; Fang, Xiuzhong; Noor‐E‐Alam, Md.

doi:10.1016/j.apenergy.2021.116882

Cited by 22 publications

(7 citation statements)

References 44 publications

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“…Authors in [10] investigate a phase-based decision-making model for the participation of wind generation owners in different power markets based on a two-stage stochastic programming (SP) method and exhibit the importance of information updating in sequential optimization. A two-stage SP with chance constraints framework is established in [11] by scenario trees to obtain a tradeoff between costs and service quality which manages both the day-ahead bidding and real-time dispatch strategy of EH incorporating AC/DC microgrids.…”

Section: Two-stage Probabilistic Optimization Of Eh Schedulingmentioning

confidence: 99%

“…On the other hand, as mentioned in [20], usually these energy conversion devices run continuously, and few units shut down for idle. Since our work focuses on the coordinated energy bidding of EH in hybrid trading markets, and robust scheduling strategies hedging against worst-case uncertain distributions in different timescales, the multi-energy management model without considering nonlinear conversion features [11], [30] and startup shutdown costs [10], [31] can also be expressed. Interested readers can refer to [9] and [32] for more information about needed solution methods.…”

Section: Energy Hub Model Developmentmentioning

confidence: 99%

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Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling

et al. 2022

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Section: Two-stage Probabilistic Optimization Of Eh Schedulingmentioning

confidence: 99%

Section: Energy Hub Model Developmentmentioning

confidence: 99%

Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling

et al. 2022

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“…Where ∆ Ps , ∆ P up s and ∆ P dw s are imbalance power, positive imbalance power and negative imbalance power in a SI. (21) calculates imbalance power that is the difference among HA power schedule and DA promised power as well as regulation power. The set S tN O S is defined as…”

Section: B Balancing Market Optimizationmentioning

confidence: 99%

“…In addition, ancillary services provision by HPPs is becoming another promising revenue stream as described in the literature. The optimal trade of power reserve in reserve market is discussed in [20], [21], while the provision of frequency containment normal reserve (FCR-N) in DA FCR-N market is investigated in [22]. The trade of regulation power in hour-ahead (HA) balancing market is considered as a revenue stream in [23].…”

Section: Introductionmentioning

confidence: 99%

Optimal Participation of Co-located Wind-battery Plants in Sequential Electricity Markets

Zhu¹,

Das²,

Sørensen³

et al. 2022

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<p>Since hybrid power plants (HPPs) play an intensive role in the energy supply balance of future energy systems, there is today an increased attention on co-located wind-battery HPPs both in industry and academia. However, the profitability of HPPs in sequential electricity markets to overcome initial investment costs has not been yet well examined, especially with respect to balancing services provision. This article proposes a novel energy management system (EMS) for optimal participation of wind-battery HPPs in two sequential electricity markets, namely in spot market and balancing market. The methodology consists of three optimization models, which allow HPPs to achieve energy arbitrage, to provide balancing services, and to reduce real-time imbalance costs. Furthermore, the profitability of HPPs in future (2030) energy scenario is analyzed based on the new designed and developed EMS taking balancing service into account. The results of the overplanting case show that HPPs operated based on the proposed EMS achieve net present value 3.6 times as high as sole operation in spot market.</p>

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“…Uncertainty presents a non-trivial challenge to decision-making. Stochastic programming is a popular approach for developing decision-making frameworks for energy applications since it allows uncertainty to be incorporated into the model [91]. A common technique for handling uncertainty in stochastic programming is introducing many scenarios, each representing a realization of the uncertain parameters.…”

Section: The Use Of Decomposition Techniquesmentioning

confidence: 99%

Decision making under uncertainty for variable resource generators participating in energy markets

Al Lawati

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Your constant support, encouragement, and guidance have been invaluable throughout this journey, and I am indebted to your unwavering dedication to my success. I also extend a special thanks to my committee members, Dr. Kayse Lee Maass and Dr. Xiaoning "Sarah" Jin, Associate Professors, Mechanical and Industrial Engineering. Your thoughtful feedback, insightful comments, and critical analysis have greatly shaped this work and helped me to grow as a researcher. I would also like to acknowledge my colleagues at the Decisions Analytics lab, Dr. Tasnim Ibn Faiz, Dr. Jose Luis Crespo, and Victoria Okra. Your technical support and assistance in talking through the models were essential to the success of this project. I am grateful for your knowledge, expertise, and friendship. I am also indebted to Dr. Alison Miller, Dr. Melinda Valente, and all my friends at The Academic Writers Space for creating a welcoming and supportive environment full of understanding, encouragement, and laughs. Your kindness and generosity have been a source of inspiration throughout this journey. And last but never least, my family, for always being there, no matter what.

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Two-stage stochastic optimization frameworks to aid in decision-making under uncertainty for variable resource generators participating in a sequential energy market

Cited by 22 publications

References 44 publications

Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling

Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling

Optimal Participation of Co-located Wind-battery Plants in Sequential Electricity Markets

Decision making under uncertainty for variable resource generators participating in energy markets

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