Security-Constrained Unit Commitment for Electricity Market: Modeling, Solution Methods, and Future Challenges

Chen, Yonghong; Pan, Feng; Qiu, Feng; Xavier, Álinson S.; Zheng, Tongxin; Marwali, Muhammad; Knueven, Bernard; Guan, Yongpei; Luh, Peter B.; Wu, Lei; Yan, Bing; Bragin, Mikhail A.; Zhong, Haiwang; Giacomoni, Anthony M.; Baldick, Ross; Gisin, B.S.; Gu, Qun; Philbrick, Russ; Li, Fangxing

doi:10.1109/tpwrs.2022.3213001

Cited by 26 publications

(4 citation statements)

References 156 publications

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“…More powerful dispatch tools that can really solve the practical problem always attracts the attention from industries. However, we observe that there is still a clear gap between the ongoing academic research and the industrial requirements [26,27] . There are actually very few studies that exactly respond to the practical industrial requirement and provide a promising computational performance for practical applications.…”

Section: Proportion Of Electric Power (%)mentioning

confidence: 83%

Revisit power system dispatch: Concepts, models, and solutions

Yang

Yong

Xiang

2023

iEnergy

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Power system dispatch is a general concept with a wide range of applications. It is a special category of optimization problems that determine the operation pattern of the power system, resulting in a huge influence on the power system security, efficiency, and economics. In this paper, the power system dispatch problem is revisited from the basis. This paper provides a categorization of the dispatch problem, especially with an emphasis on industrial applications. Then, this paper presents a detailed review of the dispatch models. The common formulations of the dispatch problem are provided. Finally, this paper discusses the solutions of the dispatch problem and lists the major challenges.

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Section: Proportion Of Electric Power (%)mentioning

confidence: 83%

Revisit power system dispatch: Concepts, models, and solutions

Yang

Yong

Xiang

2023

iEnergy

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“…Despite the fact that the security-constraint unit commitment problem (SCUCP) has received major attention in power systems and many studies have been conducted on it (e.g., [58,59]), limited studies have addressed it in the presence of CHP units [60,61].…”

Section: Security Constraintsmentioning

confidence: 99%

A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions

Abdi

2023

Mathematics

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Combined generation units of heat and power, known as CHP units, are one of the most prominent applications of distributed generations in modern power systems. This concept refers to the simultaneous operation of two or more forms of energy from a simple primary source. Due to the numerous environmental, economic, and technical advantages, the use of this technology in modern power systems is highly emphasized. As a result, various issues of interest in the control, operation, and planning of power networks have experienced significant changes and faced important challenges. In this way, the unit commitment problem (UCP) as one of the fundamental studies in the operation of integrated power, and heat systems have experienced some major conceptual and methodological changes. This work, as a complementary review, details the CHP-based UCP (CHPbUCP) in terms of objective functions, constraints, simulation tools, and applied hardwares. Furthermore, some useful data on case studies are provided for researchers and operators. Finally, the work addresses some challenges and opens new perspectives for future research.

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“…For instance, the Midcontinent Independent System Operator (MISO) oversees one of the world's largest electricity markets, encompassing over 45,000 buses and 1400 generation resources. Its OPF model encompasses extensive resource-level constraints and system-wide constraints [4]. To simplify the large-scale OPF, MISO has implemented Lagrangian Relaxation (LR), decomposing the problem into smaller subproblems to enhance efficiency [5,6].…”

Section: Introductionmentioning

confidence: 99%

Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review

Jiang,

Wang,

et al. 2024

Energies

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Optimal power flow (OPF) is a crucial tool in the operation and planning of modern power systems. However, as power system optimization shifts towards larger-scale frameworks, and with the growing integration of distributed generations, the computational time and memory requirements of solving the alternating current (AC) OPF problems can increase exponentially with system size, posing computational challenges. In recent years, machine learning (ML) has demonstrated notable advantages in efficient computation and has been extensively applied to tackle OPF challenges. This paper presents five commonly employed OPF transformation techniques that leverage ML, offering a critical overview of the latest applications of advanced ML in solving OPF problems. The future directions in the application of machine learning to AC OPF are also discussed.

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Security-Constrained Unit Commitment for Electricity Market: Modeling, Solution Methods, and Future Challenges

Cited by 26 publications

References 156 publications

Revisit power system dispatch: Concepts, models, and solutions

Revisit power system dispatch: Concepts, models, and solutions

A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions

Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review

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