The Significance of Time Constraints in Unit Commitment Problems

被引:0
作者
Bukhsh, Waqquas [1 ]
机构
[1] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XW, Scotland
关键词
Generators; Renewable energy sources; Mathematical models; Costs; Biological system modeling; Electricity supply industry; Power markets; Linear programming; Optimization methods; Market research; Power system planning; Investment; Incentive schemes; Electricity markets; integer programming; optimization; unit commitment problem; merit order dispatch; linear programming; MERIT ORDER; OPTIMIZATION;
D O I
10.1109/ACCESS.2024.3369484
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electricity market clearing models are crucial for operational and investment planning in modern power systems. Two commonly used models for market clearing are the merit-order and unit commitment models. While the merit-order employs a snapshot approach and lacks precision in representing time-based variations in demand and generation, the unit commitment model incorporates crucial temporal constraints. This paper highlights the significance of temporal constraints in market clearing models, emphasizing the potential for significant errors in generation commitment if these constraints are not carefully considered. Using real data from the Irish electricity system, the impact of temporal constraints on intra-day market clearing is demonstrated, comparing with the merit-order rule with the unit commitment solution. The findings reveal 6% underestimation in market clearing prices when compared to unit commitment solutions. The minimum stable operating constraints of thermal units were identified as having the most substantial impact on the unit commitment solution. This study underscores the risk of significant errors in generation planning if temporal constraints are not adequately factored in, advocating for a more accurate approach for market clearing models.
引用
收藏
页码:31515 / 31522
页数:8
相关论文
共 29 条
[1]  
Agapoff S, 2015, 2015 IEEE EINDHOVEN POWERTECH
[2]  
Al-Sumaiti A. S., 2020, P IEEE INT C POW EL, P1
[3]  
Anjos M. F., 2017, Found. Trends Electr. Energy Syst., V1, P220
[4]  
[Anonymous], 2015, The Need for a Second North South Electricity Interconnector
[5]  
Baringa Partners LLP, 2016, Sem Plexos Model Validation
[6]   Turn Down for What? The Economic Value of Operational Flexibility in Electricity Markets [J].
Bistline, John E. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (01) :527-534
[7]  
Bukhsh W., 2019, Documentation of OATS
[8]   OATS: Optimisation and Analysis Toolbox for Power Systems [J].
Bukhsh, Waqquas ;
Edmunds, Calum ;
Bell, Keith .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (05) :3552-3561
[9]   Should unit commitment be endogenously included in wind power transmission planning optimisation models? [J].
Burke, Daniel J. ;
Tuohy, Aidan ;
Dillon, Jody ;
O'Malley, Mark J. .
IET RENEWABLE POWER GENERATION, 2014, 8 (02) :132-140
[10]   Pricing Multi-Interval Dispatch Under Uncertainty Part II: Generalization and Performance [J].
Chen, Cong ;
Guo, Ye ;
Tong, Lang .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36 (05) :3878-3886