Carbon-oriented generation planning: a market-driven approach
File(s)
Author(s)
Wang, Junkai
Type
Thesis or dissertation
Abstract
Under the circumstances of the urgent global challenges posed by climate change, decarbonisation has become a critical priority. In this context, the GB government has set ambitious goals to decarbonise its power sector by 2035, aligning with the net-zero target by 2050. This thesis examines generation planning under stringent carbon emission restrictions from four distinct aspects: the value of market structure, the role of demand flexibility, the impact of energy storage, and the feasibility of achieving a fully decarbonised GB power system by 2035.
To meet these objectives, the proposed bi-level models encompass an upper-level problem, representing the decision-making process of the self-interested generation company, alongside two lower-level problems: the first lower-level problem represents the joint clearing process of the day-ahead energy market and the real-time balancing market to co-optimise the generation scheduling and reserve deployment; the second lower-level problem represents the clearing process of the green certificate market. Notably, the proposed models incorporate demand and wind power uncertainty through a series of chance constraints. Furthermore, the time-coupling demand flexibility and energy storage models are also integrated into the bi-level models.
Numerous case studies have provided valuable insights on generation planning under current carbon targets using real-world data from the 2021 GB power system and predicted data from the 2035 GB power system. Overall, the scope of the case studies is three-fold. Firstly, they quantitatively compare the role of vertically integrated monopoly utilities and deregulated energy markets. Secondly, they explore how demand flexibility and energy storage benefit market-driven generation planning by mitigating massive renewable uncertainty. Finally, they demonstrate that the high levels of demand flexibility, in conjunction with utility-scale energy storage, not only ensure the stable operation of a 100% renewable GB power system but also guarantee adequate economic benefits.
To meet these objectives, the proposed bi-level models encompass an upper-level problem, representing the decision-making process of the self-interested generation company, alongside two lower-level problems: the first lower-level problem represents the joint clearing process of the day-ahead energy market and the real-time balancing market to co-optimise the generation scheduling and reserve deployment; the second lower-level problem represents the clearing process of the green certificate market. Notably, the proposed models incorporate demand and wind power uncertainty through a series of chance constraints. Furthermore, the time-coupling demand flexibility and energy storage models are also integrated into the bi-level models.
Numerous case studies have provided valuable insights on generation planning under current carbon targets using real-world data from the 2021 GB power system and predicted data from the 2035 GB power system. Overall, the scope of the case studies is three-fold. Firstly, they quantitatively compare the role of vertically integrated monopoly utilities and deregulated energy markets. Secondly, they explore how demand flexibility and energy storage benefit market-driven generation planning by mitigating massive renewable uncertainty. Finally, they demonstrate that the high levels of demand flexibility, in conjunction with utility-scale energy storage, not only ensure the stable operation of a 100% renewable GB power system but also guarantee adequate economic benefits.
Version
Open Access
Date Issued
2024-03-15
Date Awarded
2024-08-01
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Strbac, Goran
Publisher Department
Electrical and Electronic Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)