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Yuzhou Jiang Dissertation.pdf (4.37 MB)

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Analyses of Issues Emerging from the Current Electricity Market Design Using Mathematical Optimization

Jiang, Yuzhou
http://rave.ohiolink.edu/etdc/view?acc_num=osu1701268477476333

Abstract Details

2023, Doctor of Philosophy, Ohio State University, Industrial and Systems Engineering.
The design of electricity markets is a challenging task. On one hand, it is complicated by the different characteristics of each market design, an example of which is the classification of either a centrally committed market or a self-committed market. Under a centrally committed market, generators submit variable and fixed offers to a market operator (MO) and the market is cleared by minimizing the sum of both types of costs. Under a self-committed market, only variable offers are passed to the MO. On the other hand, it is involved with the dynamics of new technology integration, which includes the rapid development of energy storage and renewable energy. Since issues such as policy equality and market efficiency play a vital role in social welfare, they require thorough study from the research community continuously. This dissertation investigates three issues emerging from electricity market design by applying operations research techniques. The first topic is about the impact of having market operators dispatch energy storage. There is a debate on whether we should authorize market operators to make energy-storage-operations decisions. Some stakeholders argue that having market operators dispatch energy storage is akin to market operators owning and operating generation. As a result, the independence of a market operator may be compromised. It is important we clear up this misconception before appropriate treatment of energy storage can occur. To analyze the market clearing condition, we apply duality theory on a stylized optimalpower- flow problem. The second topic is about the comparison between two market designs, i.e., a centrally-committed model adopted in North America and a self-committed model employed by western Europe. The key difference is in the offer submitted by generating entities as well as how the MO utilizes these offers under the two market designs. Additionally, we allow for strategic behavior of market participant. We formulate the two designs as bi-level optimization problems and provide solution techniques for both. The two designs are evaluated based on offer behavior, system efficiency and participant profitability. The last topic is about the optimal scheduling strategy that provides supply-side flexibility to an electricity market, as well as the design of an incentive mechanism to induce this optimal scheduling. Flexibility is receiving substantially more interest due to its ability to maintain the balance of demand and supply during real-time. We consider a market model where generators have different operating costs if committed in advance and dispatched during real-time. We procure the optimal scheduling strategy, which is a curve that separates generators committed in advance and generators reserved during real-time. We also construct an incentive mechanism to induce truthful revelation and consistency between individual choice and socially optimal decision.
Ramteen Sioshansi (Advisor)
Energy; Operations Research

Recommended Citations

Citations

  • Jiang, Y. (2023). Analyses of Issues Emerging from the Current Electricity Market Design Using Mathematical Optimization [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1701268477476333

    APA Style (7th edition)

  • Jiang, Yuzhou. Analyses of Issues Emerging from the Current Electricity Market Design Using Mathematical Optimization. 2023. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1701268477476333.

    MLA Style (8th edition)

  • Jiang, Yuzhou. "Analyses of Issues Emerging from the Current Electricity Market Design Using Mathematical Optimization." Doctoral dissertation, Ohio State University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=osu1701268477476333

    Chicago Manual of Style (17th edition)

osu1701268477476333
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