Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


Thesis.pdf (1.5 MB)

ETD Abstract Container

Abstract Header

Prices in Wholesale Electricity Markets and Demand Response

Aketi, Venkata Sesha Praneeth
http://rave.ohiolink.edu/etdc/view?acc_num=osu1388765872

Abstract Details

2014, Doctor of Philosophy, Ohio State University, Industrial and Systems Engineering.
Price determination for a wholesale electricity market has been a long-standing issue in energy systems modeling. From an economic perspective, the complication arises from determining prices that achieve market equilibrium while supporting the quantities in an economic dispatch. From a modeling point of view, the complexity stems from the indivisibilities of the mixed integer mathematical programming models which lead to duality gaps and non-unique dual prices. While the determination of a supporting price that results in no losses for the suppliers poses challenges on one hand, there is also the regulatory issue of trying to achieve more uniform distribution of nodal wholesale prices, i.e., the Locational Marginal Prices (LMPs). With the advent of smart-grids, dynamic retail pricing structures and technologies such as advanced metering infrastructure (AMI) and smart-meters, there is a need to model and regulate the demand response to ensure that the redistribution of demand indeed reduces the peaking of LMPs and the associated high costs. This dissertation addresses the above issues and presents models and methods for wholesale electricity price determination and regulation. The first part of the dissertation is a case study for the state of Ohio that illustrates and analyzes the aforementioned issues from a consumer demand response perspective. From a research point of view, a modeling and simulation study is presented that analyzes the economic impact of introducing advanced metering and its smarter versions. Advanced metering refers to a set of technologies that enables promoting demand response through two-way communications between utilities and consumers, and controlling energy usage via smart meters. A framework is developed to model the integration of such smart-meters with basic AMI in the presence of dynamic pricing structures. The novelty of the approach is in modeling the integration using a linear programming model to capture the online negotiations between the consumers and utilities under various operating constraints and bounds. Such a modeling framework drives the automation of demand response, reduces its uncertainty, and enables the achievement of the goal of reducing peak LMPs. The use of linear programming provides for easy scaling of the analysis. The framework is used to present the results of a fairly comprehensive case study for the state of Ohio, for 2015, that quantifies the benefit metrics associated with consumers and utilities, and analyzes the trends in their behavior to enable extrapolation. The second part of the dissertation focuses on both optimization and economic aspects of determining prices that support the wholesale electricity market. Mathematical models for electricity pricing (e.g. unit commitment models) are complicated by a variety of factors. In particular, the mixed-binary nature of the models is characterized by the absence of standard linear programming type duality presenting a major hurdle for pricing. At least two approaches exist in literature that try to address this - while one promotes economic efficiency and market equilibrium at the cost of introducing high uplift payments, the other is motivated by the need to reduce uplift payments which in turn creates loss in economic efficiency. A zero-uplift pricing strategy, termed as the left-hand-side-convex-hull (LHS-CH) pricing and based on a novel non-convex dual formulation, is presented in this dissertation. The economic justification for the LHS-CH pricing approach is shown to come from its close ties to marginal as well as average cost pricing. From an optimization perspective, it is shown that the prices result from a non-convex Lagrangian-type dual problem whose properties (e.g. zero duality gap) provide a strong theoretical support. A comparison is made with the existing pricing strategies, and the dominance of the proposed pricing is shown using a fixed-charge model analogy and a couple of standard examples from the literature. Computational methods and generalizations have been presented for unit commitment problems ranging from single period to multiple time periods with different types of constraints. The modeling is specific to the electricity market models, but the scope of the pricing, methodologies and algorithms extend beyond the application. They are applicable to a variety of problems that involve resource and cost allocation or cost recovery like pricing for toll road problems etc.
Suvrajeet Sen (Advisor)
Simge Kucukyavuz (Committee Chair)
Theodore Allen (Committee Member)
120 p.
Industrial Engineering; Operations Research
Electricity Pricing; Uplifts; Non Convexity; Mixed Binary Linear Programs; Duality; Demand Response; Advanced Metering Infrastructure; Smart Meters

Recommended Citations

Citations

  • Aketi, V. S. P. (2014). Prices in Wholesale Electricity Markets and Demand Response [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388765872

    APA Style (7th edition)

  • Aketi, Venkata Sesha Praneeth. Prices in Wholesale Electricity Markets and Demand Response. 2014. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1388765872.

    MLA Style (8th edition)

  • Aketi, Venkata Sesha Praneeth. "Prices in Wholesale Electricity Markets and Demand Response." Doctoral dissertation, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388765872

    Chicago Manual of Style (17th edition)

osu1388765872
1,229
© 2014, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.