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- Genre: Academic theses
Description
Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling of operating reserves in the existing deterministic reserve requirements acquire the operating reserves on a zonal basis and do not fully capture the impact of congestion. The purpose of a reserve zone is to ensure that operating reserves are spread across the network. Operating reserves are shared inside each reserve zone, but intra-zonal congestion may block the deliverability of operating reserves within a zone. Thus, improving reserve policies such as reserve zones may improve the location and deliverability of reserve.
As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired.
One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones.
Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies.
As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired.
One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones.
Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies.
ContributorsWang, Fengyu (Author) / Hedman, Kory W. (Thesis advisor) / Zhang, Muhong (Committee member) / Tylavsky, Daniel J. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this dissertation, a distribution system operator (DSO) framework is proposed to optimally coordinate distributed energy resources (DER) aggregators' comprehensive participation in the retail energy market as well as wholesale energy and regulation markets. Various types of DER aggregators, including energy storage aggregators (ESAGs), dispatchable distributed generation aggregators (DDGAGs), electric vehicles charging stations (EVCSs), and demand response aggregators (DRAGs), are modeled in the proposed DSO framework. An important characteristic of a DSO is being capable of handling uncertainties in the system operation. An appropriate method for a market operator to cover uncertainties is using two-stage stochastic programming. To handle comprehensive retail and wholesale markets participation of distributed energy resource (DER) aggregators under uncertainty, a two-stage stochastic programming model for the DSO is proposed. To handle unbalanced distribution grids with single-phase aggregators, A DSO framework is proposed for unbalanced distribution networks based on a linearized unbalanced power flow which coordinates with wholesale market clearing process and ensures the DSO's non-profit characteristic.
When proposing a DSO, coordination with the ISO is important. A framework is proposed to coordinate the operation of the independent system operator (ISO) and distribution system operator (DSO). The framework is compatible with current practice of the U.S. wholesale market to enable massive distributed energy resources (DERs) to participate in the wholesale market. The DSO builds a bid-in cost function to be submitted to the ISO market through parametric programming. A pricing problem for the DSO is proposed. In pricing problem, after ISO clears the wholesale market, the locational marginal price (LMP) of the ISO-DSO coupling substation is determined, the DSO utilizes this price to solve the DSO pricing problem. The DSO pricing problem determines the distribution LMP (D-LMP) in the distribution system and calculates the payment to each aggregator. An efficient algorithm is proposed to solve the ISO-DSO coordination parametric programming problem. Notably, our proposed algorithm significantly improves the computational efficiency of solving the parametric programming DSO problem which is computationally intensive.
Various case studies are performed to analyze the market outcome of the proposed DSO framework and coordination with the ISO.
ContributorsMousavi, Mohammad (Author) / Wu, Meng (Thesis advisor) / Khorsand, Mojdeh (Committee member) / Byeon, Geunyeong (Committee member) / Nguyen, Duong (Committee member) / Arizona State University (Publisher)
Created2023