PhD Seminar: Demand Response and Battery Energy Storage Systems in Electricity Markets: Frameworks & Models

Wednesday, July 17, 2019 2:30 pm - 2:30 pm EDT (GMT -04:00)

Candidate: Nitin Padmanabhan

Title: Demand Response and Battery Energy Storage Systems in Electricity Markets: Frameworks & Models

Date: July 17, 2019

Time: 2:30 PM

Place: EIT 3141

Supervisor(s): Bhattacharya, Kankar - Ahmed, Mohamed H. (Adjunct)

Abstract:

Ensuring a balance between the generation and demand is one of the most challenging tasks in power systems because of contingencies, sudden load changes, forecasting errors and other disturbances, occurring from time to time. The peak demand, which occurs only for a short duration, has always been a concern for independent system operators (ISOs), as it leads to high market prices and reliability concerns. Furthermore, in recent years there have been significant increase in the penetration of renewable energy resources (RES) to address the challenge of significantly reducing carbon dioxide (CO2) and other greenhouse gas (GHG) emissions and the system's dependence on fossil fuels based generation resources. However, the high penetration of RES, because of their intermittency and uncertainty, poses operational and reliability issues and thus necessitates an increase in the procurement and deployment of primary and secondary regulation reserves, as well as spinning and non-spinning reserves.

In the recent years, demand response (DR) and battery energy storage systems (BESS), because of their characteristic features such as fast response time, high ramp rate, and the ability to provide  flexible upward and downward response as compared to conventional generators, have been considered as promising and viable options by the ISO to reduce the peak demand, facilitate RES integration and for the provision of ancillary services, such as regulation and spinning reserves. 

Despite the benefits and the growth opportunities of DR and BESS, there are still many challenges associated with their market participation. To address the challenges pertaining to DR and BESS participation in electricity markets, this thesis proposes appropriate models and frameworks, which can efficiently integrate these resources into the day-ahead and real-time electricity markets, and at the same time effectively address the aforementioned challenges of ISOs.

This thesis first presents a new bid/offer structure for DR provisions, simultaneously through price responsive demand (PRD) based bids and load curtailment based DR offers from customers. Thereafter, incorporating the DR offer structure, a novel day-ahead, co-optimizing market auction framework and mathematical model for DR-energy-spinning reserve market, based on LMPs, which includes transmission loss representation within the dc power flow constraints is proposed. The impact of DR on both energy and spinning reserve market prices, market dispatch, line congestions, and other economic indicators, is studied using the IEEE Reliability Test System (RTS), by considering various scenarios and cases.

In the next stage, the thesis considers the BESS participation in the day-ahead markets. First, a novel BESS cost function model, considering Degradation Cost, based on depth of discharge (DOD) and discharge rate, and Flexibility Cost, in terms of the battery power-to-energy (P/E) ratio, is presented. A detailed bid/o er structure based on the proposed cost functions is formulated. Thereafter, a new framework and mathematical model for BESS participation in an LMP-based, co-optimized, day-ahead energy and spinning reserve market, have been developed. Three case studies are presented to investigate the impact of BESS participation on system operation and market settlement. The proposed model is validated on the IEEE RTS to demonstrate its functionalities.

Finally, the thesis considers BESS participation in the real-time operations. Firstly, a novel framework for simultaneously procuring primary and secondary regulation reserves alongside energy, in a BESS integrated electricity market, by taking into account probabilistic scenarios of contingencies, is proposed. Thereafter, an appropriate mathematical model is developed considering BESS alongside conventional generators to determine the optimal real-time primary and secondary regulation reserves and energy market clearing, in a co-optimized, LMP based market, taking into consideration the a priori cleared day-ahead market schedules. Lastly, the impact of participation of BESS in day-ahead and real-time energy and reserve markets on prices, market clearing dispatch, and other economic indicators are investigated using the IEEE RTS, for various scenarios and cases.