A framework for enabling the utilization of flexible loads to provide frequency regulation

Frequency regulation is becoming increasingly important with deeper penetration of variable generation resources. This dissertation is about exploiting the flexibility of distributed energy resources (DERs) to provide frequency regulation though the framework of an aggregator, which groups DERs into simple, yet accurate, models; offers capability based on these models; and coordinates the DERs to provide the service. Flexible loads have been proposed as a low-cost provider of frequency regulation. For example, the flexibility of loads with inherent thermal energy storage resides in their ability to vary their electricity consumption without compromising their end function. The aggregate flexibility of a collection of diverse residential air-conditioning loads has previously been shown to be well modeled as a virtual battery using first principles load models. In this dissertation, through developing control and parameter identification schemes, we show that the virtual battery can also model more complex loads such as buildings with large, multi-zone air conditioning systems. The small power ratings and capacity constraints of individual flexible loads is an obstacle to their integration. Thus, we additionally propose a framework wherein an aggregator coordinates the response of many flexible loads and other types of distributed energy resources (DERs) (e.g., plug-in electric vehicles and microturbines) connected to electric power distribution networks to provide frequency regulation services. In this framework, the aggregator participates in the day-ahead and real-time ancillary services markets by submitting an offer to provide frequency regulation. If the offer is accepted, the aggregator must coordinate the response of the DERs in order to provide the service. The DERs are compensated through bilateral contracts, the terms of which are negotiated in advance. The DER coordination problem the aggregator is faced with is cast as an optimal control problem, and we propose a bilayer framework to obtain a sub-optimal solution. In the first layer, we utilize model-predictive control techniques driven by regulation signal forecasts and parameter estimates to obtain a reference control action for the DERs. A second control layer provides closed-loop regulation around the reference computed by the top layer, which minimizes the error that arises due to forecast error, plant-model mismatch, and the slower speed of the optimal control.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2016

Author dc:creator

• Hughes, Justin Todd

Contributors dc:contributor

• Domínguez-García, Alejandro D.
• Overbye, Thomas J.
• Poolla, Kameshwar
• Sauer, Peter W.

• Power Systems
• Frequency Regulation
• Flexible Loads

Statement dc:rights

• Copyright 2016 Justin T. Hughes

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/90734

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/90734