In April 2016 Manchester eScholar was replaced by the University of Manchester’s new Research Information Management System, Pure. In the autumn the University’s research outputs will be available to search and browse via a new Research Portal. Until then the University’s full publication record can be accessed via a temporary portal and the old eScholar content is available to search and browse via this archive.

Optimal Demand Response from Home Energy Management System: Modeling and Benefits for Distribution Networks

Althaher, Sereen

[Thesis]. Manchester, UK: The University of Manchester; 2015.

Access to files

Abstract

The increasing levels of renewable generation and the electrification of transport and heating as parts of the movement towards low-carbon energy systems to cope with climate change will place significant challenges on the electricity system to facilitate the way towards future low carbon energy systems in a cost effective way and ensure secure power delivery. New solutions and higher levels of flexibility are required than currently exist in order to reduce the integration costs of low carbon generation and demand technologies. Price-based demand response in residential sector is considered as one of these potential solutions. However, a certain level of automation is required to reduce both the uncertainty in the consumer response and the complexity for consumers to react to the price signal. This thesis presents a comprehensive and general residential optimization-based Automated Demand Response (ADR). The modelling of home appliances has been extensively developed to include all the classifications proposed in the literature, namely, deferrable and thermal in addition to new groups of critical and fully curtailable loads. The operations of the appliances are controlled in response to dynamic price signals to reduce the consumer’s electricity bill whilst minimizing the daily volume of curtailed energy and therefore considering the user’s comfort level. To avoid shifting most portion of consumer demand towards the least price intervals, which could create network issues due to loss of diversity, higher prices are applied when the consumer’s demand goes beyond a power threshold level. The arising mixed integer nonlinear optimization problem is solved in an iterative manner rolling throughout the day to follow the changes in the anticipated price signals and the variations in the controller inputs while information is updated. The results from different case studies show the effectiveness of the proposed controller to minimize the household’s daily electricity bill while preserving comfort level as well as preventing creation of new least-price peaks.This thesis also proposes a two-stage distribution-planning framework to assess the benefits of the proposed ADR models in response to a location-specific time of use Distribution Use of Systems Charge (DUoSC) on the required investments to connect future low-carbon technologies. The network investments and the satisfaction of consumers in terms of energy curtailment are both quantified. The first stage aims to generate location-specific time of use price signals for all users in the network, which represents their contributions in future network investments due to congestion and security constraints. The second stage relates to a group of ADR controllers at residential premises that aims to minimise the daily energy payment whilst maximising consumer comfort in response to the corresponding price signal produced from the first stage.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Electrical and Electronic Engineering
Publication date:
Location:
Manchester, UK
Total pages:
195
Abstract:
The increasing levels of renewable generation and the electrification of transport and heating as parts of the movement towards low-carbon energy systems to cope with climate change will place significant challenges on the electricity system to facilitate the way towards future low carbon energy systems in a cost effective way and ensure secure power delivery. New solutions and higher levels of flexibility are required than currently exist in order to reduce the integration costs of low carbon generation and demand technologies. Price-based demand response in residential sector is considered as one of these potential solutions. However, a certain level of automation is required to reduce both the uncertainty in the consumer response and the complexity for consumers to react to the price signal. This thesis presents a comprehensive and general residential optimization-based Automated Demand Response (ADR). The modelling of home appliances has been extensively developed to include all the classifications proposed in the literature, namely, deferrable and thermal in addition to new groups of critical and fully curtailable loads. The operations of the appliances are controlled in response to dynamic price signals to reduce the consumer’s electricity bill whilst minimizing the daily volume of curtailed energy and therefore considering the user’s comfort level. To avoid shifting most portion of consumer demand towards the least price intervals, which could create network issues due to loss of diversity, higher prices are applied when the consumer’s demand goes beyond a power threshold level. The arising mixed integer nonlinear optimization problem is solved in an iterative manner rolling throughout the day to follow the changes in the anticipated price signals and the variations in the controller inputs while information is updated. The results from different case studies show the effectiveness of the proposed controller to minimize the household’s daily electricity bill while preserving comfort level as well as preventing creation of new least-price peaks.This thesis also proposes a two-stage distribution-planning framework to assess the benefits of the proposed ADR models in response to a location-specific time of use Distribution Use of Systems Charge (DUoSC) on the required investments to connect future low-carbon technologies. The network investments and the satisfaction of consumers in terms of energy curtailment are both quantified. The first stage aims to generate location-specific time of use price signals for all users in the network, which represents their contributions in future network investments due to congestion and security constraints. The second stage relates to a group of ADR controllers at residential premises that aims to minimise the daily energy payment whilst maximising consumer comfort in response to the corresponding price signal produced from the first stage.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:263927
Created by:
Althaher, Sereen
Created:
6th May, 2015, 12:43:40
Last modified by:
Althaher, Sereen
Last modified:
16th November, 2017, 14:24:47

Can we help?

The library chat service will be available from 11am-3pm Monday to Friday (excluding Bank Holidays). You can also email your enquiry to us.