The current state of Ontario???s electricity system and natural environment has prompted the provincial government to call for the province to adopt a ???culture of conservation.??? Answering this call will involve the promotion of a variety of solutions. Included in that will be the use of information and communication technology, which encompasses technologies such as home energy management system (HEMS). It is believed that the feedback and home automation features of the HEMS will enable its users to alter their electricity consumption behaviours, via net reductions and/or load shifting. This study has assessed the ability of HEMS to encourage reduction in total and on-peak electricity consumption while in a time-of-use pricing environment. Additional focus was on which consumers had the greatest success using the HEMS to adopt electricity conservation behaviours. Two hundred and sixteen participants of a Milton, Ontario HEMS pilot study were chosen to take part in this case study. These participants were divided into two equal groups: a sample group, those who received a HEMS, and a control group, those who did not receive a HEMS. Participants from both groups were asked to complete two surveys and allow their electricity consumption data to be analyzed. The initial survey was to establish some baseline information about the participants. The second survey was designed to determine if changes had occurred in the household since the initial baseline survey. Through the analysis of the survey and households electricity consumption data, conclusions were drawn on how participants used the HEMS. The study had a 2.9% relative reduction in total electricity consumption and a 13.2% relative reduction in on-peak electricity consumption. However, additional analysis of the results revealed promising findings with regard to the HEMS ability to catalyze conservation and demand management among recent time-of-use pricing adopters.

The current state of Ontario’s electricity system and natural environment has prompted the provincial government to call for the province to adopt a ‘culture of conservation.’ Answering this call will involve the promotion of a variety of solutions. Included in that will be the use of information and communication technology, which encompasses technologies such as home energy management system (HEMS). It is believed that the feedback and home automation features of the HEMS will enable its users to alter their electricity consumption behaviours, via net reductions and/or load shifting. This study has assessed the ability of HEMS to encourage reduction in total and on-peak electricity consumption while in a time-of-use pricing environment. Additional focus was on which consumers had the greatest success using the HEMS to adopt electricity conservation behaviours. Two hundred and sixteen participants of a Milton, Ontario HEMS pilot study were chosen to take part in this case study. These participants were divided into two equal groups: a sample group, those who received a HEMS, and a control group, those who did not receive a HEMS. Participants from both groups were asked to complete two surveys and allow their electricity consumption data to be analyzed. The initial survey was to establish some baseline information about the participants. The second survey was designed to determine if changes had occurred in the household since the initial baseline survey. Through the analysis of the survey and households electricity consumption data, conclusions were drawn on how participants used the HEMS. The study had a 2.9% relative reduction in total electricity consumption and a 13.2% relative reduction in on-peak electricity consumption. However, additional analysis of the results revealed promising findings with regard to the HEMS ability to catalyze conservation and demand management among recent time-of-use pricing adopters.

The objective of this work is to design and implement an architectural framework for a web-based demand management system that allows an electric utility to reduce system peak load by automatically managing end-use appliances based on homeowners' preferences. The proposed framework comprises the following components: human user interface, home energy management (HEM) algorithms, web services for demand response communications, selected ZigBee and smart energy profile features for appliance interface, and security aspects for a web-based HEM system. The proposed web-based HEM system allows homeowners to be more aware about their electricity consumption by allowing visualization of their real-time and historical electricity consumption data. The HEM system enables customers to monitor and control their household appliances from anywhere with an Internet connection. It offers a user-friendly and attractive display panel for a homeowner to easily set his/her preferences and comfort settings. An algorithm to autonomously control appliance operation is incorporated in the proposed web-based HEM system, which makes it possible for residential customers to participate in demand response programs. In this work, the algorithm is demonstrated to manage power-intensive appliances in a single home, keeping the total household load within a certain limit while satisfying preset comfort settings and user preferences. Furthermore, an extended version of the algorithm is demonstrated to manage power-intensive appliances for multiple homes within a neighborhood. As one of the demand response (DR)-enabling technologies, the web services-based DR communication has been developed to enable households without smart meters or advanced metering infrastructure (AMI) to participate in a DR event via the HEM system. This implies that an electric utility can send a DR signal via a web services-enabled HEM system, and appropriate appliances can be controlled within each home based on homeowner preferences. The interoperability with other systems, such as utility systems, third-party Home Area Network (HAN) systems, etc., is also taken into account in the design of the proposed web services-based HEM system. That is, it is designed to allow interaction with authorized third-party systems by means of web services, which are collectively an interface for machine-to-machine interaction. This work also designs and implements device organization and interface for end-use appliances utilizing ZigBee Device Profile and Smart Energy Profile. Development of the Home Area Network (HAN) of appliances and the HAN Coordinator has been performed using a ZigBee network. Analyses of security risks for a web-based HEM system and their mitigation strategies have been discussed as well. / Master of Science

The efficiency, security and resiliency are very important factors for the operation of a distribution power system. Taking into account customer demand and energy resource constraints, electric utilities not only need to provide reliable services but also need to operate a power grid as efficiently as possible. The objective of this dissertation is to design, develop and deploy the Multi-Agent Systems (MAS) - together with control algorithms - that enable demand response (DR) implementation at the customer level, focusing on both residential and commercial customers. For residential applications, the main objective is to propose an approach for a smart distribution transformer management. The DR objective at a distribution transformer is to ensure that the instantaneous power demand at a distribution transformer is kept below a certain demand limit while impacts of demand restrike are minimized. The DR objectives at residential homes are to secure critical loads, mitigate occupant comfort violation, and minimize appliance run-time after a DR event. For commercial applications, the goal is to propose a MAS architecture and platform that help facilitate the implementation of a Critical Peak Pricing (CPP) program. Main objectives of the proposed DR algorithm are to minimize power demand and energy consumption during a period that a CPP event is called out, to minimize occupant comfort violation, to minimize impacts of demand restrike after a CPP event, as well as to control the device operation to avoid restrikes. Overall, this study provides an insight into the design and implementation of MAS, together with associated control algorithms for DR implementation in smart buildings. The proposed approaches can serve as alternative solutions to the current practices of electric utilities to engage end-use customers to participate in DR programs where occupancy level, tenant comfort condition and preference, as well as controllable devices and sensors are taken into account in both simulated and real-world environments. Research findings show that the proposed DR algorithms can perform effectively and efficiently during a DR event in residential homes and during the CPP event in commercial buildings. / Ph. D.

The global energy demand in residential sector is increasing steadily every year due to advancement in technologies. The present electricity grid is designed to support peak demand rather than Peak to Average (PAR) demand. Utilities are investigating the residential Demand Response (DR) to lower the (PAR) ratio and eliminate the need of building new power infrastructure. This requires Home Energy Management System (HEMS) at grid edge to manage and control the energy demand. In this thesis, we presented an MDPSO based DR enabled HEMS model for optimal allocation of energy resources in a smart dwelling. The algorithm is designed to lower peak energy demand as well as encourage the active participation of customers by offering a reward to comply with DR request. We categorized appliances as elastic non-deferrable loads and inelastic deferrable loads based on their DR potential and operating characteristics. The scheduling of elastic and inelastic class of appliances is performed separately using canonical and binary version of PSO given how we expressed out load categories. We performed use case simulation to validate the performance of MDPSO for combination of different tariffs: Time of Use (TOU), TOU and Critical peak rebate signal (CPR), TOU and upper demand limit. Simulation results show that algorithm can reduce the electricity cost in range of 28% to 7% under increasing comfort conditions in response to TOU prices and Peak demand reduction of about 24% under TOU pricing and medium comfort conditions for single household. Under CPR DR requests, with respect to TOU pricing, there is effectively no change in the peak under the minimum comfort scenario. Furthermore, algorithm is able to suppress the peak upto 25% under combination of TOU and hard constraint on maximum power withdrawn from grid with no change in the electricity cost. Scheduling of multiple houses under TOU pricing results in peak reduction of 7 % as compared to baseline state. Under combination of TOU and CPR the aggregate peak energy demand of multiple households during DR activation time intervals is reduced by 32 %. The algorithm can suppress the peak demand by 27% under TOU and hard constraint on maximum power withdrawn from grid by multiple houses.

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.

Denna studie undersöker hur ett smart energihanteringssystem påverkar användarbeteende och vanor hos användaren när det kommer till energianvändning. Med dagens fokus på energi och dess viktighet i samhället utvecklas tjänster som tillåter individen att övervaka sin energiförbrukning. Exempel på sådana tjänster är E.ON Elna™ och Tibber, där användaren kan se och övervaka sin energiförbrukning i hemmet i realtid. Tidigare forskning inom användarbeteende i relation till energianvändning visar att medvetenhet, feedback och egenkontroll är viktiga faktorer för ett förändrat användarbeteende. För att besvara studiens frågeställning genomfördes ett samarbete med E.ON och deras tjänst Elna™ där intervjuer utfördes med användare av Elna™-tjänsten samt icke-användare.  Studiens resultat visade att användningen av ett smart energihanteringssystem har medfört en positiv påverkan på användarens användarbeteende och medvetenhet kring deras energiförbrukning. Vidare visade resultaten från intervjuerna med respondenterna att ett smart energihanteringssystem har potentialen att främja energieffektivt beteende och öka användarnas medvetenhet om elförbrukning. / This study examines how smart energy management systems influence user behavior and habits of the user when it comes to energy use. With today's focus on energy and its importance in society, services are being developed that allow the individual to monitor their energy consumption. Examples of such services are E.ON Elna™ and Tibber, where the user can see and monitor their energy consumption in the home in real time. Previous research in user behavior in relation to energy use shows that awareness, feedback and self-control are important factors for a change in user behavior. To answer the study's question, a collaboration was carried out with E.ON and their service Elna™ where interviews were conducted with users of the Elna™ service and non-users. The results of the study showed that the use of a smart energy management system has had a positive impact on the user's user behavior and awareness of their energy consumption. Furthermore, the results from the interviews with the respondents showed that a smart energy management system has the potential to promote energy efficient behavior and increase users' awareness of electricity consumption.

Abstract Achieving the objective of a decarbonised economy by 2050 will require massive efforts in the energy sector. Emissions from residential houses will have to be almost completely cut, by around 90% by 2050. Home automation is a potential tool for achieving this goal. However, the environmental and economic benefits of automation technologies first need to be assessed. This thesis evaluates the impact of home automation for electricity management in the residential sector using environmental and economic indicators. To this end, a life cycle assessment was performed to evaluate the impacts of the manufacturing, use and disposal phases. The influences of end-user behaviour, household size and multiple levels of technological deployment were also investigated. A Markov chain simulation tool, built on the MatLab platform, was developed to assess all possible combinations of impacting factors. Dynamic environmental indicators were developed based on the ReCiPe method for aggregating the impacts of processes. All these indicators were then combined to form a single index based on multi-criteria acceptability analysis. The results suggest that home automation can decrease peak load, but that overall electricity consumption may increase due to electricity use by the actual automation system. The effect of home automation was more noticeable in larger households than in one-person households. In addition, use of dynamic environmental indicators proved more relevant than fixed indicators to represent the environmental impact of home automation. Within the life cycle of automation technology, the manufacturing phase had the highest impact, but most of the CO2 emissions originated from the use phase. In conclusion, the most important environmental benefit of home automation is reducing CO2 emissions during peak time by load shifting. / Tiivistelmä Vähähiilisen talouden saavuttaminen vuoteen 2050 mennessä edellyttää valtavia ponnisteluja energia-alalla. Rakennuksista aiheutuvia päästöjä on vähennettävä radikaalisti, jopa 90 % vuoteen 2050 mennessä. Rakennusten energiatehokkuutta edistävä automaatiotekniikka on yksi keino tämän päämäärän saavuttamiseen. Kotiautomaation kautta voidaan sekä vähentää energian kokonaiskulutusta että tasoittaa energiankäyttöprofiilia. On kuitenkin tutkittava myös, mitkä ovat automaatiotekniikan ympäristö- ja taloudelliset vaikutukset. Tässä työssä käsitellään kotiautomaation vaikutusta sähkön kulutuksen hallintaan asuinrakennuksissa käyttämällä ympäristö- ja talousindikaattoreita. Tätä varten suoritettiin kotiautomaation elinkaariarviointi selvittämällä laitteiden valmistus-, käyttö- ja hävittämisvaiheiden ympäristövaikutukset. Työssä tarkasteltiin myös asukkaiden käyttäytymisen, kotitalouden koon ja eri teknologiavaihtoehtojen vaikutuksia ympäristö- ja talousvaikutuksiin. Arviointi suoritettiin Markovin ketjun simulointityökalulla, joka rakennettiin Matlab-alustalle. Dynaamisia ympäristömittareita kehitettiin ReCiPe-menetelmää käyttäen. Indikaattorit on edelleen yhdistetty yhdeksi indeksiksi käyttäen monikriteeriarviointia. Tulokset viittaavat siihen, että huippukuormitusta voidaan vähentää käyttämällä kotiautomaatiota, mutta sähkön kokonaiskulutus voi kasvaa automaatiojärjestelmän sähkönkulutuksen takia. Kotiautomaation vaikutukset ovat eniten havaittavissa suurissa kotitalouksissa. Lisäksi, dynaamiset indikaattorit edustavat paremmin kotiautomaation vaikutusta ympäristöön kuin staattiset indikaattorit. Automaatioteknologian elinkaaressa suurimmat ympäristövaikutukset ovat valmistusvaiheessa, mutta CO2-päästöjä syntyy eniten käyttövaiheessa. Lopuksi voidaan todeta, että kotiautomaation merkittävin ympäristöhyöty on CO2-päästöjen vähentäminen huippukulutuksen aikana siirtämällä kuormitusta toiseen ajankohtaan.