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.

Commercial buildings consume more than 40% of the total energy consumption in the United States. Almost 90% of these buildings are small- and medium-sized buildings that do not have a Building Energy Management (BEM) system. The reasons behind this are – lack of awareness, unavailability of inexpensive packaged solutions, and disincentive to invest in a BEM system if the tenant is not the owner. Several open source tools and technologies have emerged recently that can be used for building automation and energy management. However, none of these systems is turnkey and deployment ready. They also lack consistent and intuitive navigation, security, and performance required for a BEM system. The overall project - of which this thesis research is a part - addresses the design and implementation of an open source secure web based user platform to monitor, schedule, control, and perform functions needed for a BEM system serving small and medium-size buildings. The focus of this work are: principles of intuitive graphical user interface design, abstracting device functions into a comprehensive data model, identifying threats and vulnerabilities, and implementing a security framework for the web platform. Monitor and control solutions for devices such as load controllers and sensors are abstracted and their decentralized control strategies are proposed and implemented using an open source robust scalable user platform accessible locally and remotely. The user platform is open-source, scalable, provides role-based access, dynamic, and modular in design. The comprehensive data model includes a user management model, device model, session model, and a scheduling model. The data model is designed to be flexible, robust and can be extended for any new device type. Security risks are analyzed using a threat model to identify security goals. The proposed security framework includes user authentication, device approval, role-based access, secure information exchange protocols, and web platform security. Performance of the user interface platform is evaluated for responsiveness in different screen sizes, page response times, throughput, and the performance of client side entities. / Master of Science

In the United States, over 40% of the country's total energy consumption is in buildings, most of which are either small-sized (<5,000 sqft) or medium-sized (5,000-50,000 sqft). These buildings offer excellent opportunities for energy saving and demand response (DR), but these opportunities are rarely utilized due to lack of effective building energy management systems and automated algorithms that can assist a building to participate in a DR program. Considering the low load factor in US and many other countries, DR can serve as an effective tool to reduce peak demand through demand-side load curtailment. A convenient option for the customer to benefit from a DR program is to use automated DR algorithms within a software that can learn user comfort preferences for the building loads and make automated load curtailment decisions without affecting customer comfort. The objective of this dissertation is to provide such a solution. First, this dissertation contributes to the development of key features of a building energy management open source software platform that enable ease-of-use through plug and play and interoperability of devices in a building, cost-effectiveness through deployment in a low-cost computer, and DR through communication infrastructure between building and utility and among multiple buildings, while ensuring security of the platform. Second, a set of reinforcement learning (RL) based algorithms is proposed for the three main types of loads in a building: heating, ventilation and air conditioning (HVAC) loads, lighting loads and plug loads. In absence of a DR program, these distributed agent-based learning algorithms are designed to learn the user comfort ranges through explorative interaction with the environment and accumulating user feedback, and then operate through policies that favor maximum user benefit in terms of saving energy while ensuring comfort. Third, two sets of DR algorithms are proposed for an incentive-based DR program in a building. A user-defined priority based DR algorithm with smart thermostat control and utilization of distributed energy resources (DER) is proposed for residential buildings. For commercial buildings, a learning-based algorithm is proposed that utilizes the learning from the RL algorithms to use a pre-cooling/pre-heating based load reduction method for HVAC loads and a mixed integer linear programming (MILP) based optimization method for other loads to dynamically maintain total building demand below a demand limit set by the utility during a DR event, while minimizing total user discomfort. A user defined priority based DR algorithm is also proposed for multiple buildings in a community so that they can participate in realizing combined DR objectives. The software solution proposed in this dissertation is expected to encourage increased participation of smaller and medium-sized buildings in demand response and energy saving activities. This will help in alleviating power system stress conditions by employing the untapped DR potential in such buildings. / Ph. D.

Being located in subtropical area, the weather in Taiwan is constantly hot and humid which imposes huge cooling load on buildings. Especially, the economic booms in Taiwan further boosted power demand, and worsened the power shortage situation. Dr. H.T. Lin and Dr. K.H. Yang had conducted systematic research since mid-1980s, which constructed a solid ground in this field in Taiwan. Among these results, the ENVLOAD index has become legal binding since 1997 while the PACS index is now under investigation. However, it is in short of analysis and full-scale experimental investigation on energy use of hotels in Taiwan. Therefore, the establishment of the EUI and DUI indexes in Taiwan is the goal of this study. A simplified calculation method has been established in analyzing the energy use and demand use of hotels in Taiwan, by normalizing experimental data from full-scale tests. The result can be drawn accurately based on a few terms, which are available from daily building operations such as occupancy, and is thus practically straightforward and easy to use. In addition, the accuracy was validated by experiments performed and data collected through information technology with Internet access in 4 different forms, which yielded successful results. It is anticipated that the calculation methodology developed in this study on EUI and DUI, and the experimental validation would provide a foundation for the establishment of hotel building energy codes in Taiwan in the future.

Le bâtiment est un noeud énergétique important et un support idéal pour développer etanalyser les effets d’un système de gestion optimisée d’énergie (SGEB) tant son impactpotentiel sur la demande énergétique globale est important. Cependant, pour que ces objectifssoient atteints, plusieurs verrous doivent être levés. Au-delà des problématiques liées àl’architecture de distribution, aux modèles (y compris ceux relatifs au comportement desusagers), aux outils de dimensionnement, à la formalisation des paramètres, contraintes etcritères, aux systèmes de production et aux modes de connexions au réseau de distribution, lesproblèmes liés à la mise en oeuvre d’un outil de gestion décentralisée et à sa validation sontcentraux centrale. Ces travaux s’inscrivent directement dans cette optique. Ils portent enparticulier sur l’élaboration de modèles énergétiques, de stratégies de gestion d’énergie dansune configuration multi-sources et multi-charges et surtout de mise en oeuvre de méthodes etd’outils de validation au travers de bancs tests variés où certains composants peuvent êtreréels.Ce travail analyse le gestionnaire énergétique « G-homeTech » comprenant plusieursfonctionnalités de gestion testées sur des bancs d’essai virtuels et hybrides qui permettent decombiner à la fois des composants matériels et logiciels dans les simulations. Cela a permisd'insérer des actionneurs communicants pour tester leur pertinence. Les validations menéesmontrent que le gestionnaire énergétique permet l'effacement de pointes de consommation etdes économies sur la facture énergétique globale tout en respectant les contraintes techniqueset réglementaires.Les évènements prédits ne sont pas toujours ceux qui se produisent. Nous avons alorssimulé de telles situations. La radiation solaire et la consommation totale des services noncontrôlables sont différentes de celles prédites. Cette différence a conduit à des dépassementsde puissance électrique souscrite qui a activé le mécanisme de gestion réactive du gestionnaireénergétique. Des ordres de délestage sont alors dynamiquement envoyés à certainséquipements. Ces ordres alimentent directement les modèles des équipements électriques.Selon les importances relatives données au coût et au confort, nous avons montré que legestionnaire énergétique permet de faire des économies substantielles en évitant lesconsommations durant les pics de prix et évitant les dépassements de souscription pareffacement, par modulation du fonctionnement des systèmes de chauffage et par décalage defonctionnement des services temporaires dans les périodes plus intéressante énergétiquement. / The building is an important energy node and an ideal support to develop and analyzethe effects of an Energy Management System (EMS). Because of its potential impact, such amanagement of global energy demand is important. However, to achieve these goals, severallocks must be removed. Beyond issues related to the distribution architecture, to models(including those relating to user behavior), sizing tools, the formalization of parameters,constraints and criteria, production systems and methods of connection to the grid, problemrelated to implementation of decentralized management tool and its validation are central. Mywork is part of this context. It focuses in particular on the development of energy models,strategies for energy management in a multi-source and multi-load configuration, andespecially, the implementation methods and the validation tools through various test bencheswhere some components are real.This paper analyzes the energy manager “G-homeTech” including several managementfeatures tested on virtual and hybrid test benches that combine both hardware and softwarecomponents in the simulations. This has put communicating actuators to test their relevance.The validations show that the energy manager allows the deletion of peak demand andsavings on the overall energy bill while respecting the technical and regulatory constraints.Predicted events are not always those that occur. We then simulated such situations.Solar radiation and the total consumption of uncontrollable services are different from thosepredicted. This difference has led to over-subscribed electric power which has enabled themanagement mechanism of reactive energy manager. Load shedding orders are thendynamically sent to certain equipement. These orders directly supply models of electricalequipment.According to the relative importance given to cost and comfort, we have shown that theenergy manager can make substantial savings avoiding consumption during price peaks andavoiding over-subscription by erasure, by modulation of heating system operation and byshefting the timed service operation in the most interesting periods in energy.