Electrical power systems consist of a large number of power generators connected to consumers through a complex system of transmission and distribution lines. Within the electric grid, a continuous balance between generation and consumption of electricity must be maintained., ensuring stable operation of the grid. In recent decades due to increasing electricity demand, there is an increased likelihood of electrical power systems experiencing stress conditions. These conditions lead to a limited supply and cascading failures throughout the grid that could lead to wide area outages. Demand Response (DR) is a method involving the curtailment of loads during critical peak load hours, that restores that balance between demand and supply of electricity. In order to implement DR and ensure efficient energy operation of buildings, detailed energy monitoring is essential. This information can then be used for energy management, by monitoring the power consumption of devices and giving users detailed feedback at an individual device level. Based on the data from the Energy Information Administration (EIA), approximately half of all commercial buildings in the U.S. are 5,000 square feet or smaller in size, whereas the majority of the rest is made up of medium-sized commercial buildings ranging in size between 5,001 and 50,000 square feet. Given that these medium-size buildings account for a large portion of the total energy demand, these buildings are an ideal target for participating in DR. In this dissertation, two broad solutions for commercial building DR have been presented. The first is a load disaggregation technique to disaggregate the power of individual HVACs using machine learning classification techniques, where a single power meter is used to collect aggregated HVAC power data of a building. This method is then tested over a number of case studies, from which it is found that the aggregated power data can be disaggregated to accurately predict the power consumption and state of activity of individual HVAC loads. The second work focuses on a DR algorithm involving the determination of an optimal bid price for double auctioning between the user and the electric utility, in addition to a load scheduling algorithm that controls single floor HVAC and lighting loads in a commercial building, considering user preferences and load priorities. A number of case studies are carried out, from which it is observed that the algorithm can effectively control loads within a given demand limit, while efficiently maintaining user preferences for a number of different load configurations and scenarios. Therefore, the major contributions of this work include- A novel HVAC power disaggregation technique using machine learning methods, and also a DR algorithm for HVAC and lighting load control, incorporating user preferences and load priorities based on a double-auction approach. / Doctor of Philosophy / Electrical power systems consist of a large number of power generators connected to consumers through a complex system of transmission and distribution lines. Within the electric grid, a continuous balance between generation and consumption of electricity must be maintained., ensuring stable operation of the grid. When electricity demand is high, Demand Response (DR) is a method that can be used to reduce user loads, restoring the balance between demand and supply of electricity. Based on data from the Energy Information Administration (EIA), half of all commercial buildings in the US measure 5,000 square feet or smaller in size, whereas the majority of the other half is made up of medium-sized commercial buildings measuring in at between 5,001 to 50,000 square feet. This makes these commercial buildings an ideal target for participating in DR. In this dissertation, two broad solutions for commercial building DR have been presented. The first is a load disaggregation technique, where power consumption and activity of individual HVACs can be obtained, using a single power meter. The second work focuses on a DR algorithm, that controls single floor HVAC and lighting loads in a commercial building, based on a user generated bid price for electricity, user preferences and load priorities, when electricity demand is at its peak.

The demand for electricity of a particular location can vary significantly based on season, ambient temperature, time of the day etc. High demand can result in very high wholesale price of electricity. The reason for this is very short operating duration of peaking power plants which require large capital investments to establish. Those power plants remain idle for most of the time of a year except for some peak demand periods during hot summer days. This process is inherently inefficient but it is necessary to meet the uninterrupted power supply criterion. With the advantage of new technologies, demand response can be a preferable alternative, where peak reduction can be obtained during the short durations of peak demand by controlling loads. Some controllable loads are with thermal inertia and some loads are deferrable for a short duration without making any significant impact on users' lifestyle and comfort. Demand response can help to attain supply - demand balance without completely depending on expensive peaking power plants. In this research work, an incentive-based model is considered to determine the potential of peak demand reduction due to the participation of residential customers in a demand response program. Electric water heating and air-conditioning are two largest residential loads. In this work, hot water preheating and air-conditioning pre-cooling techniques are investigated with the help of developed mathematical models to find out demand response potentials of those loads. The developed water heater model is validated by comparing results of two test-case simulations with the expected outcomes. Additional energy loss possibility associated with water preheating is also investigated using the developed energy loss model. The preheating temperature set-point is mathematically determined to obtain maximum demand reduction by keeping thermal loss to a minimal level. Case studies are performed for 15 summer days to investigate the demand response potential of water preheating. Similarly, demand response potential associated with pre-cooling operation of air-conditioning is also investigated with the help of the developed mathematical model. The required temperature set-point modification is determined mathematically and validated with the help of known outdoor temperature profiles. Case studies are performed for 15 summer days to demonstrate effectiveness of this procedure. On the other hand, total load and demand response potential of a single house is usually too small to participate in an incentive-based demand response program. Thus, the scope of combining several houses together under a single platform is also investigated in this work. Monte Carlo procedure-based simulations are performed to get an insight about the best and the worst case demand response outcomes of a cluster of houses. In case of electrical water heater control, aggregate demand response potential of 25 houses is determined. Similarly, in case of air-conditioning control (pre-cooling), approximate values of maximum, minimum and mean demand reduction amounts are determined for a cluster of 25 houses. Expected increase in indoor temperature of a house is calculated. Afterwards, the air-conditioning demand scheduling algorithm is developed to keep aggregate air-conditioning power demand to a minimal level during a demand response event. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm. / Master of Science

[EN] The electric power industry is being shaken by a new idea that is taking shape: smart grids. Three aspects are considered keys to reach smart grids: a) The structure of the network must meet the smart grid concept, i.e. it must be resistant to failures, e.g. causing the automatic separation of any broken element without affecting the operation of the other components; it must be flexible to allow the connection or disconnection of loads and distributed generators, it must maintain efficient operation under various load conditions, and so on. b) The network should open the possibilities of participation of large and small generators as well as users, enabling new business opportunities and active participation, so that "intelligent" generation or consumption may benefit. c) All participants must have easy access to the information needed to choose the best operating strategy in each case. In regard to the first condition (a) there are significant challenges to solve: network automation, optimal design, development of new protection and control equipment, etc. It will be necessary to develop equipment adapted to new problems and new needs that will be generated in these networks. Those items of equipment should be standardised, it will be necessary to define tests to take into account issues that currently are not usually needed, such as the presence of disturbances in voltage, or others. In this sense, marginally though, the research team in which the author works has collaborated with a laboratory for electrical testing, the Flex Power Grid Lab Research Infrastructure DNV KEMA in the Netherlands, in the definition and implementation of some tests, as described in Chapter 3. Smart grids. In the second aspect (b), deep social changes are needed and, above all, regulation changes are crucial. In any case, the first step is to know how the consumption of loads is, how can demand be modified, how can small generation (mainly renewable) and energy storage influence generation, and so on. Having accurate models that provide this information is a key factor for network agents to establish their best strategies. This dissertation discusses many aspects of energy demand and the problem of controlling several resources and agents in the system operation is addressed and Chapter 3. Smart grids shows the management and control software (in which the author has collaborated during the design and development stages) of a small smart grid that exists in LabDER laboratory at UPV, where various resources are integrated according to the needs of demand, energy prices, and so on. In the third condition (c) there are also major challenges to be solved, such as mass information management and the increasing volume of data traffic that it can involve. This dissertation proposes several algorithms to facilitate treatment of the available data to optimise the management of the resources in a smart grid or to make decisions about the participation in demand response programs, as shown in Chapter 8. Energy Management Systems for Smart Customers. / [ES] La industria eléctrica de potencia está siendo sacudida por una idea que va tomando forma: las smart grids. Tres aspectos pueden considerarse claves para llegar a las smart grids: a) La estructura de la red debe responder al concepto de red inteligente, es decir, ser resistente a fallos, por ejemplo provocando la separación automática de cualquier elemento averiado sin afectar al funcionamiento del resto de la red; ser flexible para permitir la conexión o desconexión de cargas y generadores distribuidos, mantener un funcionamiento eficiente bajo diversos estados de carga, etc. b) La red debe abrir las posibilidades de participación de grandes y pequeños generadores así como de los usuarios, permitiendo nuevas posibilidades de negocio y de participación activa, de manera que la generación o el consumo "inteligentes" se vean beneficiados. c) Todos los participantes deben tener acceso fácil a la información necesaria para poder elegir la mejor estrategia de funcionamiento en cada caso. En lo que respecta a la primera condición (a) hay importantes retos por resolver: automatización de la red, diseño óptimo, desarrollo de nuevas protecciones y equipos de control, etc. Será necesario desarrollar equipos adaptados a los nuevos problemas y nuevas necesidades que se generarán en estas redes. Esos equipos deberán ser normalizados, para lo cual será necesario definir ensayos que tengan en cuenta aspectos que actualmente no suelen ser necesarios, como la presencia de perturbaciones en la tensión, u otros. En este sentido, aunque de forma marginal, se ha colaborado con un laboratorio para ensayos eléctricos, la Flex Power Grid Lab Research Infrastructure del DNV KEMA en los Países Bajos, en la definición y realización de algunos ensayos, como se indica en el Capítulo 3. Smart grids. En el aspecto segundo (b), son necesarios profundos cambios sociales y, sobre todo, legislativos. En cualquier caso, el primer paso consiste en saber cómo es el consumo de los receptores, de qué manera puede variarse la demanda, qué influencia puede tener la pequeña generación (renovable principalmente) y el almacenamiento de energía, etc. Disponer de modelos precisos que proporcionen esta información es clave para que los actores de la red puedan establecer sus mejores estrategias. En la tesis se analizan muchos aspectos relacionados con la demanda de energía y se aborda el problema del control de la participación de diversos recursos y diversos agentes en el funcionamiento del sistema y en el Capítulo 3. Smart grids se muestra el software de gestión y control (en cuyo diseño y desarrollo se ha colaborado) de una pequeña smart grid que existe en el laboratorio LabDER de la UPV, donde se integran diversos recursos en función de las necesidades de la demanda, los precios de la energía, etc. En la tercera condición (c) hay, también, grandes retos por resolver, como la gestión masiva de información y el incremento en el volumen de tránsito de datos que puede representar. En la tesis se proponen diferentes algoritmos para facilitar el tratamiento de los datos disponibles a la hora de optimizar la gestión de los recursos de una smart grid o tomar decisiones de cara a participar en programas de respuesta de la demanda, tal como puede verse en el Capítulo 8. Sistemas de Gestión Energética para Smart Customers. / [CA] La indústria elèctrica de potència està sent sacsada per una idea que va prenent forma: les smart grids. Tres aspectes poden considerar-se claus per a arribar a les smart grids: a) L'estructura de la xarxa ha de respondre al concepte de xarxa intel·ligent, és a dir, ser resistent a fallades, per exemple amb la separació automàtica de qualsevol element avariat sense afectar el funcionament de la resta de la xarxa; ser flexible per a permetre la connexió o desconnexió de càrregues i generadors distribuïts; mantindre un funcionament eficient davall diversos estats de càrrega, etc. b) La xarxa ha d'obrir les possibilitats de participació de grans i xicotets generadors així com dels usuaris. Així, ha de permetre noves possibilitats de negoci i de participació activa, de manera que la generació o el consum "intel·ligents" es vegen beneficiats. c) Tots els participants han de tindre accés fàcil a la informació necessària per a poder triar la millor estratègia de funcionament en cada cas. Pel que fa a la primera condició (a) hi ha importants reptes per resoldre: automatització de la xarxa, disseny òptim, desenrotllament de noves proteccions i equips de control, etc. Serà necessari desenrotllar equips adaptats als nous problemes i noves necessitats que es generaran en aquestes xarxes. Aqueixos equips hauran de ser normalitzats, per a la qual cosa serà necessari definir assajos que tinguen en compte aspectes que actualment no solen ser necessaris, com la presència de pertorbacions en la tensió, o altres. En aquest sentit, encara que de forma marginal, s'ha col·laborat amb un laboratori per a assajos elèctrics, la Flex Power Grid Lab Research Infrastructure del DNV KEMA en els Països Baixos, en la definició i realització d'alguns assajos, com s'indica en el Capítol 3. Smart grids. En l'aspecte segon (b), són necessaris profunds canvis socials i, sobretot, legislatius. En qualsevol cas, el primer pas consisteix a saber com és el consum dels receptors, de quina manera pot variar-se la demanda, quina influència pot tindre la xicoteta generació (renovable principalment) i l'emmagatzemament d'energia, etc. Disposar de models precisos que proporcionen aquesta informació és clau perquè els actors de la xarxa puguen establir les seues millors estratègies. En la tesi s'analitzen molts aspectes relacionats amb la demanda d'energia i s'aborda el problema del control de la participació de diversos recursos i diversos agents en el funcionament del sistema i en el Capítol 3. Smart grids es mostra el programari de gestió i control (en el disseny i desenrotllament del qual s'ha col·laborat) d'una xicoteta smart grid que existeix en el laboratori LabDER de la UPV, on s'integren diversos recursos en funció de les necessitats de la demanda, els preus de l'energia, etc. En la tercera condició (c) hi ha, també, grans reptes per resoldre, com ara la gestió massiva d'informació i l'increment en el volum de trànsit de dades que pot representar. En la tesi es proposen diferents algoritmes per a facilitar el tractament de les dades disponibles a l'hora d'optimitzar la gestió dels recursos d'una smart grid o prendre decisions de cara a participar en programes de resposta de la demanda, tal com pot veure's en el Capítol 8. Sistemes de Gestió Energètica per a Smart Customers. / Roldán Blay, C. (2016). Avances en Verificación y Medida de la Respuesta de la Demanda y Aplicación a su integración en Smart Grids [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61302

Energy systems are evolving into structures in which the role of the consumer is more and more significant. Consumers are no longer the passive entities that in the past had to be supplied in an unidirectional way (from the network to the customer), but can also supply power to the grid through renewable resources, storage capacity through the batteries of their electric vehicles or operating services through the use of their flexibility. However, when discussing on smart grids, electricity supply and consump-tion are the only considered side on many occasions, neglecting other dimensions such as natural gas, sanitary hot water or transport. In this context, this dissertation represents a novel approach to the role of consumers in the natural gas sector. While it is true that electricity consumers have been involved for years in different operation services related to the use of their flexibility (especial-ly in countries such as the United States and more recently in the European Union), the use of demand response resources in the gas sector has been so far non-existent. However, the success of demand response initiatives in electricity systems and their similarity to the gas sector, where their regulatory and technological development has been carried out in parallel in recent years, allows us to expect similar successful re-sults when implementing equivalent programs to gas networks. This dissertation highlights the huge potential that remains unexplored on the demand side of natural gas, which could be used by gas network operators for the solution of technical constraints, balance services or optimization of programming of under-ground storage. This potential is especially interesting at the moment, when the mas-sive installation of smart gas meters has started in some European countries, an infra-structure that would facilitate the use of demand response resources for the better op-eration of gas networks. The dissertation presents, firstly, an exhaustive analysis of the demand response pro-grams currently used in electrical systems around the world, identifying those services that could be equally applicable to the gas sector. The traditional structure based on which gas systems have been developed in different countries is analyzed below. In order to make better use of resources and to optimize its operation, an architecture based on the concept of smart grid is then proposed, identifying the agents that would participate in this structure and emphasizing the role that consumers would play, not only as energy demanders, but also as providers of network services. This active role of demand requires the use of adequate measurement, control and communication technologies, aspect that is also properly analyzed. Based on the results of the analysis mentioned above, this thesis proposes a new meth-odology for the development and evaluation of demand response mechanisms that allow a greater participation of gas consumers in the provision of operating services to the manager of the network, increasing the joint efficiency of the system and reducing the costs associated with such services. The proposed methodology has been successfully applied to the gas network in Italy, where the analyzed operation services have been evaluated in a town of 16,000 inhab-itants located in the central north-Italian area. In that town, consumers have been grouped by end-use, sector and size, which evidences the need to enhance the role of the aggregator for the proper use of the potential of smaller consumers, whether they receive a gas supply directly or through a distributed heat network. The results presented in this dissertation should encourage regulators to empower the use of the consumers' flexibility in order to increase the efficiency of the natural gas system, as it reduces operating costs while favoring the participation of customers in a more dynamic energy structure. / Los sistemas energéticos están evolucionando hacia estructuras en las que el papel desempeñado por el consumidor es cada vez más importante. Hoy en día, los consumidores ya no son los entes pasivos de antaño a los que había que suministrar energía de forma unidireccional (de la red al cliente), sino que también pueden suministrar energía a la red a través de recursos renovables, capacidad de almacenamiento mediante las baterías de sus vehículos eléctricos o servicios de operación a través de la utilización de su flexibilidad. Sin embargo, al hablar de redes inteligentes, en muchas ocasiones se sobreentiende únicamente lo relativo al suministro y consumo de electricidad, obviando otras dimensiones como pueden ser el gas natural, el agua caliente sanitaria o el transporte. En este marco, esta tesis supone un enfoque novedoso en lo que se refiere al papel de los consumidores en el sector del gas natural. Si bien es cierto que los consumidores de electricidad han participado desde hace años en diferentes servicios relacionados con el uso de su flexibilidad, la utilización de la respuesta de la demanda en el sector gasista ha sido hasta ahora inexistente. Sin embargo, el éxito de iniciativas de respuesta de la demanda en los sistemas eléctricos y su similitud con el sector gasista, cuyo desarrollo normativo y tecnológico se ha realizado en paralelo en los últimos años, permite esperar resultados igualmente exitosos al aplicar programas equivalentes a las redes de gas. Esta tesis pone de manifiesto el enorme potencial que permanece inexplorado en el lado de la demanda de gas natural, el cual podría ser utilizado para la solución de restricciones técnicas, servicios de balance u optimización de la programación de los almacenamientos subterráneos. Este potencial resulta especialmente interesante en estos momentos, cuando en algunos países europeos se ha comenzado la instalación masiva de contadores inteligentes de gas. La tesis presenta un análisis exhaustivo de los programas de respuesta de la demanda utilizados en la actualidad en sistemas eléctricos alrededor del mundo, identificándose aquellos servicios que podrían ser aplicables al sector gasista. A continuación se analiza la estructura tradicional en base a la que los sistemas gasistas se han desarrollado en diversos países, proponiéndose a continuación una arquitectura basada en el concepto de red inteligente, donde se identifican los agentes que participarían en esta estructura y se enfatiza el rol que los consumidores desempeñarían no sólo como demandantes de energía, sino también como proveedores de servicios de red. Este papel activo de la demanda necesita de la utilización de tecnologías de medición, control y comunicación adecuadas, aspecto que también se analiza en detalle. En base a los resultados del análisis mencionado, esta tesis propone una nueva metodología para el desarrollo y evaluación de mecanismos de respuesta de la demanda que permitan una mayor participación de los consumidores de gas en la provisión de servicios de operación al gestor de la red, aumentando la eficiencia conjunta del sistema y reduciendo los costes asociados a dichos servicios. La metodología propuesta ha sido aplicada con éxito a la red gasista de Italia, donde los servicios de operación analizados han sido evaluados en una ciudad de 16.000 habitantes, donde los consumidores han sido agrupados por uso final, sector y tamaño. Esto ha puesto de manifiesto la necesidad de potenciar el papel del agregador para valorizar el potencial de los consumidores más pequeños, tanto si reciben un suministro de gas directo o a través de una red de calor distribuido. Los resultados expuestos en esta tesis deberían impulsar a los reguladores a incentivar la utilización de la flexibilidad de los consumidores a fin de incrementar la eficiencia del sistema de gas natural, ya que reduce los costes de operación al tiempo que favorece la particip / Els sistemes energètics estan evolucionant cap a estructures en què el paper exercit pel consumidor és cada vegada més important. Avui dia, els consumidors ja no són els ens passius d'antany als quals calia subministrar energia de forma unidireccional (de la xarxa al client), sinó que també poden subministrar energia a la xarxa a través de recursos renovables, capacitat d'emmagatzematge mitjançant les bateries dels seus vehicles elèctrics o serveis d'operació a través de la utilització de la seva flexibilitat. No obstant això, en parlar de xarxes intel·ligents, en moltes ocasions se sobreentén únicament quant al subministrament i consum d'electricitat, obviant altres dimensions com poden ser el gas natural, l'aigua calenta sanitària o el transport. En aquest marc, aquesta tesi suposa un enfocament nou pel que fa al paper dels consumidors en el sector del gas natural. Si bé és cert que els consumidors d'electricitat han participat des de fa anys en diferents serveis d'operació relacionats amb l'ús de la seva flexibilitat, la utilització de la resposta de la demanda en el sector gasista ha estat fins ara inexistent. No obstant això, l'èxit d'iniciatives de resposta de la demanda en els sistemes elèctrics i la seva similitud amb el sector gasista, el desenvolupament normatiu i tecnològic s'ha realitzat en paral·lel en els últims anys, permet esperar resultats igualment reeixits en aplicar programes equivalents a les xarxes de gas. Aquesta tesi posa de manifest l'enorme potencial que roman inexplorat en el costat de la demanda de gas natural, el qual podria ser utilitzat per a la solució de restriccions tècniques, serveis de balanç o optimització de la programació dels emmagatzematges subterranis. Aquest potencial és especialment interessant en aquests moments, quan en alguns països europeus s'ha començat la instal·lació massiva de comptadors intel·ligents de gas. La tesi presenta una anàlisi exhaustiva dels programes de resposta de la demanda utilitzats en l'actualitat en sistemes elèctrics voltant del món, identificant-se aquells serveis que podrien ser aplicables al sector gasista. A continuació s'analitza l'estructura tradicional sobre la base de la qual els sistemes gasistes s'han desenvolupat en diversos països, proposant-se a continuació una arquitectura basada en el concepte de xarxa intel·ligent, on s'identifiquen els agents que participarien en aquesta estructura i s'emfatitza el paper que els consumidors exercirien no només com a demandants d'energia, sinó també com a proveïdors de serveis de xarxa. Aquest paper actiu de la demanda necessita de la utilització de tecnologies de mesurament, control i comunicació adequades, aspecte que també s'analitza en detall. En base als resultats de l'anàlisi esmentat, aquesta tesi proposa una nova metodologia per al desenvolupament i avaluació de mecanismes de resposta de la demanda que permetin una major participació dels consumidors de gas a la provisió de serveis d'operació al gestor de la xarxa, augmentant l'eficiència conjunta del sistema i reduint els costos associats a aquests serveis. La metodologia proposada ha estat aplicada amb èxit a la xarxa gasista d'Itàlia, on els serveis d'operació analitzats han estat avaluats en una ciutat de 16.000 habitants, on els consumidors han estat agrupats per ús final, sector i grandària. Això ha posat de manifest la necessitat de potenciar el paper de l'agregador per valoritzar el potencial dels consumidors més petits, tant si reben un subministrament de gas directe o mitjançant una xarxa de calor distribuïda. Els resultats exposats en aquesta tesi haurien d'impulsar els reguladors a incentivar la utilització de la flexibilitat dels consumidors a fi d'incrementar l'eficiència del sistema de gas natural, ja que redueix els costos d'operació i alhora afavoreix la participació dels clients en una estructura més dinàmica. / Montuori, L. (2017). Application of demand response strategies for the management of natural gas systems under the smart grid configuration: development of a methodology for technical, economic and environmental evaluation [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90407

Electric Vehicles (EVs) are active loads as they increase the demand for electricity and introduce several challenges to electrical distribution feeders during charging. Demand Response (DR) or performing load control in commercial buildings along with the deployment of solar photovoltaic (PV) and ice storage systems at the building level can improve the efficiency of electricity grids and mitigate expensive peak demand/energy charges for buildings. This research aims to provide such a solution to make EV penetration transparent to the grid. Firstly, this research contributes to the development of an integrated control of major loads, i.e., Heating Ventilation and Air Conditioning (HVAC), lighting and plug loads while maintaining occupant environmental preferences in small- and medium-sized commercial buildings which are an untapped DR resource. Secondly, this research contributes to improvement in functionalities of EnergyPlus by incorporating a 1-minute resolution data set at the individual plug load level. The research evaluates total building power consumption performance taking into account interactions among lighting, plug load, HVAC and control systems in a realistic manner. Third, this research presents a model to study integrated control of PV and ice storage on improving building operation in demand responsive buildings. The research presents the impact of deploying various combinations of PV and ice storage to generate additional benefits, including clean energy generation from PV and valley filling from ice storage, in commercial buildings. Fourth, this research presents a coordinated load control strategy, among participating commercial buildings in a distribution feeder to optimally control buildings' major loads without sacrificing occupant comfort and ice storage discharge, along with strategically deployed PV to absorb EV penetration. Demand responsive commercial building load profiles and field recorded EV charging profiles have been added to a real world distribution circuit to analyze the effects of EV penetration, together with real-world PV output profiles. Instead of focusing on individual building's economic benefits, the developed approach considers both technical and economic benefits of the whole distribution feeder, including maintaining distribution-level load factor within acceptable ranges and reducing feeder losses. / Ph. D. / Utilities generally meet peak demand through expensive peaking units which are operated only for short periods of time. At the same time the growing demand for Electric Vehicles (EVs) in the U.S. impacts the already burdened distribution feeder during peak hours. EVs are active loads as they increase the distribution feeder’s demand when charging. EV charging may bring about several challenges to the distribution feeder, including reduced load factors, potential transformer overloads, feeder congestion and violation of statutory voltage limits. On the other hand, building owners want to make buildings demand responsive so that they can participate in a demand response program offered by a regional electric grid operator to earn additional revenues. Allowing buildings to be demand-responsive by controlling buildings’ major loads, including HVAC (Heating, Ventilation and Air Conditioning), lighting and plug loads based on demand reduction signals from the grid has proven to provide tremendous savings. Additionally, optimized peak demand reductions at the building level by means of coordinated control of building loads, solar photovoltaic (PV) and ice storage systems can play a major role in flattening the building load shape, thereby decreasing its peak electricity consumption and at the same time mitigating grid stress conditions when needed. This study discusses the impacts of EV charging on a distribution feeder serving demand responsive commercial customers and develops a mitigation strategy to make EV penetration transparent to the grid. The mitigation strategy relies on coordinated control of major loads in demand responsive commercial buildings, ice storage discharge, along with strategically deployed PV. The analysis presented in this study shows that the developed approach can help mitigate EV penetration challenges by reducing the peak distribution system load, reducing feeder losses and improving distribution system load factor.

This master thesis evaluates the incentives of a newly implemented market controlled network tariff by analyzing consumption data and constructing a time-differentiated debiting model. The tariff was implemented by Sandviken Energi Elnät AB and the thesis evaluates its customers consumption data compared to data provided by Sundsvall Elnät AB. The differences in data is evaluated by statistical tests of Students t-test, Bayesian t-test and χ2-test with the result that no statistically significant change in user pattern can be found and thus an elucidation of the incentives must be made in the form of a hourly time-differentiated debating model. The thesis also evaluates the cost incentives of the model compared to spot prices where it is shown that the tariff model can benefit much from the spot prices hourly incentives in its hourly time-differentiated model. Five time-differentiated models were constructed and presented where three uses a color coding scheme. The conclusion is that a color coded time-differentiated tariff should give the costumers clear and cost-effective incentives.

Die Verwendung elektrischer Energie ist ein essenzieller Bestandteil industrieller Prozesse. Aufgrund der aktuellen Bemühungen für eine Energiewende hin zu regenerativen Energien ist es sehr wahrscheinlich, dass die industrielle Bedeutung des elektrischen Stromes weiter zunehmen wird. Damit dabei die Ziele der Roadmap 2050, eine Reduzierung des CO2-Ausstoßes um 80 % bezogen auf 1990, erreichbar bleiben, bedarf es der unausweichlichen Etablierung erneuerbarer Energien. Dies ist kostenintensiv und aufgrund der ungleichmäßigen Energiebereitstellung nicht ohne Probleme für die aufgebauten Netzstrukturen. Der flexible Leistungsbezug (Demand Response) wird aufgrund seines netzdienlichen Charakters als ein Schlüssel zur Netzstabilisierung und direkten Energiekostenreduzierung gesehen. Jedoch trägt die energieintensive Papierindustrie mit ihren Papiermaschinen bislang keinen bedeutenden Teil zu diesem Ansatz bei und profitiert demnach auch nicht von den finanziellen Vorteilen. Eine Ursache dafür ist, dass dieser Branche auf Grundlage der bisherigen Be-wertungsmethoden kaum wirtschaftliche Potentiale für einen flexiblen Lastbezug zugespro-chen werden. Ein wesentlicher Teil der vorliegenden Arbeit widmet sich der Entwicklung eigner, den Be-dürfnissen der Papierindustrie angepassten, Erhebungs-, Bewertungs- sowie angeschlosse-nen Vermarktungsmethoden für eine Energiekostenreduzierung auf der Grundlage flexibler Lasten. Für die Kostenoptimierung stehen unterschiedliche Möglichkeiten, wie die in der vor-liegenden Arbeit betrachtete Regelleistungsvermarktung, zur Verfügung. Die Ergebnisse eines sortenspezifischen Analyseansatzes von Prozess- und Energieein-satzkennzahlen zeigen, dass von der Papierindustrie ein größeres Mitwirken am Regelleis-tungsmarkt zu erwarten sein kann, als es bisher angenommen wurde. Die erkannten Poten-tiale zur Lastflexibilisierung sind jedoch nicht jederzeit verfügbar. Damit diese Verfügbarkeit nicht überschritten wird, müssen die Mechanismen, die zum Regellastabruf führen, verstan-den und deren Einfluss auf einen Lastabruf genutzt werden. Zu diesem Zweck wurde im Zuge der Arbeit die Grenzlast eingeführt. Die Grenzlast kennzeichnet die Regellasthöhe, welche aus statistischer Sicht nicht öfter abgerufen wird, als es die Verfügbarkeit zulässt. Es wird belegt, dass auch von der Papierindustrie eine Beteiligung am Regelenergiemarkt möglich ist und die Energiekosten auf diese Weise reduzierbar wären, ohne den Fokus auf das Kerngeschäft zu verlieren.:I. Abbildungsverzeichnis II. Tabellenverzeichnis III. Formelverzeichnis IV. Abkürzungen, Formelzeichen V. Thesenübersicht 1 Einleitung und Motivation 1.1 Zielstellung und Aufbau der Arbeit 1.1.1 Ziele der Untersuchungen 1.1.2 Abgrenzung zu verfügbaren Software-Lösungen 1.2 Energieoptimierung – Sichtweisen und Definitionen 1.3 Energiepolitik und umweltpolitische Forderungen 1.3.1 Roadmap 2050 1.3.2 Zieldreieck 1.3.3 Flexible Lasten und der zukünftige Energiemarkt 2 Theoretische Grundlagen 2.1 Key Perfomance Indicator - Schlüsselfaktoren 2.2 Kennzahlen der Papierindustrie 2.3 Energiesystem in Deutschland 2.3.1 Energiepreise – Preisbildung 2.4 Netzregulierung – Regelleistung 2.5 Charakterisierung von Regelleistungsarten 2.5.1 Datenaufbereitung des Regelleistungseinsatzes 2.5.2 Minutenreserve 2.5.3 Sekundärreserve 2.6 Demand Response 2.6.1 Demand Response - Definition 2.6.2 Demand Response – Speicher 2.6.3 Finanzielle Auswirkungen von Demand Response 3 Methodik – Entwicklung und Durchführung 3.1 Ableitung konkreter Arbeitsaufgaben 3.2 Erhebung sortenspezifischer Kennzahlen 3.2.1 Sortenspezifische Kennwertberechnung 3.2.2 For-Schleife 3.2.3 Anwendungssoftware 3.2.4 Überführung produktspezifischer Kennzahlen in den Produktionsplan 3.3 Potentialerhebung flexibler Lasten 3.3.1 Potentialermittlung nach Klobasa 3.3.2 Diskussion der Klobasa Methode im Kontext weiterer Methoden 3.4 Analyse der Auktionsergebnisse von Regelleistung 3.5 Ermittlung und Einflussnahme auf die Abrufdauer von Regelleistung 3.5.1 Grenzlastprognose 3.5.2 Entwicklung der Preisstruktur zur Energiekostenoptimierung 3.6 Eignungsbewertung der ermittelten Regelleistungspotentiale 4 Anwendung grundlegender Erkenntnisse und Methoden 4.1 Reservelastpotential durch Änderung des Dampfbezuges 4.1.1 Ermittlung der Potentialhöhe 4.1.2 Qualitätsbewertung der potentiellen Reserveleistung 4.1.3 Ermittlung der Potentialverfügbarkeit 4.1.4 Herleitung und Bewertung des Arbeitspreises 4.1.5 Herleitung und Bewertung des Leistungspreises 4.1.6 Bestimmung der Energiekostenoptimierung 4.2 Reservelastpotential durch Änderung der Antriebslast - Ausblick 4.2.1 Qualitätsbewertung – sortenspezifische Betrachtung der Antriebslast 5 Effizienzsteigerung durch sortenspezifische Kennwerte 5.1 Energieoptimierungssystem 5.1.1 Zielwerterhebung im Energie Optimierungs System (EOS) 5.1.2 Funktionsweise des EOS 6 Zusammenfassung VI. Literaturverzeichnis VII. Anhang

District heating plays a major role in the Swedish energy system. It is deemed a renewable energy source and is the main provider for multi-family dwellings with 90 %. Although the district heating fuel mix consists of majority renewables, a share of 5 % is provided from fossil fuels. To reduce fossil fuel usage and eradicate CO2-emissions from the district heating system new solutions are sought after. In this project, the potential for shortterm thermal energy storage in buildings is investigated. This concept is referred to as customer flexibility. Demand flexibility is created in the district heating system (DHS) by varying the indoor temperature in 50 multi-family dwellings with maximum 1◦C, without jeopardizing the thermal comfort for the tenants. The flexible load makes it possible to store energy shortterm in the building’ envelope. Consequently, heat load curves are evened in production. This leads to a reduction of the peak load in the DHS. Peaks are associated with high costs and environmental impact. Therefore, the potential benefits of customer flexibility are reduced peak production, fuel costs, and CO2-emissions, depending on the fuel mix in the DHS. The project objective is to examine the techno-economic potential of customer flexibility in a specific DHS. The case study is made in a DHS owned by the company Vattenfall, located in the Stockholm area. To evaluate the potential benefits of implementing the concept, seven key performance indicators are chosen. They are peak power, peak fuel usage, produced volume, total fuel cost, fuel cost per produced MWh, climate footprint, and primary energy. Moreover, an in-house optimization model is used to simulate multiple scenarios of the district heating DHS. Different sets of assumptions about the available flexibility in the DHS and the thermal characteristics of the buildings are made. Customer flexibility is modeled as virtual heat storage that can be charged up or down depending on the speed and size of the available storage at a specific outdoor temperature. Simulation results give a maximum peak power reduction of 10.9 % and annual fuel cost reduction between 0.9-3.6 % depending on the scenario. The results found are comparable to values found in similar studies. However, the environmental key performance indicators generated an increase in CO2-emissions and primary energy compared to the baseline scenarios. The result would have looked different if fossil fuels were used in peak production instead of biofuels. The master thesis also aimed to validate assumptions and parameters made in the input data to the optimization model. This was achieved by using results attained from a pilot in the specific DHS. Therefore results generated from the simulations are deemed accurate and confirm that customer flexibility leads to reduced peak production and DHS optimization. / Se filen

Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration. This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity. The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales. / Graduate / 0791 / sahandbehboodi@gmail.com

The implementation of a low carbon electricity system within the GB requires a significant change to the generation mix with an increasing role for renewable generation. Much of this generation will be intermittent. To date system balancing has largely relied on predicting demand and ensuring provision. With substantial intermittency, continuation of this paradigm necessitates significant investment in peaking plant and/or storage. However, some of this investment can be avoided by harnessing the flexibility inherent in many electrical loads. Despite the attractiveness of such services, we do not see their large-scale implementation. The aim of this thesis is to consider why. A historical analysis reveals that both nationalisation and subsequent privatisation provide precedents for significant structural change as the integration of large-scale flexible demand might require. The need for political will is identified as a crucial enabling factor. Without an ideological driver, however, a perception of economic and/or technological risk can preclude the implementation of supportive policy. This perception is addressed through demonstration. An effective demonstration must show the ability to aggregate many small loads in a coordinated manner. A genetic algorithm that provides this core dispatch and optimisation capability is presented. This algorithm is shown to be effective in aggregating many small loads to provide a net effect that can be used as a balancing service and to do so in an optimal way considering both cost and reliability. Having demonstrated feasibility appropriate incentives must be created. An initial outline for a framework based on SysML is presented that can be used to identify where structural barriers to implementation are present to aid the design of appropriate policy incentives.