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 el marco de un mercado de la electricidad con precios cada vez más altos y donde la participación de fuentes renovables de generación está jugando un papel cada vez más importante, esta tesis supone un enfoque innovador hacia la participación de recursos de demanda en mercados de operación, prestando una atención especial a segmentos industriales como el sector alimentario con un consumo energético intensivo. En primer lugar, esta tesis describe detalladamente la situación actual de los programas de respuesta de la demanda que existen en diferentes partes del mundo. Este estudio permite concluir que los consumidores no han sido tenidos en cuenta suficientemente en la fase de diseño de los programas existentes, lo que ha provocado la infrautilización de recursos de demanda que, actualmente, permanecen sin explorar. Por otro lado, los consumidores no son conscientes del valor que su flexibilidad podría tener para el sistema eléctrico en su conjunto, ignorando que puedan existir otros agentes dispuestos a pagarles a cambio de reducir sus cargas en períodos determinados. Como resultado, esta tesis desarrolla una nueva metodología para explorar y valorar nuevos mecanismos de respuesta de la demanda donde el punto de vista de consumidores, operadores de red y cualquier otro agente interesado pueda ser tenido en cuenta. Esta metodología, basada en la evaluación y análisis detallado de los procesos, proporciona a los consumidores las herramientas adecuadas para evaluar su capacidad para reaccionar al precio de la electricidad, lo que permitiría al regulador poner en valor el beneficio social de dicha flexibilidad si pudiera ser utilizada en mercados de operación, ayudándole a definir los programas necesarios para utilizar de forma adecuada el potencial identificado por los consumidores. La metodología desarrollada en esta tesis ha sido aplicada satisfactoriamente al sub-segmento de la industria cárnica, por lo que varias fábricas pertenecientes a este segmento han sido estudiadas en detalle. En concreto, la factibilidad de las acciones propuestas ha sido probada y validada satisfactoriamente en una fábrica dedicada a la producción de jamón curado en España, en la que se han evaluado diferentes estrategias de flexibilidad. Finalmente, se ha realizado una evaluación económica de la rentabilidad de la aplicación de las acciones de flexibilidad propuestas tanto para el consumidor como para el sistema eléctrico en su conjunto, donde se han considerado los precios reales de los mercados de operación en España, aun cuando los consumidores no puedan participar realmente en dichos mercados en la actualidad. / Alcázar Ortega, M. (2011). Evaluation and Assessment of New Demand Response Products based on the use of Flexibility in Industrial Processes: Application to the Food Industry [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10078

[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

One hundred and twenty-two students at Virginia Tech who had completed teacher certification requirements in science and/or mathematics from 1980 to 1986 were surveyed to determine their current employment status, and if not currently teaching, then what reforms in the conditions of teaching might encourage them to return to or enter teaching. Opinions were solicited from three groups: current teachers, those who had left teaching, and those who had never taught. Data were reported in four categories: general demographics of all groups, importance of work satisfaction for all groups, modifications in the conditions of teaching necessary to entice those not currently teaching to return to or enter teaching, and opinions of current teachers on how to improve recruitment and retention of qualified science and mathematics teachers. It was determined that the general demographics of the individuals surveyed conformed to general descriptions of teachers in current literature with the exception that the parents of Virginia Tech graduates were more highly educated and tended to hold professional and semiprofessional positions in higher percentages. No significant differences were determined among current teachers, those who left teaching, and those who had never taught in regard to opinions of work satisfaction in teaching. Lack of administrative support, poor student discipline, and low salaries were factors involved with decisions not to teach. Others left teaching to raise a family. Improvements in working conditions that would encourage non-teachers to teach include improvement of student discipline, reduction of class size, removal of incompetent teachers, reduction of teacher isolation, reduction of stress, and the improvement of the physical environment. Almost 60% of individuals not currently teaching would teach if offered a suitable position. The majority of current teachers believe that raising teachers' salaries would be the most important improvement to increase recruitment and retention of teachers, however, beginning teachers' salaries compared favorably with those of individuals employed outside of education. Almost two out of three current teachers indicated they planned to leave teaching within five or more years. / Ed. D.

This dissertation provides a comprehensive examination of the role of Transportation Networking Companies (TNC) across four dimensions. First, we examined the factors affecting Transportation Networking Companies (TNC) pricing and destination choice behavior using weekday TNC trip data from Chicago spanning January 2019 through December 2019. Towards achieving this goal, we developed a joint model framework where trip fare is modelled using linear regression model (LR) and destination choice is modelled using a multinomial logit model (MNL). Second, we build a systematic framework to analyze spatial TNC demand patterns (origins) across the urban region at the census tract (CT) level and compare them to overall transportation demand. We propose and compute a novel metric at the census tract level to identify the potential imbalance between overall transportation demand and TNC demand by developing a Generalized Ordered Logit. The model applicability is further illustrated through elasticity analysis. Third, based on earlier studies we identified that current TNC related macroscopic studies do not incorporate attributes at the microscopic resolution. We bridge the macroscopic and microscopic analysis using a bi-level modeling approaching that accommodates for the influence of microscopic attributes within the macroscopic modeling approach. In this proposed framework, the trip level destination choice model (microscopic model) takes the form of a multinomial logit model and the origin-destination flow model (macroscopic model) takes the form of a multinomial logit fractional split model. Finally, in our effort to incorporate TNCs into travel demand tools, we conducted a comprehensive literature review on studies examining the impact of TNCs on various components of travel demand models (TDM). We provide guidelines for potential travel demand model updates using three use case examples including vehicle ownership model, trip generation model, and trip level mode choice components.

Yes / This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

The diploma thesis deals with the analyses of demand using standard tools of engineering mathematics. Mathematical models of demand, both single and multi- factor are investigated. Elasticity of demand is applied for decision making in price policy. Problems of optimization of demand reflecting utility and budget constraints are under consideration. Constructions of demand curve and compensated demand curve are presented. The text is accompanied by illustrative examples aiming at methodical aspects of the work

Fuel supply issues are a major concern in remote island communities and this is an engineering field that needs to be analyzed in detail for transition to sustainable energy systems. Power generation in remote communities such as the islands of the Maldives relies on power generation systems primarily dependent on diesel generators. As a consequence, power generation is easily disrupted by factors such as the delay in transportation of diesel or rises in fuel price, which limits shipment quantity. People living in remote communities experience power outages often, but find them just as disruptive as people who are connected to national power grids. The use of renewable energy sources could help to improve this situation, however, such systems require huge initial investments. Remote power systems often operate with the help of financial support from profit-making private agencies and government funding. Therefore, investing in such hybrid systems is uncommon. Current electrical power generation systems operating in remote communities adopt an open loop control system, where the power supplier generates power according to customer demand. In the event of generation constraints, the supplier has no choice but to limit the power supplied and this often results in power cuts. Most smart grids that are being established in developed grids adopt a closed loop feedback control system. The smart grids integrated with demand side management tools enable the power supplier to keep customers informed about their daily energy consumption. Electric utility companies use different demand response techniques to achieve peak energy demand reduction by eliciting behavior change. Their feedback information is commonly based on factors such as cost of energy, environmental concerns (carbon dioxide intensity) and the risk of black-outs due to peak loads. However, there is no information available on the significant link between the constraints in resources and the feedback to the customers. In resource-constrained power grids such as those in remote areas, there is a critical relationship between customer demand and the availability of power generation resources. This thesis develops a feedback control strategy that can be adopted by the electrical power suppliers to manage a resource-constrained remote electric power grid such that the most essential load requirements of the customers are always met. The control design introduces a new concept of demand response called participatory demand response (PDR). PDR technique involves cooperative behavior of the entire community to achieve quality of life objectives. It proposes the idea that if customers understand the level of constraint faced by the supplier, they will voluntarily participate in managing their loads, rather than just responding to a rise in the cost of energy. Implementation of the PDR design in a mini-grid consists of four main steps. First, the end-use loads have to be characterized using energy audits, and then they have to be classified further into three different levels of essentiality. Second, the utility records have to be obtained and the hourly variation factors for the appliances have to be calculated. Third, the reference demand curves have to be generated. Finally, the operator control system has to be designed and applied to train the utility operators. A PDR case study was conducted in the Maldives, on the island of Fenfushi. The results show that a significant reduction in energy use was achieved by implementing the PDR design on the island. The overall results from five different constraint scenarios practiced on the island showed that during medium constrained situations, load reductions varied between 4.5kW (5.8%) and 7.7kW (11.3%). A reduction of as much as 10.7kW (15%) was achieved from the community during a severely constrained situation.

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.

This thesis is divided into two parts. Part I deals with demand management. For goods with no substitutes, under supply constraints, fairness considerations introduce negative externalities and lead to a market failure. One example of such a good with no substitutes is water. In case of a market failure, it is necessary to design coordination mechanisms called contracts which provide the right incentives for coordination. As “repetition can yield coordination”, the aim in this part is to design price based dynamic demand management contracts which, under supply constraints, mitigate the market failure. In these contracts, we consider complete information settings; and use the status quo proposition as a fairness criterion for designing them. The contracts are designed as almost noncooperative dynamic games, within the agency theory framework, where the agent (the consumer) is induced to consume at a specified consumption level based on the incentive mechanism offered by the principal (the producer). These contracts use the solution concept of sub-game perfect Nash equilibrium (SPNE) to compute the price (mal-incentive) that acts as a credible threat for deviation from the specified consumption level. In these contracts, unlike the dynamic contracts with asymmetric information, the penalty for deviation is proportional to the amount of deviation. First, we consider a two-period demand management contract for a single consumer satisfying the status quo proposition. Under the assumption that the gain to the consumer and the loss to the producer by deviation is small, the contract is shown to be economically efficient. It is shown that, in the finite horizon, a fair demand management contract cannot be efficient. The demand management contract is homeomorphic to finite horizon alternating bargaining model. In the finite horizon alternating bargaining model, there is a unique SPNE, in which the player who offers last is always at an advantageous position. In the two-period contract, the assumption considered attenuates the last mover advantage and leads to the efficiency. We have shown that one possible way to achieve efficiency, without the assumption, is to make the agents uncertain about the period of interaction. This possibility can be included in an infinite horizon contract. Hence, next, we design an infinite horizon contract for a single consumer. It is proved that this contract is economically efficient and provides revenue sufficiency. The sensitivity analysis of the contract shows that the discounting rate measures the aversion to conservation characteristics of the consumer. The analysis of the contract shows that a sufficiently time-patient consumer is not penalized for the deviation, as the consumer himself is aware of conservation requirements. This result is similar to the results for the present-biased preferences in behavioral economics. Lastly, the infinite horizon contract is extended to two consumers case which internalizes the externality a consumer causes to another. In the two consumer case, consumers are strategically noninteracting; and it is shown that the producer acts as a budget balancer. These contracts are also shown to be economically efficient. The demand management contracts achieve both the procedural and end-state fairness. Also, the infinite horizon contracts are homeomorphic to infinite horizon alternating bargaining model. The efficiency of infinite horizon contracts is due to their homeomorphism with the alternating bargaining process as they exhaust all possible mutual gains from exchange. In the two-period model, the bargaining process is constrained and hence all possible mutual gains are not eliminated, leading to the inefficiency. In part II of the thesis, we discuss the notions of exchangeability in the Shapley value. The Shapley value is a probabilistic value for the transferable utility (TU) cooperative games, in which each player subjectively assigns probabilities to the events which define their positions in the game. In this part, the objective have been to explore the aspect of subjective probability which leads to the uniqueness of the Shapley value. This aspect of subjective probability is known as exchangeability. We derive the Shapley value using de Finetti’s theorem. We also show that, in the Shapley value, each player’s prospects of joining a t-player game as the last member of the game is a moment sequence of the uniquely determined uniform distribution. We stress on finite exchangeability; and deduce that, with finite exchangeability, the Shapley value is the only value in which the probability assignment is a unique mixture of independent and identical distributions. It is concluded that, in both the finite and infinite exchangeable cases, the uniqueness of probability assignment in the Shapley value is due to exchangeability and the mixing with the uniform distribution.