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.

The ability for domestic consumers to provide demand response to dynamic electricity pricing will become increasingly valuable for integrating the high penetrations of renewables that are expected to be connected to electricity networks in the future. The aim of this thesis is to investigate whether domestic consumers will be willing and able to provide demand response in such low-carbon futures. A broad approach is presented in this thesis, with research contributions on subjects including data privacy, behavioural economics, and battery modelling. The principle argument of the thesis is that studying the behaviour of consumers with grid-connected photovoltaic ('PV') systems can provide insight into how consumers might respond to dynamic pricing in future low-carbon power systems, as both experience irregular electricity prices that are correlated with intermittent renewable generation. Through a combination of statistical and qualitative methods, this thesis investigates the demand response behaviour of consumers with PV systems in the UK. The results demonstrate that these consumers exhibit demand response behaviour by increasing demand during the day and decreasing demand during the evening. Furthermore, this effect is more pronounced on days with higher irradiance. The results are novel in three ways. First, they provide quantified evidence that suggests that domestic consumers with PV systems engage in demand response behaviour. Second, they provide evidence of domestic consumers responding to irregular electricity prices that are correlated with intermittent renewable generation, thereby addressing the aim of this thesis, and supporting the assumption that consumers can be expected to respond to dynamic pricing in future markets with high penetrations of renewables. Third, they provide evidence of domestic consumers responding to dynamic pricing that is similar to real-time pricing, while prior evidence of this is rare and confined to the USA.

Over recent years, political, technological, environmental and economic factors have combined to increase interest in distributed energy resources (DER), and flexibility in the power system. As a resource which is both distributed and flexible, flexible demand (FD) can be considered to be particularly of interest. However, due to many facets of its nature, understanding the available flexibility, and potential value of that flexibility, is difficult. Further, understanding the effects of FD exploitation on other multi-energy system actors, given the complex nature of modern liberalised energy systems, complicates the picture further. These factors form material obstructions to the assessment of FD, for example, for the construction of business cases. To address these gaps this thesis first assesses the nature and value of various applicable current and potential markets and charging/incentive regimes, before detailing a novel multi-energy domestic demand simulation model, capable of modelling, in detail, domestic FD resources. Subsequently, a multi-commodity stochastic energy/reserve optimisation model, capable of modelling various DERs and taking into account price signals related to various energy-related commodities and services (including user utility) is specified. The separation of price components for application at different aggregation levels, which is applied in the optimisation model, also informs the described value mapping methodology, which illustrates the impacts of any, particularly demand-side, intervention on the wider multi-energy system. The power of the above detailed contributions are demonstrated through various studies, which show the physical and economic impact of various demand side interventions and of greater market participation by FD resources.

Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.

L’intégration des producteurs décentralisés (DG) dans un réseau de distribution peut modifier le profil de tension et influencer le réglage de tension conventionnel. Pour le bon fonctionnement du réseau, le raccordement des DG ainsi que les charges grosses sont limités par le dimensionnement du réseau. Les travaux de cette thèse ont pour but de proposer une approche du réglage de tension dans un réseau de distribution avec producteur, en appuyant sur la flexibilité de la demande. Les moyens de réglage de tension seront constitués du régleur en charge (OLTC), la régulation de DG ainsi que la demande flexible. Une optimisation centralisée de type MINLP est proposée pour coordonner ces moyens de réglage. Il est montré que si les moyens de l’OLTC et de la puissance réactive ne suffissent pas de lever la contrainte de tension, il faut réduire la puissance active de producteur. Pour le gain de producteur, la demande flexible peut être considérée comme une source active. La modulation de « demand response » (DR) utilisant les charges thermiques est alors proposée au réglage de tension. L’effet de rebond est pris en compte pour les charges thermiques afin de ne pas affecter le profil de tension après l’action de DR. Ces travaux permettent d’envisager un réglage de tension plus active dans le réseau intelligent et augmenter la flexibilité du réseau. / Growth of distributed generations (DG) in actual distribution networks will bring voltage issues that cannot be fixed by conventional voltage control means. For the sake of network safety, the size of DG and load in a distribution network is limited by the network parameters. The research described in this thesis aims to propose a voltage control strategy on distribution networks using the flexibility of demand. The voltage control means will consist of the on load tap changer (OLTC), the regulation of DG, and flexible demand. A centralized optimization of MINLP type is proposed to coordinate these voltage control means. It shows if it is not able to remove the voltage constraint with OLTC and reactive power regulation, then it must reduce the active power of DG. In order not to reduce active power of DG, the flexible demand is considered as an active source to take part in voltage control. The demand response (DR) modulation using thermal loads is thus proposed for voltage control. For the thermal load, the cold load pick-up (CLPU) effect must be taken into account in order not to affect the voltage profile after DR action. This work allows us to consider a voltage control strategy more active in smart distribution network and improve the flexibility of network.

L’intégration des producteurs décentralisés (DG) dans un réseau de distribution peut modifier le profil de tension et influencer le réglage de tension conventionnel. Pour le bon fonctionnement du réseau, le raccordement des DG ainsi que les charges grosses sont limités par le dimensionnement du réseau. Les travaux de cette thèse ont pour but de proposer une approche du réglage de tension dans un réseau de distribution avec producteur, en appuyant sur la flexibilité de la demande. Les moyens de réglage de tension seront constitués du régleur en charge (OLTC), la régulation de DG ainsi que la demande flexible. Une optimisation centralisée de type MINLP est proposée pour coordonner ces moyens de réglage. Il est montré que si les moyens de l’OLTC et de la puissance réactive ne suffissent pas de lever la contrainte de tension, il faut réduire la puissance active de producteur. Pour le gain de producteur, la demande flexible peut être considérée comme une source active. La modulation de « demand response » (DR) utilisant les charges thermiques est alors proposée au réglage de tension. L’effet de rebond est pris en compte pour les charges thermiques afin de ne pas affecter le profil de tension après l’action de DR. Ces travaux permettent d’envisager un réglage de tension plus active dans le réseau intelligent et augmenter la flexibilité du réseau. / Growth of distributed generations (DG) in actual distribution networks will bring voltage issues that cannot be fixed by conventional voltage control means. For the sake of network safety, the size of DG and load in a distribution network is limited by the network parameters. The research described in this thesis aims to propose a voltage control strategy on distribution networks using the flexibility of demand. The voltage control means will consist of the on load tap changer (OLTC), the regulation of DG, and flexible demand. A centralized optimization of MINLP type is proposed to coordinate these voltage control means. It shows if it is not able to remove the voltage constraint with OLTC and reactive power regulation, then it must reduce the active power of DG. In order not to reduce active power of DG, the flexible demand is considered as an active source to take part in voltage control. The demand response (DR) modulation using thermal loads is thus proposed for voltage control. For the thermal load, the cold load pick-up (CLPU) effect must be taken into account in order not to affect the voltage profile after DR action. This work allows us to consider a voltage control strategy more active in smart distribution network and improve the flexibility of network.

Abstract The global energy system is undergoing a slow but massive change, initiated by environmental concerns but it is increasingly driven also by the zero-marginal cost of renewable energy. This change includes an increase in the effort to make the electric power system the main transport path for energy in the future. A massive research and development effort has henceforth been put into modernizing the electricity grid towards a so-called Smart Grid, by combining the power grid with communication networks and automation, as well as modernized market systems and structures. This work contributes to this process by introducing two unique models. The first provides a tool for better understanding the impact of combined infrastructure networks with a simple yet complex model of a combined energy, communication and decision model. The second model provides a detailed agent-based environment of an electricity market, supporting various independent entities inside the market, as well as a high time resolution and the often-neglected aspect of coupled market stages. That is, all mis-predictions of the first market stage (day-ahead) have to be settled at the second (balancing) stage. Both models are then used to assess the problem of demand side management, in which the traditional practice of power production being adjusted to the demand is at least partially dropped and flexibility in the demand is used to match the supply – as such technologies are deemed crucial to integrate the unsteady supply from renewable resources, like wind and solar power. We find that complicated scaling effects can be found even in the simplified model, hinting at insufficient consideration of the complexities involved in the real world. We then go to show such unfavorable scaling effects also exist in the current market environment as modeled in our second model. Finally, we show how to circumvent these problems within the current environment as well as introduce a framework to analyze cyber-physical systems and better handle their complexity. / Tiivistelmä Globaali energiajärjestelmä on hitaan, mutta massiivisen muutoksen edessä. Tämän muutostarpeen on käynnistänyt ympäristöämme koskevat huolet, mutta lisääntyvässä määrin tähän vaikuttaa nykyään uusiutuvan energian marginaalikustannusten nollataso. Tähän muutokseen liittyy selkeä sähköverkkojen roolin korostuminen, ja pyrkimyksenä näyttää olevan muutos, jossa sähköverkot siirtävät suurimman osan käyttämästämme energiasta. Tämän seurauksena on käynnistetty merkittäviä tutkimus-ja tuotekehityspanostuksia, joiden tavoitteena on nykyaikaistaa sähköverkot älysähköverkoiksi. Älysähköverkoissa yhdistyvät sähköverkkoon integroidut tietoliikenneverkot ja automaatio sekä modernit sähkömarkkinajärjestelmät ja -rakenteet. Tämä työ tuottaa lisää ymmärrystä uudistumisprosessiin tuottamalla kaksi uutta malliratkaisua. Ensimmäisessä mallissa kehitetään työkalu, jonka avulla pystytään paremmin ymmärtämään toisiinsa yhdistettyjen infrastruktuuriverkkojen toimintaa yksinkertaisella, mutta kompleksisella mallilla, jossa energia- ja tietoliikenneverkot sekä tarvittava päätöksenteko yhdistetään. Toinen malli tuottaa yksityiskohtaisen agenttipohjaisen ympäristön sähkömarkkinasta. Malli tukee erilaisten itsenäisten sähkömarkkinaosapuolten mallintamista korkealla aikaresoluutiolla ja erityisesti usein huomiotta jätettyjen toisiinsa kytkeytyvien eri markkinavaiheiden mallintamista. Malli antaa eväitä vastata kysymykseen, miten ensimmäisessä markkinavaiheessa (vuorokausimarkkina) syntyvä ero tuotannon ja kulutuksen välillä tasapainotetaan toisessa markkinavaiheessa (tasapainotusmarkkina). Kumpaakin luotua mallia hyödynnetään arvioitaessa kulutushallintaa, jossa sähköverkkojen perinteisestä tuotannon ja kulutuksen tasapainosta ainakin osittain luovutaan ja kysyntä- eli kulutusjoustoa käytetään tasaamaan kulutus tuotannon suuruiseksi. Tämänkaltaiset mekanismit ovat oleellisia ja kriittisiä, kun sähköverkkoon liitetään suuria määriä vaihtelevatuottoista uusiutuvaa energiaa, kuten aurinko- ja tuulienergiaa. Tutkimuksessa huomasimme merkittäviä ja monimutkaisia skaalautuvuusilmiöitä, jotka kertovat, että sähköverkkojen tutkimuksessa reaalimaailman kompleksisuuden huomioiminen on ollut riittämätöntä. Sähkömarkkinamallia hyödyntämällä huomasimme vastaavia epätoivottuja skaalausilmiöitä esiintyvän myös nykyisessä sähkömarkkinassa. Erityisesti loimme keinoja, joilla skaalausilmiöistä on mahdollista päästä eroon nykyistä sähkömarkkinarakennetta käytettäessä. Tässä työssä luotuja malleja ja niiden viitekehystä hyödyntämällä pystymme paremmin analysoimaan kyberfysikaalisia järjestelmiä ja hallitsemaan niiden kompleksisuutta.

The purpose of this thesis is to simulate different scenarios where all vehicles are replaced by electric vehicles in the future.   An addition of electric vehicles to the electric grid is not easy to handle, especially not if the consumers choose to charge their vehicles with higher power. As can be seen in the results of this report, flexible demand through power management is a good option to reduce overall power consumption. Of course, customers will have to agree to that their consumption is controlled in this manner.   Using solar cells during the summer works well, but it’s harder wintertime as the largest electric demands arise during the night, when there is close to no sunlight. However, in the case of batteries, they may be helpful. Possibly by letting the solar cells charge the battery during the day and then use it to help charge the electric vehicle during the night. Unfortunately, it was not possible to include this scenario as the used software was unable to handle batteries in that way.   By completely replacing the heat source, in this case with district heating, and thus releasing available power in the transformer, turned out to be the best option. In this way, virtually all predicted amounts of electric cars could be charged with optional charging strength between 3.7 and 11 kW.   As for the T422 transformer, there is no choice but to replace it if a larger number of electric vehicles wants to start charging there. At present, it can handle a maximum of 10-20 electric vehicles that charge at the lowest power as there is only about 50 kW available there winter time. District heating cannot be applied either as the connected customers do not use electric heating. / Detta arbete har till syfte att simulera olika scenarier i ett område där samtliga fordon ersätts av elbilar i framtiden.   En tillkomst av elbilar i elnätet är inte lätt att hantera, speciellt inte om kunderna i nätet väljer att ladda med högre effekt. Vilket kan ses i resultatet i denna rapport, är flexibel förbrukning genom effektstyrning ett bra alternativ för att sänka den totala effektförbrukningen. Fast det gäller då givetvis att kunderna går med på att förbrukningen styrs på detta sätt.   Att använda solceller fungerar bra sommartid, men vintertid är det värre, då det största elbehovet uppstår på natten, när det inte är lika stor solljustillgång. I samband med batterier kan de dock vara till hjälp. Möjligen genom att låta solcellerna ladda upp batteriet under dagen och sedan använda det för att hjälpa till att ladda elbilen under natten. Dessvärre var det inte möjligt att simulera detta scenario på grund av brister i mjukvaran som användes.   Att helt ersätta värmekällan, i detta fall med fjärrvärme, och därmed frigöra effekt i transformatorn visade sig däremot vara det bästa alternativet. På så sätt kunde i stort sett samtliga mängder elbilar laddas med valfri laddningsstyrka mellan 3,7 och 11 kW.   Vad gäller transformator T422, ses inget annat val än att byta ut den om ett flertal elbilar ska börja ladda där. I nuläget klarar den av högst 10-20 elbilar som laddar på lägsta effekt eftersom det endast finns ca 50 kV tillgängligt vintertid. Fjärrvärme kan inte användas där heller som komplement då de tillkopplade kunderna inte använder elektrisk uppvärmning.

The 2008 Climate Change Act set legally-binding carbon reduction targets. Demand side management (DSM) includes energy use reduction and peak shaving and offers significant potential to reduce the amount of carbon used by the electricity grid. The demand side management (DSM) schemes that have tried to meet this challenge have been dominated by engineering-based approaches and so favour tools like automation (which aims to make shifting invisible) and pricing (which requires customer response) to shift demand. These approaches tend to focus on the tools for change and take little account of people and energy-use practices. This thesis argues that these approaches are limited and therefore unlikely to produce the level of response that will be needed in future. The thesis therefore investigates the potential for time-shifting domestic energy demand but takes a different angle by trying to understand how people use energy in their daily lives, whether this use can be shifted and some of the implications of shifting it. The centrepiece of the work is an empirical study of eleven households energy-use practices. The interdisciplinary methodology involved in-house observations, interviews, photographs, metered energy data and disruptive interventions. The data was collected in two phases. Initially, a twenty-four hour observation was carried out in each household to find out how energy was implicated in everyday practices. Next, a series of three challenges were carried out, aimed at assessing the implications of disrupting practices by time-shifting food preparation, laundry and work/ leisure. A practice theory approach is used to shift the focus of attention from appliances, tools for change, behaviour or even people, to practices. The central finding of this work is that practices were flexible. This finding is nuanced, in the light of the empirical research, by an extended discussion on the nature of practices; in particular, the relationship between practices and agency and the temporal-spatial locatedness of practices. The findings demonstrate that, in this study at least, expanding the range of demand response options was possible. The research suggests numerous possibilities for extending the potential of practices to shift in time and space, shift the energy used in practices or substitute practices for other non-energy-using practices, though there are no simple technological or behavioural fixes . More profoundly, however, the thesis concludes that infrastructures of provision , such as the electricity grid and the companies that run it, underpin and facilitate energy-use practices irrespective of the time of day and year. In this context technology-led demand response schemes may ultimately contribute to the problem they purport to solve. A more fundamental interrogation of demand and the infrastructures that serve it is therefore necessary and is almost entirely absent from the demand response debate.