No / The current global challenge of climate change has made renewable energy usage very important. There is an ongoing drive for the deployment of renewable energy resource at the domestic level through feed-in tariff, etc. However the intermittent nature of renewable energy has made storage a key priority. In this work, a community having a solar farm with energy storage embedded in the house of the energy consumers is considered. Consumers within the community are aggregated in to a local virtual power plant. Genetic algorithm was used to develop an optimized energy transaction for the virtual power plant. The results shows that it is feasible to have a virtual power plant setup in a local community that involve the use of renewable generation and embedded storage. The result also show that when maximization of battery state of charge is considered as part of an optimization problem in a day ahead market, certain trade-off would have to be made on the profit of the virtual power plant, the incentive of the prosumer, as well as the provision of peak service to the grid.

Yes / Technological advancement on the electricity grid has focused on maximizing its use. This has led to the introduction of energy storage. Energy storage could be used to provide both peak and off-peak services to the grid. Recent work on the use of small units of energy storage like battery has proposed the vehicle to grid system. It is propose in this work to have energy storage device embedded inside the house of the energy consumer. In such a system, consumers with battery energy storage can be aggregated in to a community virtual power plant. In this paper, an optimized energy resource allocation algorithm is presented for a virtual power plant using genetic algorithm. The results show that it is critical to have a pricing scheme that help achieve goals for grid, virtual power plant, and consumers. / Mr. Oghenovo Okpako is grateful to the Niger Delta Development Commission of Nigeria for funding the work. The work has been also supported by the British Council and the UK Department of Business innovations and Skills under the GII funding of the SITARA project.

Yes / Recently, significant advances in renewable energy generation have made it possible to consider consumers as prosumers. However, with increase in embedded generation, storage of electrical energy in batteries, flywheels and supercapacitors has become important so as to better utilize the existing grid by helping smooth the peaks and troughs of renewable electricity generation, and also of demand. This has led to the possibility of controlling the times when stored energy from these storage units is fed back to the grid. In this paper we look at how energy resource sharing is achieved if these storage units are part of a virtual power plant. In a virtual power plant, these storage units become energy resources that need to be optimally scheduled over time so as to benefit both prosumer and the grid supplier. In this paper, a smart energy resources allocation algorithm is presented for a virtual power plants using genetic algorithms. It is also proposed that the cause of battery depreciation be accounted for in the allocation of discharge rates. The algorithm was tested under various pricing scenarios, depreciation cost, as well as constraint. The results are presented and discussed. Conclusions were drawn, and suggestion for further work was made. / Mr. Oghenovo Okpako is grateful for the support of the Niger Delta Development Commission of Nigeria for supporting the work. The work has been also supported by the British Council and the UK Department of Business innovations and Skills under the GII funding of the SITARA project.

One feature that is hoped for in the smart grid is the participation of energy prosumers in a power market through demand response program. In this work, we consider a third-party virtual power plant (VPP) that has “real-time” control over a number of prosumers’ storage units within an envisaged free market. Typically, a VPP with domestic energy storage will involve a bidirectional flow of energy, where energy can either flow from the grid to the prosumers’ battery or from the prosumers’ battery to the grid. Such a system requires prices to be set correctly in order to meet the market objectives of all the VPP stakeholders (VPP Aggregator, prosumers, and grid). Previous work has shown how VPPs could operate, and the benefits of using energy storage, coupled with pricing, in terms of reducing energy cost for stakeholders and providing the grid with its required load shape. The published work either assumes prices or costs or then optimises for least cost within the grid parameters i.e. losses, voltage limits, etc. However, the setting of prices in such a way that energy can be traded among VPP stakeholders that satisfies all stakeholders’ objectives has not been fully explored in the literature, particularly with real-time VPP aggregators. In this thesis, we present novel strategies for evaluating and setting the prices of a community VPP with domestic storage based on the bidirectional flow of energy through the VPP aggregator between the grid and the prosumers that mutually meet all VPP stakeholders’ objectives. This showed that depending on pricing and the VPP objectives, demand-side management could be attractive. However, the effect on the grid in terms of the load was not what was desired. A new performance index called the “Cumulative Performance Index” CPI is proposed to measure the VPP’s performance. Using the CPI, it was possible to compare and contrast between the VPP technical performance and its business case for stakeholders. Optimizing with respect to the grid’s requirement for DSM from the VPP, it was possible to achieve a CPI of 100%. This work was implemented using a novel approach on a genetic algorithm platform. / Niger Delta Development Commission of Nigeria

This thesis concerns with design of micro sources and their implementation in Micro grid system. In the first part the work is aimed at definition of smart - grid, where describes their advantages, disadvantages and necessary changes, which has to be made in current distribution network for implementation this system. Further on the thesis concerns with detailed description of Micro grid, configuration of this kind of network, the issues in implementation and possibilities to provide ancillary services. The work also describes marginally virtual power plants, presents definition, components and types of virtual power plants. The final chapter describes the creation of micro sources in System modeler and subsequent testing of consumption cover to operate in island mode.

The current shift towards renewable energy resources creates volatility in the electricity production that must be compensated by nevi sources of balancing energy. To ensure a normal operation of the power system, the transmission system operators procure power reserves able to provide regulation energy through market processes. Virtual power plants are now likely to participate on the balancing markets. In this study, the technical and economic feasibility of having virtual power plants participate in the Swiss balancing market is assessed. The study begins with the evaluation and compa.rison of four European balancing market designs and continues with the clarification of the concept of virtual power plant. The focus is then set on the Swiss ancillary services market, recently open to virtual pmver plants. After a detailed market description, an economic model simulating the participation of a virtual power plant made of industrial resources on the secondary and tertiary control markets has been developed. This model \Vas evaluated on an actual market design: the Sv.riss ancillary servicel:l market. 5 cases were simulated, allowing to estimate the opportunity fom both the capacity and the energy market productl:l. The simulations indicated that an example company (based on an actual situation) could hope a decrease in its energy cost between :3 and 4% by participating in a control pool over a year. Other simulations demonstrated the greater profit expected from secondary reserves compared to tertiary rel:lerves, and the need to develop an automatized activation system. The encouraging economic study is followed by a technical overview of the envisioned system. A generic technical characterization of virtual power plant is presented, on v.rhich the Swiss use-case is later applied. The breakdown into functional requirements allowed to highlight specific issues. The design of the control strategy, particularly to deliver secondary control, as well as the hardware communication interface to use are tvw aspects that ,vill require further analysis. Additionally, on an economic level, the investment cost for remote communication modules are acceptable with respect to the economic potentials estimated in the first part, for medium­sized industrial energy resources. In conclusion, the study established the profitability of an aggregation project on the Swisl:l market but also demonstrated the need to pursue research for the project to be fully feasible on a technical level.

Virtual Power Plants (VPPs) are an emerging form of technology that allows owners of electricity producing appliances, such as electric vehicles, to partake in a pool of producers of sustainable energy. The Swedish electricity grid owner Svenska Kraftnät hosts a platform where VPPs act as intermediaries between energy producing customers and third party buyers. A requirement to participate in these transactions, however, is to post a bid specifying the amount of power that can be produced from a VPP during a given hour at least 48 hours into the future. This is where forecasting comes into the picture. This report compares the accuracy of eight different machine learning models when tasked with forecasting power output using the same training data from an electric vehicle-based VPP. The study also examines which inferences about customer behavior can be drawn from the same data and give strategic recommendations to VPPs based on the findings of the study. Upon evaluating the results, it was found that deep learning models outperformed autoregressive models, which in turn outperformed Random Forest Regression and Support Vector Regression. As for customer behaviors found in the data, a small negative correlation between spot prices and delivered output was found, suggesting that customers limit their charging when spot prices are high. Further, more power is generally produced during nighttime and on weekends. The data also shows an autocorrelation with a lag of 24 hours, suggesting that charging behaviors on a given day influence charging behaviors the subsequent day. / Virtuella kraftverk (VPPs) är en framväxande form av teknologi som tillåter ägare av elproducerande enheter, till exempel elbilar, att delta i ett nätverk av producenter av hållbar energi. Den svenska elnätsägaren Svenska Kraftnät driver en plattform där VPPs agerar mellanhänder mellan energiproducerande kunder och tredjepartsköpare. Ett krav för att delta i budgivningen är dock att som VPP kunna lägga ett bud som specificerar hur stor effekt som kan produceras under en viss timme, minst 48 timmar i framtiden. Här kommer prognoser in i bilden. Denna rapport jämför precisionen för åtta olika maskininlärningsmodeller som har i uppgift att predicera effektproduktion med hjälp av samma data från ett elbilsbaserat VPP. Denna studie undersöker också vilka slutsatser som kan dras angående kundbeteenden från given data och ger strategiska rekommendationer baserat på studiens resultat. Efter utvärdering av resultaten kunde det konstateras att Deep Learning-modeller överträffade autoregressiva modeller, som i sin tur överträffade Random Forest Regression och Support Vector Regression. Vad gäller kundbeteenden i given data, kan sägas att en låg negativ korrelation fanns mellan spotpriser och effektproduktion, vilket tyder på att kunder begränsar laddning av elbilar när spotpriserna är höga. Vidare kan sägas att mer effekt generellt sett produceras på kvällar och helger. Studiens data visar också på en autokorrelation med en eftersläpning (lag) på 24 timmar, vilket tyder på att laddningsmönster under en given dag influerar laddningsmönster under nästkommande dag.

Στο πρώτο κεφάλαιο, γίνεται μία αναφορά στις ανανεώσιμες πηγές ενέργειας και αναλύεται περισσότερο η αιολική. Αναφέρεται η πορεία αξιοποίησής της, και παραθέτονται πληροφορίες για την τωρινή χρήση της στην παραγωγή ηλεκτρικής ενέργειας αλλά και μελλοντικές βλέψεις. Στο δεύτερο κεφάλαιο παρουσιάζονται τα χαρακτηριστικά του ανέμου και οι εξισώσεις της ανεμογεννήτριας που μας επιτρέπουν να απομαστεύουμε ενέργεια από τον άνεμο μέσω των ανεμογεννητριών. Στο τρίτο κεφάλαιο παρουσιάζονται τα δομικά στοιχεία και ο τρόπος με τον οποίο γίνεται η κατηγοριοποίηση των ανεμογεννητριών, οι έλεγχοι που χρησιμοποιούνται και τα είδη των ανεμογεννητριών που χρησιμοποιούνται σήμερα στη βιομηχανία. Στο τέταρτο κεφάλαιο παρουσιάζονται οι τεχνικές απαιτήσεις για τους αιολικούς σταθμούς στο ελληνικό Σ.Η.Ε. Στο πέμπτο κεφάλαιο, γίνεται η προσομοίωση μέσω του προγράμματος Matlab - Simulink ενός μη γραμμικού ελέγχου ισχύος ανεμογεννητριών DFIG για ενσωμάτωση σε εικονικούς σταθμού ισχύος (V.P.P). / In the first chapter, there is a general description about renewable energy resources and more specific, about the wind energy. We present the current worldwide electrical power production and the future requirements for electrical power production in Europe and Greece. In the second chapter, we study the features of the wind performance and the equations that allows us to drain energy from the wind ,using a wind turbine. The third chapter presents the components, the kinds of control and the categories of wind turbines that are in use in industry nowadays. The fourth chapter presents the technical requirements for the wind farms in the Greek System of Electrical Energy. In the fifth chapter we use the program Matlab - Simulink in order to simulate a non-linear direct power control of DFIG wind turbines for Virtual Power Plant (V.P.P.) integration.

Les politiques entreprises dans le domaine de la production d’électricité pour lutter contre le changement climatique reposent communément sur le remplacement des moyens de production fossiles et centralisés par de nouveaux moyens de type renouvelables. Ces énergies renouvelables sont en grande partie distribuées dans les réseaux moyenne et basse tension et sont le plus souvent intermittentes (énergies éolienne et photovoltaïque principalement). Les gestionnaires de réseaux s’attentent à ce que ce changement de paradigme induise des difficultés conséquences dans leurs opérations. Les mondes de la recherche et de l’industrie se sont ainsi structurés depuis le milieu des années 2000 afin d’apporter une réponse aux problèmes anticipés. Cette réponse passe notamment par le déploiement de technologies de l’information et de la communication (TIC) dans les réseaux électriques, des centres de contrôle jusqu’au sein même des moyens de production distribués. C’est ce que l’on appelle le Smart Grid. Parmi le champ des possibles du Smart Grid, ces travaux de thèses se sont en particulier attachés à apporter une réponse aux enjeux de stabilité en fréquence du système électrique, mise en danger par la réduction anticipée de l’inertie des systèmes électriques et la raréfaction des moyens de fourniture de réserve primaire (FCR), auxquels incombent le maintien de la fréquence en temps réel. En vue de suppléer les moyens de fourniture de réserve conventionnels et centralisés, il a ainsi été élaboré un concept de coordination de charges électriques délestables distribuées, qui se déconnectent et se reconnectent de manière autonome sur le réseau au gré des variations de fréquence mesurées sur site. Ces modulations de puissance répondent à un schéma préétabli qui dépend de la consommation électrique effective de chacune des charges. Ces travaux ont été complétés d’une étude technico-économique visant à réutiliser cette infrastructure de coordination de charges délestables pour la fourniture de services systèmes ou de produits de gros complémentaires. Ce travail de thèse réalisée au sein des équipes innovation de Schneider Electric et du laboratoire de Génie Electrique de Grenoble (G2Elab), est en lien avec les projets Européens EvolvDSO et Dream, financés dans le cadre du programme FP7 de la Commission Européenne. / Climate change mitigation policies in the power generation industry lead commonly on the replacement of bulk generation assets by Renewable Energy Resources (RES-E). Such RES-E are largely distributed among the medium and low voltage grids and most of them are intermittent like photovoltaic and wind power. System Operators expect that such new power system paradigm induces significant complications in their operations. The communities of research and industry started thus to structure themselves in the mid-2000s in order to respond to these coming issues, notably through the deployment of Information and Communication Technology (ICT) in power systems assets, from the Network Operations Centers (NOCs) down to Distributed Energy Resources (DERs) units. This is the Smart Grid. Among the range of possibilities of the Smart Grid, this Ph.D work aims in priority to provide a solution to handle the issue of frequency stability of the power system that are endangered by the combined loss of inertia of the power system and the phasing-out of conventional assets which used to be in charge of the maintain of the frequency in real time through the supply of Frequency Containment Reserve (FCR). The concept developed lead on a process of coordinated modulation of the level of loads of DERs, whose evolve depending on the system frequency measured in real time on-site. The strategy of modulation of each DER follows a pattern which is determined at the scale of the portfolio of aggregation of the DER, depending on the effective level of load of the DER at normal frequency (i.e. 50Hz in Europe). This work is completed by a cost benefit analysis that assesses the opportunity of sharing of the previous infrastructure of coordinated modulation of DERs for the supply of ancillary services and wholesale products. This thesis conducted within Schneider Electric’s Innovation teams and Grenoble Electrical Engineering Laboratory (G2Elab) is linked with the European projects Dream and EvolvDSO, and funded under European Commission’s FP7 program.

本研究針對先進國家「用戶群代表」制度之政策與法規進行探討，並進一步探討如何施行於台灣電力市場。首先定義並解釋「用戶群代表」涵意後，整理出先進國家(包含美國、歐盟、德國、澳洲、韓國五個地區與EnerNOC、Comverge、CPower、OhmConnect四個公司)的用戶群代表商業模式案例，藉由文獻分析與個案研究，觀察先進國家政策方向與用戶群代表市場定位差異。同時，本研究由我國用戶群代表相關制度法規，探討用戶群代表於我國電力市場實施之適法性。此外，本研究根據文獻回顧整理出發展用戶群代表制度的關鍵成功因素，並詳細探討我國當前條件是否適合發展。最後針對政府與台電、產業界、學術界、電力用戶的不同角度，提出可行的政策法規建議。 / This thesis explores the policies and regulations of aggregator systems in advanced countries and explores how to implement aggregator system in Taiwan electricity market. In order to achieve this objective, we first define and elaborate the meanings of aggregator. Then, experience and case studies of USA, European Union, Germany, Australia and Korea are studied. In addition, business models of four aggregators, EnerNOC, Comverge, CPower and OhmConnect are presented. Furthermore, we examine current related regulations of an aggregator in Taiwan electricity market for feasibility analysis. In addition, this study summarizes the key success factors of the development of aggregator systems according to the literature review, and discusses in detail whether Taiwan's current conditions are suitable for development. Finally, market models and policy regulations in relation to the aggregator are recommended.