Virtual Power Plant (VPP) is a concept that aggregate Distributed Energy Resources (DER) together, aims to overcome the capacity limits of single DER and the intermit-ted natural characteristics of renewable energy sources like wind and solar. The whole system can be viewed as a single large-capacity power plant from the system‘s point of view. In this project, the literature review of VPP concept, architecture, existed project and the survey of VPP in Sweden are being conducted first. Secondly, the simplified VPP model is built on MATLAB/Simulink software. The simplified system contains a wind farm, a hydro power plant, a dynamic system load and an infinite bus representing the large transmission grid. During the simulation process, the generation and consump-tion unites are running according to the real history data located in external database. In the third place, optimized control schemes for the hydro unit in VPP model to decrease its effects on transmission grid are implemented in Simulink model. At the same time, hydro turbine should be controlled in an optimized way that without large turbulence. Basically, the hydro power plant is responsible for balancing the active power between the wind farm and dynamic load. Since there is a limit for the hydro turbine output, the rest of either power shortage or surplus power need to be com-pensated by the grid. This is the fundamental control scheme, so called run time con-trol scheme. The advanced control schemes here are based on the moving average control method and forecast compensation control method. The forecast compensa-tion control method use the 24 hours ahead load forecasting data generated by Artifi-cial Neural Network. Later on, analysis of those three control schemes will be pre-sented. The last part of the project is the conclusion of the different control schemes according to comparison of their control results.

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.

The phenomenon of Virtual Power Plant (VPP) has gained increased attention in many parts of the world in recent years. In 2022 the European Union, in response to the rising energy prices as well as the ongoing Russian invasion of Ukraine, set a goal of speeding up the process of creating a digital energy system (European Commission, 2022, p. 20). VPP is the/a solution to the problem, and the EU is set to start its deployment of a common European energy data space no later than 2024 (European Commission, 2022, p. 3).  Previous academic research on VPP has been conducted on the technical aspects of the phenomenon and the adoption of VPP has not been approached from a consumer standpoint. We therefore identified a research gap, since, to the best of our knowledge, no qualitative or quantitative research has been conducted in the area of acceptance of VPP by individuals or households. We could see that there is a need for this type of research due to the goals set by the European Union, and the lack of current research. To fulfill the purpose of our study, we draw on the literatures on supplier switching in homogenous markets, innovation adoption, and technology acceptance to develop a conceptual framework and further empirically extend it via a mixed-method approach. The qualitative component of the study consists of three online on-on-one interviews, conducted with the help of a discussion guide. The interviewees selected were considered to be appropriate participants, suited for our study. The interviews gave us a deeper understanding of how VPP came across to the Swedish consumer, as well as how it was perceived by them. The quantitative study was done by the means of a survey of 75 respondents, enabling us to conduct a set of linear regressions in order to test our hypotheses.  Through our mixed-method study, we were able to develop an integrative framework, showcasing factors related to Swedish consumers’ intention to partake in VPP. We could conclude that Swedish consumers see value in VPP, and that there is curiosity related to the topic which indicates that there is an interest to explore and partake in VPP. We further discuss a range of recommendations to policy-makers and energy providers, as well as the potential contributions of VPP to the two important social aspects: sustainability and energy security.

Distributed energy sources are becoming more and more important in the German electricitynetwork. One solution to manage this growing number of distributed assets liesin the Virtual Power Plant concept. A Virtual Power Plant aggregates decentralizedgenerators and loads to behave like a large power plant. Based on new technologies, ituses advanced communication technologies to provide different services (generation ofenergy, steering of power systems, balancing services ...). This thesis proposes a mixedintegerstochastic model of a Virtual Power Plant. The participation to different productsis being studied: selling power on day-ahead basis on the spot market, providingflexibility to the secondary and tertiary reserve market. The particularity of this modelis to consider the revenue generated by the stochastic activation of the reserve market.An operational tool named AlocaBid is implemented in Python, based on the developedmathematical model. The performance of the model is being evaluated using four studycases, representing typical market situations. The results demonstrate the advantage ofthe proposed model over state-of-the-art method for bids’ allocation. / Distribuerade energik¨allor blir allt viktigare i det tyska eln¨atverket. En l¨osning f¨or atthantera det v¨axande antalet distribuerade tillg°angar ¨ar Virtual Power Plant-konceptet.Ett virtuellt kraftverk styr decentraliserade generatorer och laster f¨or att efterlikna ettnormalt kraftverk. Baserat p°a ny teknik anv¨ander det avancerad kommunikationsteknikf¨or att tillhandah°alla olika tj¨anster (generering av energi, styrning av kraftsystem, balanseringstj¨anster ...). Denna avhandling f¨oresl°ar en stokastisk blanda heltalsmodell avett virtuellt kraftverk. Deltagandet i olika produkter studeras: F¨ors¨aljning av maktp°a daglig basis p°a spotmarknaden, vilket ger flexibilitet till den sekund¨ara och terti¨arareservmarknaden. Det speciella med denna modell ¨ar att den tar h¨ansyn till de int¨aktersom genereras av den stokastiska aktiveringen av reservmarknaden. Ett operationsverktygmed namnet AlocaBid implementeras i Python, baserat p°a den utvecklade matematiskamodellen. Modellens prestanda utv¨arderas med fyra studiefall, som representerartypiska marknadssituationer. Resultaten visar f¨ordelen med den f¨oreslagna modelleframf¨or den senaste tekniken f¨or budgivningens f¨ordelning.

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.

The diploma thesis is dealing with possible approaches to control distributed energy resources and storage systems. One of these approaches is a virtual power plant and its concept is described in the first part of the thesis. The virtual power plant is a controlled system of distributed energy resources, storage systems and controllable loads interconnected via communication network, that can act as a conventional power plant. The theoretical part contains a survey of control system's topologies, a brief summary of available communication infrastructures and standards. The second part of the thesis is focused on the description of operation and control of hybrid system that represents an inseparable component of virtual power plant. A Matlab Simulink model was created for this purpose. A simulation of hybrid inverter's step response is realised to test the operation of the hybrid system and it is compared with the real measurements in the laboratory. A comparison of control approaches of hybrid system implemented on the basis of measurements is also included in this thesis and was published in the scientific paper attached in the appendix.

With increasing intermittency from renewable energy production, such as solar and wind power, the need for increased flexibility is quickly arising. The Åland Islands have an ambitious energy transition agenda with the goal of having a 100 % renewable energy system. Since there is no possibility of hydropower acting as regulatory power on Åland, reaching the goal is a challenging task. Increasing flexibility can be achieved by either implementing energy storage in the system or by matching the demand with the production.   The purpose of this study was to estimate and evaluate the technical potential of demand response (DR) on Åland, both in 2019 and for a scenario in 2030 when domestic production of wind and solar have increased. Six areas of interest were identified; electric heating, refrigeration processes, lighting, ventilation and air conditioning, electric vehicles and industries. Electricity import from Sweden to Åland was examined since high import coincides with either low domestic renewable production or high consumption. Import is therefore a good indicator for when flexibility is most required.  The results show that the technical potential of DR on Åland can lower the maximum electricity import from Sweden by 18 % in 2019. 4.3 % of the total import can be moved to times when there is less stress on the grid. Electric heating is the biggest contributor, and can by itself lower the import with three fourths of the total reduction. The domestic renewable production for 2019 is too low for DR to have an effect on the self-sufficiency. In 2030, the self-sufficiency and utilization of domestic renewable production could be increased with 4.2-9.9 % and 5.4-12 % respectively when using DR, depending on if vehicle-to-grid is implemented on a large scale or not. The cost of implementing DR is still uncertain, and varies between different resources. Nonetheless, DR in electric heating is presumably a less expensive alternative in comparison to batteries, while providing a similar service.