With the world becoming more conscious about achieving 1.5-degree scenario as promisedby the most powerful economies of the world, much needed push was received by the renewable energy technology providers.  This has led to an increased a share of energy production from renewables and a decrease in the fossil-based energy production with the overall energy production.  As a result, a large share of inertia of the system is lost and a big challenge in the name of flexibility is presented to the world of energy.  Virtual Power Plant is quite a novel and new concept to address the new generation challenge of flexibility and can offer various other benefits like competitivity,reliability, accessibility etc.  In this thesis, a commercial virtual power plant is studied by developing a mixed integer linear model to emulate the trading for short term markets with the risk mea- sures in a Nordic Electricity Framework.  Further, the developed model is implemented in a quite a new mathematical programming language known as “Julia”.  The model is implemented using a hypothetical portfolio consisting of a dispatchable unit, a battery system and a wind farm in the SE3 bidding zone of Sweden.  An investigation on varia- tion of imbalance costs in three different modes also has been carried out, to demonstratethe advantage of such a virtual power plant concept in reducing the imbalance costs. / För att uppfylla 1,5-gradersmålet som beslutats av världens ledande ekonomier har olika‌typer av förnybar energiproduktion fått ett stort uppsving. Detta har lett till ökad energiproduktion från förnybara källor och minskad energiproduktion från fossila källor. För elsystemen innebär en högre andel förnybar produktion minskad svängmassa ochökat behov av flexibilitet för att kompensera för variationen hos förnybara energikällor. Virtuella kraftverk är ett nytt koncept för att tillgodose behovet av flexibilitet och kanäven ge andra fördelar som konkurrenskraft och tillförlitlighet. I denna uppsats studeras ett virtuellt kraftverk genom att utveckla en optimeringsmodell för att emulera handeln i elmarknader med riskmått inom ett ramverk för den nordiska elmarknaden. Modellen implementeras i det nya programmeringsspråket Julia. Modellen innehåller en hypotetisk blandning av resurser bestående av ett planerbart kraftverk, ett batterisystem och en vindpark i elområdet SE3 i Sverige. Balanseringskostnaderna i tre olika modeller undersöks för att visa potentialen hos det virtuella kraftverket att minska dessa kostnader.

Chlor-alkali electrolysis indicates significant demand response potential, accounting for over 2% of Germany’s total elec-tricity demand. To fully analyze this potential, digital models or digital twins are necessary. In this study, we use the IRPopt modeling framework to develop a digital model of an electrolysis process and examine the cost-optimal load shifting application in the day-ahead spot and balancing reserve market for various price scenarios (2019, 2030, 2040). We also investigate the associated CO2 emissions. Combined optimization at both markets results in greater and more robust cost savings of 16.1% but cannibalizes the savings that are possible through optimization separately at each market. In future scenarios, the shares of savings from spot and reserve market could potentially reverse. CO2 savings between 2.5% and 9.2% appear only through optimization at the spot market and could even turn negative if optimized solely at the reserve market.

Competitive power markets from different countries exhibit a common market design, especially because of the nature of electricity (lack of storage, inelastic load, and strong seasonal effects on multiple time scales). For example, a majority of countries have created a spot market where electricity is traded hourly. The design of the spot markets reflected an ambition of providing strong incentives for efficient and least-cost production. Subsequently, the spot market price has been considered as a reference price for other existing electricity markets such as the contract market or the real-time market. However, empirical studies on electricity markets find some evidence of abnormally high markups. The literature on the electricity spot market mainly focuses on the producers' pricing decisions. The present thesis argues that quantity choices, both in terms of available as well as contracted quantities, are crucial for understanding market power in electricity markets. / Diss. Stockholm : Handelshögskolan, 2003 [4], iii, [1] s., s. 1-6: sammanfattning, s. 7-119, [5] s.: 4 uppsatser

With the deregulation of power industry and the market competition, reliable power supply and secured system operation are major concerns of the independent system operator (ISO) or decision-maker (DM). Power dispatch under deregulated environment is complicated with various possibilities of decisions involved. Without the assistance of Energy Management System (EMS), it is not easy for ISO or DM to operate with pure experiences. To enhance the operational efficiency, EMS involves the state-of-the-art control technology, and the fast and effective computer assisted decision support system will help dispatch the power. A conventional EMS has a few major tasks, among them, the ¡§network analysis¡¨ task and the ¡§forecast and scheduling¡¨ task are the most important in assisting the on-line power dispatch. In dealing with the new deregulated environment, an ¡§operational planning¡¨ has to be added to aid the EMS for more security. There are significant changes on EMS after deregulation. This dissertation will focus on the changes and new functions, in the ¡§network analysis¡¨ and the ¡§forecast and scheduling¡¨ tasks of an EMS, which supports the operation in the competitive environment. In the ¡§network analysis¡¨ task, we discuss the real and reactive power dispatch and congestion management with AC optimal power flow (OPF). In this task, the formulation of AC OPF with deregulation issues and the effect of flexible AC transmission systems (FACTS) devices are presented. A predictor-corrector interior-point nonlinear-programming (PCIPNLP) algorithm has been developed to solve the problem. The model involves only slight modification to the present OPF for social welfare maximization to obtain the optimized bid-based dispatch and nodal spot prices. The incorporation of FACTS devices for system operations can ease the difficulties caused by transmission congestion. It is found that PCIPNLP technique is very effective for the modified OPF solution for congestion relief under deregulation. In the ¡§forecast and scheduling¡¨ task, we discuss the resource scheduling for bid-based dynamic economic dispatch and spot dispatch for power and reserve. They can be formulated for social welfare maximizing problem that is solved by using an efficient interior point method. And the optimal resource allocation and nodal spot price can be given from the various test results. We have also proposed a fuzzy based strategic gaming method to determine the GenCo¡¦s bidding strategy. Based on fuzzy set theory, a multi-criteria decision-making method is used to obtain the optimal strategy combination, bids and expected payoffs. Decision maker can find the optimal strategy combination by using weight vector to represent his subjective attitude about the structure of multi-objectives. The advantages have also been demonstrated through the numerical examples. Compared with the classical (¡§nonfuzzy¡¨) game theory, the proposed approach could help the decision maker to obtain higher expected payoffs, and make his choices easily. Possible applications of the proposed fuzzy method can be suggested for other decision-making problems in the power systems

In the aftermath of the liberalization of European Energy Markets in the 2000s, Power Exchange platforms have constantly evolved towards more integrated and competitive designs, where quality forecasts and effective optimization strategies play decisive roles. This study presents the development of a hydropower scheduling optimization algorithm for the Day-Ahead spot market using Mixed Integer Linear Programming (MILP). This work was supported by the hydro asset management team of ENGIE Global Energy Markets (GEM) located in Brussels.  The model developed is focusing on the optimization of Coindre Hydraulic Power Plant (HPP), located in the highlands of Massif Central in France. With the combined water discharge of its two interconnected reservoirs, Grande-Rhue and Petite-Rhue, the powerhouse can reach up to 36 MW of power output capacity. The two reservoirs are located kilometres apart from each other and have different storage capacities and catchment areas. The reservoirs naturally exchange water due to the level difference along an interconnection pipe. Maximum power output is limited by water level differences in both reservoirs, which makes modelling complicated. These operational constraints are a limiting factor in terms of operability, as a result the scheduling process is a non-trivial task and is time-consuming.  A framing study of the power plant was conducted over a hydraulic year to identify the governing parameters of the model. The multi-reservoir nature of the optimization problem oriented the model development towards a Mixed Integer Linear Formulation. After experimenting with different solvers, Gurobi 28.1.0 was chosen for its performance in the Branch and Cut Algorithm for the power scheduling task.  The performance of the new model has been validated by re-running the model on past production plans, results show that reservoir volume errors are less than 5% of their respective capacities on a 5 days’ time-horizon. After backtesting it was found that the new optimization strategy results in higher revenue for the plant due to the optimized operation at higher average energy prices. The results also bring out the importance of proper valve actuation in the optimization strategy, as well as the need for future studies. / Till följd av liberaliseringen av de europeiska energimarknaderna under 2000-talet har energiföretagen och elbörserna ständigt utvecklats mot mer integrerade och konkurrenskraftiga lösningar, där kvalitetsprognoser och effektiva optimeringsstrategier spelar avgörande roller. Detta examensarbete presenterar utvecklingen av en algoritm för optimering av vattenkraftplaneringen på Day-Ahead elmarknaden med hjälp av en matematisk modell av typen Mixed Integer Linear Programming (MILP). Arbetet initierades av och utfördes hos ENGIE Global Energy Markets (GEM) i Bryssel.  Modellen som utvecklats är tänkt att optimera Coindre vattenkraftverk, som ligger på höglandet inom Massif Central i Frankrike. Med det kombinerade vattenutsläppet från dess två fördämningar, Grande-Rhue och Petite-Rhue, kan kraftverket leverera upp till 36 MW el netto till elnätet. Vattenreservoarerna ligger flertalet kilometer ifrån varandra och har mycket olika kapacitet och upptagningsområden. Båda reservoarerna är kopplade till varandra genom det gemensamma tilloppsröret till kraftverket, där en reglerventil finns endast vid Petite-Rhue. Vatten kan växlas naturligt mellan de två dammarna när ventilen är öppen på grund av skillnaden i varderas vattennivå. Den maximala effekten från kraftverket är begränsad av vattennivåerna i båda reservoarerna vilket gör optimeringsmodelleringen komplicerad. Dessa operationella begränsningar är mycket hindrande vad gäller valet av driftsregim, eftersom kalkylering av driftsplaneringen blir en svår och tidskrävande uppgift.  En ramstudie av vattenkraftverket genomfördes under ett typiskt hydrauliskt år för att identifiera modellens styrparametrar. Den möjliga vattenöverföringen mellan de två dammarna orienterade modellutvecklingen mot en Mixed Integer Linear Programming (MILP) formulering. Efter att ha experimenterat med olika kalkylverktyg valdes Gurobi 28.1.0 för sin bra prestation i lösningen av Branch and Cut-algoritmen.  Systemets hydraulik har validerats genom att injicera realiserade produktionsplaner som input till modellen. Resultaten visar att volymfelet är mindre än 5% av deras respektive kapacitet under en 5-dagars tidshorisont. Efter tvärstester mot historiska data konstaterades det att den nya optimeringsstrategin resulterar i bättre genomsnittliga elpriser på varje kWh inmatad till nätet och högre intäkter för kraftverket. Resultaten visar också på vikten av korrekt ventilmanövrering i optimeringsstrategin.  Modellen körs i rimliga beräkningstider och redan används i den dagliga optimeringen av Coindre kraftverket, vilket sparar mycket tid. Specifika exempel på den optimerade prestandan och framtida förbättringar hittas i slutet av denna rapport.

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.

Text in English with summaries in English and Afrikaans / The introduction of single stock futures to a market presents the opportunity to assess an individual company's response to futures trading directly, in contrast to the market-wide impact obtained from index futures studies. Thirty-eight South African companies were evaluated in terms of a possible price, volume, and volatility effect due to the initial trading of their respective single stock futures contracts. An event study revealed that SSF trading had little impact on the underlying share prices. A normalised volume comparison pre to post SSF trading showed a general increase in spot market trading volumes. The volatility effect was the main focus of this study with a GARCH(1,1) model establishing a volatility structure (pattern of behaviour) per company. Results showed a reduction in the level and changes in the structure of spot market volatility. In addition, a dummy variable regression could find no evidence of an altered company-market relationship (systematic risk) post futures. / Business Management / M.Com. (Business Management)

Text in English with summaries in English and Afrikaans / The introduction of single stock futures to a market presents the opportunity to assess an individual company's response to futures trading directly, in contrast to the market-wide impact obtained from index futures studies. Thirty-eight South African companies were evaluated in terms of a possible price, volume, and volatility effect due to the initial trading of their respective single stock futures contracts. An event study revealed that SSF trading had little impact on the underlying share prices. A normalised volume comparison pre to post SSF trading showed a general increase in spot market trading volumes. The volatility effect was the main focus of this study with a GARCH(1,1) model establishing a volatility structure (pattern of behaviour) per company. Results showed a reduction in the level and changes in the structure of spot market volatility. In addition, a dummy variable regression could find no evidence of an altered company-market relationship (systematic risk) post futures. / Business Management / M.Com. (Business Management)

This thesis describes possibilities of electricity trading. The thesis deals with subjects at the electricity market, defines their competences, obligations and relationships among these subjects. Trading places and their advantages and disadvantages are also described in the thesis. The thesis shows composition of the electricity price and informs about its partial components. Types of ancillary services are spoken and there is also comparison between selling wholesale electricity and providing ancillary services. An influence of primary fuels and emission allowances on the electricity price is included at the end of the thesis.

Die Arbeit widmet sich dem Börsenstromhandel, insbesondere dem Einfluss von erneuerbaren Energien (EE) auf das Zustandekommen von Marktpreisen aus Spotgeschäften. Dabei werden zwei Kernfragen aufgegriffen: 1) welche kurz- und langfristige Relevanz besitzt das Spektrum der erneuerbaren Energien für die Preisentwicklung an Strombörsen im europäischen und speziell im deutschen Markt? 2) Wie kann diese Bedeutung quantifiziert werden? Dazu werden ökonometrische Ansätze zur Abbildung und Prognose der Einflussnahme von EE auf Marktpreise entwickelt. Festgestellt wird, dass Marktpreise dezidiert in direkter Weise – durch die Netzeinspeisung bestimmter EE-Mengen – und in indirekter Weise – mittels Änderungen an EE betreffender Gesetze – beeinflusst werden und sich so das Preisniveau langfristig senkt. Zudem geben die Ergebnisse Grund zur Annahme, dass die Relevanz von Strom aus erneuerbaren Quellen auf Strombörsen sogar noch steigen wird. Derweil haben sich Strombörsen in der Wertschöpfungskette von europäischen Strommärkten etabliert, so dass zu erwarten ist, dass sie auch künftig einen entscheidenden Beitrag zur Funktionsfähigkeit dieser Märkte leisten.:Kapitel 1: Einleitung Kapitel 2: Grundlagen zum Energiehandel und erneuerbaren Energien Kapitel 3: Zugrunde liegende neoinstitutionenökonomische Theorieansätze Kapitel 4: Schätzung von Marktpreisen mit GARCH-Ansätzen Kapitel 5: Transformationsansätze zur Prognose von Strompreisen Kapitel 6: Einfluss von Regulierung auf Strompreise Kapitel 7: Das Negativstrompreisphänomen Kapitel 8: Schlussbetrachtung und Ausblick Anhang Literaturverzeichnis