With increasing penetration of intermittent resources such as wind and solar, power system operations are facing much more challenges in cost effective provision of energy balancing and frequency regulation services. Enabled by advances in sensing, control and communication, the concept of Virtual Power Plant (VPP) is proposed as one possible solution which aggregates and firms up spatially distributed resources? net power injection to the system. This thesis proposes a coordinated control and bidding strategy for VPPs to provide energy balancing and grid frequency regulation services in electricity market environment. In this thesis, the VPP consists of two energy conversion assets: a Doubly Fed Induction Generator (DFIG)-based wind farm and a co-located Flywheel Energy Storage System (FESS). The coordination of the VPP is implemented through power electronics?based controllers. A five-bus system test case demonstrates the technical feasibility of VPPs to respond to grid frequency deviation as well as to follow energy dispatch signals. To enable the participation of VPPs in electricity market, this thesis also proposes an optimization based bidding strategy for VPPs in both energy balancing and frequency regulation service markets. The potential economic benefits of this bidding strategy are demonstrated under Denmark wholesale electricity market structure. Four case studies show the economic benefit of coordinating VPPs.

This thesis is a feasibility study of avirtual power plant (VPP) in centralSweden and part of a project withInnoEnergy Instinct and STRI. The VPPconsists of a wind park, small hydroplant as well as solar photovoltaic andenergy storage. The 50 kVsubtransmission network was modeled inorder to evaluate the network servicesthat could be provided by coordinatingexisting distributed energy resources inthe network. Simulations where performedusing measured hourly variations inproduction and consumption of allnetwork nodes. The studied networkservices included both reactive andactive power control.The aim of this thesis is to evaluatethe potential contribution from the VPPfor capacity firming in order to allow abalance responsible party to meet placedbids on the day-ahead spot market,minimize peak load in order to reducesubscribed power, decrease networklosses, the contribution from reactivepower control using the power convertersis studied. Comparisons of the economicgains from spot and balance markets ofthe VPP distributed energy resources aremade for each operation case.Sponsor: InnoEnergy / InnoEnergy Instinct

We discuss a model of a virtual power plant (VPP) that provides market access to privately-owned distributed generations (DGs). The VPP serves passive loads, processes bids from generators, and trades in the wholesale market. The generators can be renewable or thermal, and they act strategically to maximize their own profit. The VPP establishes the rules of the internal market to minimize the cost of energy and the cost of balancing while ensuring generator participation and load balancing. We derive a heuristic mechanism for internal market and propose a dynamic programming approach for minimizing the VPP cost. We present illustrative simulations for both single and multistage market bidding and then compare the resulting performance to the centralized VPP model, where the DGs are assumed to be owned by the VPP. We show that the proposed design incentivizes the DG agents to behave the same as in the centralized case, but the optimal cost paid by VPP is higher due to the payments to the DG owners.

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.

In this study, an examination regarding what benefits an aggregatedpopulation of Battery Energy Storage Systems (BESSs) could result incompared to when the individual units in the population are being usedseparately has been executed. The increased flexibility and reducedsafety margins as results of the aggregation was also examined. Thestudy was executed on behalf of the smart energy service companyCheckWatt AB and the study furthermore rests upon results of earlierperformed master theses on behalf of the company. By investigating previous work and studies through a literature study,the enabling of anumerical study was done. The numerical study wasbased on a simple model of a Virtual Power Plant (VPP) where severalBESSs are smartly controlled in order to be used for both local peakshaving and as common providers of the frequency reserve FrequencyContainment Reserve - Normal (FCR-N). The study involved the formation of a numerical model which simulated cases of both aggregated and non-aggregated populations of up to 45 load profile units, this in order for advantages and differences to be distinguished. The data used inthe simulations was received mainly from the CheckWatt AB andconsisted of photovoltaic (PV) electricity production and load data of 45 customers of the company. A sensibility analysis of the numericalstudy was also performed, which showed that the studied model andsystem were quite stable. The results of the simulations of the case of the study proved thatthere are some advantages connected to aggregation of several BESSs,and that the aggregation enabled an added value and a higher level offlexibility within the system. The safety margins connected todelivery of FCR-N could be reduced when aggregating several BESS,while a more extensive study is requested regarding safety marginsconnected to peak shaving. The study’s results further showed that anaggregator can be used as a sustainable and flexible solution forbalancing the electrical grid in the transition to a sustainableenergy system allowing a higher penetration of intermittentenergy sources.

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.

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.