A chance-constrained approach for electric vehicle aggregator participation in the reserve market

As recorrentes preocupações ambientais têm levado a que se verifiquem alterações nos sistemas de energia, sendo que a aposta em sistemas distribuídos é já uma realidade, contudo a aposta em energia renovável está, normalmente, associada a intermitência no que diz respeito ao aproveitamento de energia proveniente do sol, vento, ondas, etc. Assim, neste paradigma, surgem os veículos elétricos que fazem parte do sistema e têm boas perspetivas de verem a sua penetração a aumentar exponencialmente num futuro próximo, pelo que devem ser estudadas novas formas de relação entre este recurso e os agentes de mercado. Neste momento, já é possível carregar e descarregar os veículos elétricos, o que, auxiliado pelas decisões e algoritmos corretos, pode contribuir com um apoio fundamental para a rede de energia tratar de forma simplificada congestionamentos e variações nos valores nominais de tensão e frequência. Tudo isto, está dependente da disponibilidade do proprietário do veículo para fornecer este tipo de serviço e que estados mínimos de carga sejam assegurados para as viagens diárias. Geralmente, os operadores da rede elétrica gerem elevados níveis de geração e carga, pelo que surge a necessidade do conceito de agregador de veículos elétricos, que terá a função de juntar vários veículos elétricos para assim corresponder de forma mais eficaz e com capacidade de oferta conforme as necessidades da rede.Neste trabalho, pretende-se otimizar o lucro do agregador, que poderá estar sujeito a penalidades em caso de falha no fornecimento de reserva a subir ou a descer, não colocando de parte a fiabilidade no fornecimento do serviço ao mercado de reserva. Deste modo, são utilizadas técnicas de otimização estocástica que pretendem modelar incertezas de uma pequena frota de veículos elétricos como disponibilidade para fornecer o serviço e perfis de consumo. A técnica de otimização chance-constrained, mais precisamente as relaxações Big-M e McCormick, são aplicadas a fim de analisar o risco da oferta que o agregador deve submeter em mercado.Para situações de mercado real, mais precisamente o FCR-N na Dinamarca, são explorados diversos cenários para diferentes níveis de risco submetidos em mercado, diferentes probabilidades de o veículo estar conectado à redeThe recurring environmental concerns have led to changes in energy systems, and the investment in distributed systems is in progress, however, the investment in renewable energy is usually associated with intermittent with regard to the use of energy from the sun, wind, waves, etc. Thus, within this scope, electric vehicles that are part of the system rises and stand good chances of seeing their penetration increase significantly in the near future, so new forms of relationship between this resource and the market agents should be addressed. At this point, it is already possible to charge and discharge electric vehicles, which, aided by correct decisions and algorithms, can contribute with a fundamental support for the energy network to deal in a simplified way with congestion and fluctuations in voltage and frequency. It all depends on the willingness of the vehicle owner to provide this type of service and that minimum states of charge are ensured for the daily trips. In general, electricity grid operators manage high power generation and load capacities, so there is a demand for the concept of electric vehicle aggregator, which will have the function to bring together several electric vehicles to correspond more effectively and with supply capacity according to the requirements of the grid.The aim of this work is to optimise the profit of the aggregator, which may be subject to penalties in the event of a failure in the provision of reserve upward or downward, regardless of the reliability in the provision of the service to the reserve market. Therefore, stochastic optimization techniques are used to model uncertainties of a small fleet of electric vehicles as availability to provide the service and consumption profiles. The optimization technique chance-constrained, namely Big-M and McCormick the relaxation methods, are applied in order to analyze the risk the aggregator must submit in the market. For real market cases, specifically the FCR-N in Denmark, several scenarios are analyzed for different levels of risk submitted in the market, different probabilities of the vehicle being connected to the grid

Participation of an EV aggregator in the reserve market through chance-constrained optimization

The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a failure in the provision of upward or downward reserve. Therefore, stochastic and chance-constrained programming are used to handle the uncertainty of a small fleet of EVs and the risk profile of the EV aggregator. Two different relaxation approaches, i.e., Big-M and McCormick, of the chance-constrained model are tested and validated for different number of scenarios and risk levels, based on an actual test case in Denmark with actual driving patterns. As a final remark, the McCormick relaxation presents better performance when the uncertainty budget increases, which is appropriated for large-scale problems. Document type: Articl

The Effects of Battery Storage on Risk and Cost of Capital of Wind Park Investments

To reach the defined reduction goals for green house gas emissions, an increasing share of renewables and especially wind power is necessary. However, these generation technologies are intermittent and progressively exposed to market risks as a consequence of declining financial support in the future. To reduce revenue volatility, in this thesis, a wind farm is combined with a battery storage. The study emphasizes the battery’s effect on the investment risk and the accompanying cost of capital. In order to assess this effect, I develop a deterministic optimization model based on historic wind farm and market price data in order to maximize cash flows. Monte Carlo scenarios are generated to evaluate the impact on risk by using the Value-at-Risk as risk criterion. I find that batteries can indeed reduce revenue risk in a case without subsidies. Furthermore, the link to cost of capital is made. The latter, as well as the battery prices, need to be reduced by a certain amount to make the application of a battery economically reasonable. To reach the defined reduction goals for green house gas emissions, an increasing share of renewables and especially wind power is necessary. However, these generation technologies are intermittent and progressively exposed to market risks as a consequence of declining financial support in the future. To reduce revenue volatility, in this thesis, a wind farm is combined with a battery storage. The study emphasizes the battery’s effect on the investment risk and the accompanying cost of capital. In order to assess this effect, I develop a deterministic optimization model based on historic wind farm and market price data in order to maximize cash flows. Monte Carlo scenarios are generated to evaluate the impact on risk by using the Value-at-Risk as risk criterion. I find that batteries can indeed reduce revenue risk in a case without subsidies. Furthermore, the link to cost of capital is made. The latter, as well as the battery prices, need to be reduced by a certain amount to make the application of a battery economically reasonable.  Keywords: Renewable energy, Energy markets, Battery storage, Wind investment, Energy investment ris

Virtual power plant models and electricity markets - A review

In recent years, the integration of distributed generation in power systems has been accompanied by new facility operations strategies. Thus, it has become increasingly important to enhance management capabilities regarding the aggregation of distributed electricity production and demand through different types of virtual power plants (VPPs). It is also important to exploit their ability to participate in electricity markets to maximize operating profits. This review article focuses on the classification and in-depth analysis of recent studies that propose VPP models including interactions with different types of energy markets. This classification is formulated according to the most important aspects to be considered for these VPPs. These include the formulation of the model, techniques for solving mathematical problems, participation in different types of markets, and the applicability of the proposed models to real case studies. From the analysis of the studies, it is concluded that the most recent models tend to be more complete and realistic in addition to featuring greater diversity in the types of electricity markets in which VPPs participate. The aim of this review is to identify the most profitable VPP scheme to be applied in each regulatory environment. It also highlights the challenges remaining in this field of study

Energy Scheduling of Electric Vehicles for Electricity Market Participation

Global policy targets to reduce greenhouse gas emissions has led to increased interest in electric vehicles (EV) and their integration into the electricity network. Batteries in EVs offer flexibility from the demand side that could potentially compete against generating resources for providing power system services. Existing power markets, however, are not well suited to encourage direct participation of flexible demand from small consumers such as EV owners. The introduction of an aggregator agent with the functions of gathering and representing the energy needs of EV owners in electricity markets could prove useful in this regard. In this thesis, mathematical models are developed for optimizing the EV aggregator agent's: a) energy schedule for day-ahead electricity market participation, b) energy schedule for regulating power market (RPM) participation and c) energy portfolio to determine the power contracts to be obtained from forward electricity market. The modeling is done by accumulating individual vehicle batteries and treating them as a single large battery. The centralized charging and discharging of this battery is then scheduled based on the traveling needs of the EV owners determined by an aggregated driving profile and the cumulative electrical energy needs of vehicles over the optimization horizon. Two methods for scheduling EV demand, named as joint scheduling method (JSM) and aggregator scheduling method (ASM), are presented. The developed methods are then applied on selected test systems to observe the effects of EV demand scheduling on prices in the day-ahead, regulating power and retail markets. The results from the day-ahead market case study indicate that the scheduling of EV energy using JSM at high EV penetration levels of 75-100% could lead to lowering of day-ahead market prices as compared to a simpler control method such as fixed period charging. Results from RPM case study indicate that EV aggregator could potentially perform arbitrage provided that they plan and bid competitively against other market players, while considering the additional costs associated with vehicle-to-grid discharge. The case study results from energy portfolio optimization of the aggregator point to the monetary benefits from demand flexibility of EV batteries to both the electricity retailer, in the form of increased profits, and to EV owners through higher cost savings. It was found that the savings by customers could be attained provided that the ratio of variable to fixed price retail contracts is greater than 30:70 for a 10% EV penetration level and exceeds 50:50 for a 30% EV penetration level

Shift, not drift : towards active demand response and beyond

Each semester the THINK project publishes two research reports based on topics proposed by the European Commission.Topic 11QM-01-13-151-EN-CQM-01-13-151-EN-NNowadays, the European electricity systems are evolving towards a generation mix that is more decentralised, less predictable and less dispatchable to operate. In this context, additional flexibility is expected to be provided by the demand side. Thus, how to engage consumers to participate in active demand response is becoming a pressing issue. This THINK report assesses how to realise this shift towards active consumers using a consumer-centred approach and does so from the perspective of contracts. On this basis, we recommend measures to be undertaken in the short-term, during the transition and in the long term, respectively, to achieve a full take-off of active demand response. The THINK project (2010-2013) is funded by the European Commission under the Seventh Framework Programme, Strategic Energy Technology Plan. (Call FP7-ENERGY-2009-2, Grant Agreement no: 249736). Coordinator: Prof. Jean-Michel Glachant and Prof. Leonardo Meeus, Florence School of Regulation, Robert Schuman Centre for Advanced Studies, European University Institute

Efficient operation of recharging infrastructure for the accommodation of electric vehicles: a demand driven approach

Large deployment and adoption of electric vehicles in the forthcoming years can have significant environmental impact, like mitigation of climate change and reduction of traffic-induced air pollutants. At the same time, it can strain power network operations, demanding effective load management strategies to deal with induced charging demand. One of the biggest challenges is the complexity that electric vehicle (EV) recharging adds to the power system and the inability of the existing grid to cope with the extra burden. Charging coordination should provide individual EV drivers with their requested energy amount and at the same time, it should optimise the allocation of charging events in order to avoid disruptions at the electricity distribution level. This problem could be solved with the introduction of an intermediate agent, known as the aggregator or the charging service provider (CSP). Considering out-of-home charging infrastructure, an additional role for the CSP would be to maximise revenue for parking operators. This thesis contributes to the wider literature of electro-mobility and its effects on power networks with the introduction of a choice-based revenue management method. This approach explicitly treats charging demand since it allows the integration of a decentralised control method with a discrete choice model that captures the preferences of EV drivers. The sensitivities to the joint charging/parking attributes that characterise the demand side have been estimated with EV-PLACE, an online administered stated preference survey. The choice-modelling framework assesses simultaneously out-of-home charging behaviour with scheduling and parking decisions. Also, survey participants are presented with objective probabilities for fluctuations in future prices so that their response to dynamic pricing is investigated. Empirical estimates provide insights into the value that individuals place to the various attributes of the services that are offered by the CSP. The optimisation of operations for recharging infrastructure is evaluated with SOCSim, a micro-simulation framework that is based on activity patterns of London residents. Sensitivity analyses are performed to examine the structural properties of the model and its benefits compared to an uncontrolled scenario are highlighted. The application proposed in this research is practice-ready and recommendations are given to CSPs for its full-scale implementation.Open Acces

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

Risk Hedging Strategies in New Energy Markets

In recent years, two typical developments have been witnessed in the energy market. On the one hand, the penetration of renewable generations has gradually replaced parts of the traditional ways to generate energy. The intermittent nature of renewable generation can lead to energy supply uncertainty, which might exacerbate the imbalance between energy supply and demand. As a result, the problem of energy price risks might occur. On the other hand, with the introduction of distributed energy resources (DERs), new categories of markets besides traditional wholesale and retail markets are emerging. The main benefits of the penetration of DERs are threefold. First, DERs can increase power system reliability. Second, the cost of transmission can be reduced. Third, end users can directly participate in some of these new types of markets according to their energy demand, excess energy, and cost function without third-party intervention. However, energy market participants might encounter various types of uncertainties. Therefore, it is necessary to develop proper risk-hedging strategies for different energy market participants in emerging new markets. Thus, we propose risk-hedging strategies that can be used to guide various market participants to hedge risks and enhance utilities in the new energy market. These participants can be categorized into the supply side and demand side. Regarding the wide range of hedging tools analyzed in this thesis, four main types of hedging strategies are developed, including the application of ESS, financial tools, DR management, and pricing strategy. Several benchmark test systems have been applied to demonstrate the effectiveness of the proposed risk-hedging strategies. Comparative studies of existing risk hedging approaches in the literature, where applicable, have also been conducted. The real applicability of the proposed approach has been verified by simulation results

Technological Innovations and Endogenous Changes in U.S. Legal Institutions, 1790-1920

Recent scholarship highlights the importance of institutions to the processes of economic growth, but the precise nature of their relationship bears further examination. This paper considers how the evolution of legal institutions has contributed to, and in turn been affected by, major technological innovations. The first section of the paper examines the U.S. intellectual property system. Patent and copyright laws, and their interpretation and enforcement by the federal judiciary, certainly influenced the course of technical and cultural change, but it is clear that they did not develop independently of the state of technology and of the economy. Both the statutes and their interpretations altered in response to the introduction and diffusion of new technologies. The second section explores in more detail the impact of some of these technological innovations -- including steamboats, railroads, telegraphy, medical technologies, and automobiles -- on the common law, regulation and insurance. Such technological advances often led to institutional bottlenecks, which then required accommodations in legal rules and their enforcement. Although the common law had some capability for economizing on legal adjustment costs through 'adjudication by analogy', the socio-economic changes wrought by major innovations ultimately produced more fundamental change in legal institutions, such as shifts in the relative importance of state and federal policies, and in the degree of reliance on regulation by bureaucracy. In sum, the historical record of the evolution of legal rules and standards in the United States indicates a remarkable degree of flexibility as such institutions responded to changing economic circumstances.