On the Economic Value and Price-Responsiveness of Ramp-Constrained Storage

The primary concerns of this paper are twofold: to understand the economic value of storage in the presence of ramp constraints and exogenous electricity prices, and to understand the implications of the associated optimal storage management policy on qualitative and quantitative characteristics of storage response to real-time prices. We present an analytic characterization of the optimal policy, along with the associated finite-horizon time-averaged value of storage. We also derive an analytical upperbound on the infinite-horizon time-averaged value of storage. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. While the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, we first present computational experiments that suggest that optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price, but little or no elasticity far from it. We then present a computational framework for understanding the behavior of storage as a function of price and the amount of stored energy, and for characterization of the buy/sell phase transition region in the price-state plane. Finally, we study the impact of market-based operation of storage on the required reserves, and show that the reserves may need to be expanded to accommodate market-based storage

Stochastic dynamic optimization of consumption and the induced price elasticity of demand in smart grids

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 75-77).This thesis presents a mathematical model of consumer behavior in response to stochastically-varying electricity prices, and a characterization of price-elasticity of demand created by optimal utilization of storage and the flexibility to shift certain demands to periods of lower prices. The approach is based on analytical characterization of the consumer's optimal policy and the associated value function in a finite-horizon stochastic dynamic programming framework. A general model is first presented, which incorporates both load-shifting and storage, and then, the model is decoupled into two subproblems, one for load-shifting and the other for storage. The study of optimal utilization of storage, which is performed analytically and in the presence of ramp constraints, reveals, as a particularly compelling finding, that the value function is a convex piece-wise linear function of the storage state. Moreover, it is shown that the expected monetary value of storage increases with price volatility, and that when the ramping rate is finite, the value of storage saturates quickly as the capacity increases, regardless of price volatility. Furthermore, it is shown that although the demand for electricity is often deemed to be highly inelastic, optimal utilization of local storage capacity induces a considerable amount of price elasticity of demand. The study of the load-shifting problem is performed under both perfect and partial information about price distribution. It is shown that load-shifting induces considerable consumer savings that increase with price volatility. Furthermore, it is shown that the opportunity to optimally schedule the shiftable loads creates a considerable amount of price elasticity, even when the aggregate consumption over a long period remains insensitive to price variations.by Ali Faghih.S.M

Capacity market design options: a dynamic capacity investment model and a GB case study

Rising feed-in from renewable energy sources decreases margins, load factors, and thereby profitability of conventional generation in several electricity markets around the world. At the same time, conventional generation is still needed to ensure security of electricity supply. Therefore, capacity markets are currently being widely discussed as a measure to ensure generation adequacy in markets such as France, Germany, and the United States (e.g., Texas), or even implemented for example in Great Britain. We assess the effect of different capacity market design options in three scenarios: 1) no capacity market, 2) a capacity market for new capacity only, and 3) a capacity market for new and existing capacity. We compare the results along the three key dimensions of electricity policy ��� affordability, reliability, and sustainability. In a Great Britain case study we find that a capacity market increases generation adequacy since it provides incentives for new generation investments. Furthermore, our results show that a capacity market can lower the total bill of generation because it can reduce lost load and the potential to exercise market power. Additionally, we find that a capacity market for new capacity only is cheaper than a capacity market for new and existing capacity because it remunerates fewer generators in the first years after its introduction.renewable energy source

Stability Analysis of Wholesale Electricity Markets under Dynamic Consumption Models and Real-Time Pricing

This paper analyzes stability conditions for wholesale electricity markets under real-time retail pricing and realistic consumption models with memory, which explicitly take into account previous electricity prices and consumption levels. By passing on the current retail price of electricity from supplier to consumer and feeding the observed consumption back to the supplier, a closed-loop dynamical system for electricity prices and consumption arises whose stability is to be investigated. Under mild assumptions on the generation cost of electricity and consumers' backlog disutility functions, we show that, for consumer models with price memory only, market stability is achieved if the ratio between the consumers' marginal backlog disutility and the suppliers' marginal cost of supply remains below a fixed threshold. Further, consumer models with price and consumption memory can result in greater stability regions and faster convergence to the equilibrium compared to models with price memory alone, if consumption deviations from nominal demand are adequately penalized.Comment: 8 pages, 7 Figures, accepted to the 2017 American Control Conferenc

Essays on the Economics of Congestion Management - Theory and Model-based Analysis for Central Western Europe

Concerning the design of (regional) electricity markets, the weighting of uniform pricing with re-dispatch on the one hand and zonal or even nodal pricing on the other hand largely depends on the trade-off between price signals, short and long-term incentives, liquidity and competition. The combination of the said aspects determines the overall efficiency of a market design and its congestion management. The thesis at hand addresses itself to various aspects of the described trade-off. With regard to the European context, the thesis presents a methodology to identify suitable bidding zones under consideration of the fundamental market structure. Furthermore, the static and dynamic efficiency of different re-dispatch designs is analysed theoretically. Subsequently, the influence of congestion management designs on the distribution of producer and consumer surplus is quantified for the case of Germany. Additionally, the magnitude of the losses in efficiency induced by re-dispatch models is assessed

Are Energy Efficiency Standards Justified?

This paper develops and parameterizes an overarching analytical framework to estimate the welfare effects of energy efficiency standards applied to automobiles and electricity-using durables. We also compare standards with sectoral and economywide pricing policies. The model captures a wide range of externalities and preexisting energy policies, and it allows for possible “misperceptions”—market failures that cause underinvestment in energy efficiency.Automobile fuel economy standards are not part of the first-best policy to reduce gasoline: fuel taxes are always superior because they reduce the externalities related to vehicle miles traveled. For the power sector, potential welfare gains from supplementing pricing instruments with efficiency standards are small at best. If pricing instruments are not feasible, a large misperceptions failure is required to justify efficiency standards, and even in this case the optimal reductions in fuel and electricity use are relatively modest. Reducing economywide carbon dioxide emissions through regulatory packages (combining efficiency and emissions standards) involves much higher costs than pricing instruments.standards, energy taxes, market failure, climate, power sector, gasoline

Supply chain decisions for an adaptive, decentralized renewable energy system

The need for a more sustainable energy system and the shift to renewable energy and less-polluting fuels causes logistics problems related to the renewable energy supply. In particular, the transition towards more renewables creates problems related to supply-driven energy generation, location differences between energy production and energy demand, and the mismatch in production and demand profiles over time. This leads to curtailment of energy, irregular feed-in to the electricity grid, and transportation challenges related to the distribution of biogas. This thesis is based on the research project entitled “ADAPNER” (Adaptive logistics in a circular economy) which aims to "Determine optimized adaptable and sustainable configurations for different distribution alternatives regarding biomass and biogas in a circular economy”. The objective of this thesis is to determine these configurations for different decentralized renewable energy production, storage, and distribution alternatives. These include wind, photovoltaic (PV), biogas, LNG, and hydrogen.This thesis shows how challenges related to these domains are interrelated and should not be addressed in isolation. By addressing these issues, the results of this thesis contribute to the scientific literature and provide insights on designing the decentralized energy infrastructure in rural areas

Stochastic management framework of distribution network systems featuring large-scale variable renewable energy sources and flexibility options

The concerns surrounding climate change, energy supply security and the growing demand are forcing changes in the way distribution network systems are planned and operated, especially considering the need to accommodate large-scale integration of variable renewable energy sources (vRESs). An increased level of vRESs creates technical challenges in the system, bringing a huge concern for distribution system operators who are given the mandate to keep the integrity and stability of the system, as well as the quality of power delivered to end-users. Hence, existing electric energy systems need to go through an eminent transformation process so that current limitations are significantly alleviated or even avoided, leading to the so-called smart grids paradigm. For distribution networks, new and emerging flexibility options pertaining to the generation, demand and network sides need to be deployed for these systems to accommodate large quantities of variable energy sources, ensuring an optimal operation. Therefore, the management of different flexibility options needs to be carefully handled, minimizing the sideeffects such as increasing costs, worsening voltage profile and overall system performance. From this perspective, it is necessary to understand how a distribution network can be optimally operated when featuring large-scale vRESs. Because of the variability and uncertainty pertinent to these technologies, new methodologies and computational tools need to be developed to deal with the ensuing challenges. To this end, it is necessary to explore emerging and existing flexibility options that need to be deployed in distribution networks so that the uncertainty and variability of vRESs are effectively managed, leading to the real-time balancing of demand and supply. This thesis presents an extensive analysis of the main technologies that can provide flexibility to the electric energy systems. Their individual or collective contributions to the optimal operation of distribution systems featuring large-scale vRESs are thoroughly investigated. This is accomplished by taking into account the stochastic nature of intermittent power sources and other sources of uncertainty. In addition, this work encompasses a detailed operational analysis of distribution systems from the context of creating a sustainable energy future. The roles of different flexibility options are analyzed in such a way that a major percentage of load is met by variable RESs, while maintaining the reliability, stability and efficiency of the system. Therefore, new methodologies and computational tools are developed in a stochastic programming framework so as to model the inherent variability and uncertainty of wind and solar power generation. The developed models are of integer-mixed linear programming type, ensuring tractability and optimality.As mudanças climáticas, a crescente procura por energia e a segurança de abastecimento estão a modificar a operação e o planeamento das redes de distribuição, especialmente pela necessidade de integração em larga escala de fontes de energia renováveis. O aumento desses recursos energéticos sustentáveis gera enormes desafios a nível técnico no sistema, atendendo a que o operador do sistema de distribuição tem o dever de manter a integridade e a estabilidade da rede, bem como a qualidade de energia entregue aos consumidores. Portanto, os sistemas de energia elétrica existentes devem passar por um eminente processo de transformação para que as limitações atuais sejam devidamente atenuadas ou mesmo evitadas, esperando-se assim chegar ao paradigma das redes elétricas inteligentes. Para as redes de distribuição acomodarem fontes variáveis de energia renovável, novas e emergentes opções de flexibilidade, que dizem respeito à geração, carga e à própria rede, precisam de ser desenvolvidas e consideradas na operação ótima da rede de distribuição. Assim, a gestão das opções de flexibilidade deve ser cuidadosamente efetuada para minimizar os efeitos secundários como o aumento dos custos, agravamento do perfil de tensão e o desempenho geral do sistema. Desta perspetiva, é necessário entender como uma rede de distribuição pode operar de forma ótima quando se expõe a uma integração em larga escala de fontes variáveis de energia renovável. Devido à variabilidade e incerteza associadas a estas tecnologias, novas metodologias e ferramentas computacionais devem ser desenvolvidas para lidar com os desafios subsequentes. Desta forma, as opções de flexibilidade existentes e emergentes devem ser implantadas para gerir a incerteza e variabilidade das fontes de energia renovável, mantendo o necessário balanço entre carga e geração. Nesta tese é feita uma análise extensiva das principais tecnologias que podem providenciar flexibilidade aos sistemas de energia elétrica, e as suas contribuições para a operação ótima dos sistemas de distribuição, tendo em consideração a natureza estocástica dos recursos energéticos intermitentes e outras fontes de incerteza. Adicionalmente, este trabalho contém investigação detalhada sobre como o sistema pode ser otimamente gerido tendo em conta estas tecnologias de forma a que a uma maior percentagem de carga seja fornecida por fontes variáveis de energia renovável, mantendo a fiabilidade, estabilidade e eficiência do sistema. Por esse motivo, novas metodologias e ferramentas computacionais usando programação estocástica são desenvolvidas para modelizar a variabilidade e incerteza inerente à geração eólica e solar. A convergência para uma solução ótima é garantida usando programação linear inteira-mista para formular o problema

Market design for a reliable ~100% renewable electricity system: Deliverable D3.5

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: The goal of this report is to identify in which respects the design and regulation of electricity markets needs to be improved in order facilitate a (nearly) completely decarbonized electricity system. It provides a basis for scoping the modeling analyses that are to be performed in subsequent work packages in the TradeRES project. These simulations will provide the basis for an update of this deliverable in the form of a more precise description of an all-renewable electricity market design. In this first iteration1 of deliverable 3.5, we analyze how the current design of electricity markets may fall short of future needs. Where there is a lack of certainty about the best market design choices, we identify alternative choices. Alternatives may concern a choice between policy intervention and no intervention or different intervention options. Section 2 outlines current European electricity market design and the key pieces of European legislation that underlie it. The European target model is zonal pricing with bidding zones that are defined as geographic areas within the internal market without structural congestion. That implies that within one bidding zone electricity can be traded without considering grid constraints and there are uniform wholesale prices in each zone. The main European markets are Nordpool, EPEX and MIBEL. Trading between zones in the European Price Coupling Region occurs through an implicit auction where price and quantity are computed for every hour of the next day, using EUPHEMIA, a hybrid algorithm for flowbased market coupling that is considered the best practice in Europe at this time.N/