Market coupling in the power markets

The thesis analyses the European Unions’ effort to create an integrated pan-European electricity market based on “market coupling” as the proposed allocation mechanism for interconnector transfer capacity. Thus, the thesis’ main focus is if market coupling leads to a price convergence in interlinked markets and how it affects the behavior of electricity price data. The applied research methods are a qualitative, structured literature review and a quantitative analysis of electricity price data. The quantitative analysis relies on descriptive statistics of absolute price differentials and on a Cointegration analysis according to Engle & Granger (1987)’s two step approach. Main findings are that implicit auction mechanisms such as market coupling are more efficient than explicit auctions. Especially the method of price coupling leads to a price convergence in involved markets, to social welfare gains and reduces market power of producers, as shown on the example of the TLC market coupling. The market coupling initiative between Germany and Denmark, on the other hand, is evaluated as less successful and illustrates the complexity and difficulties of implementing market coupling initiatives. The cointegration analysis shows that the time series were already before the coupling date cointegrated, but the statistical significance increased. The thesis suggests that market coupling leads to a price convergence of involved markets and thus functions as method to create a single, integrated European electricity market.

Market coupling in the power markets

A dissertação analisa o esforço dos sindicatos europeus para criar um mercado pan- europeu de electricidade integrada baseada em "mercados combinados", como o mecanismo de alocação de capacidade de transferência de energia entre diferentes sistemas. Assim, o foco principal do estudo é se a integração do mercado leva a uma convergência de preços nos mercados interligados, e como isso afeta o comportamento dos preços de energia elétrica. Os métodos de investigação são uma revisão bibliográfica estruturada qualitativa e uma análise quantitativa de dados de preços de energia elétrica. A análise quantitativa se baseia em estatísticas descritivas das diferenças de preços absolutos e em uma análise de cointegração de acordo com a abordagem de Engle e Granger (1987). As principais conclusões são que os mecanismos de leilões implícitos, tais como a integração de mercado são mais eficientes que os leilões explícitos. Especialmente, o método de acoplamento de preços leva a uma convergência de preços nos mercados envolvidos, a ganhos de bem-estar social e reduz a o poder dos produtores no mercado, como mostra o exemplo da integração mercado TLC. A iniciativa mercados combinados entre a Alemanha ea Dinamarca, por outro lado, é avaliada como de menor sucesso e ilustra a complexidade e as dificuldades de implementação de iniciativas de integração de mercado. A análise de cointegração mostra que as séries temporais já estavam cointegradas antes da data de integração, mas a significância estatística aumentou. A tese sugere que a integração do mercado leva a uma convergência dos preços dos mercados envolvidos e, portanto, funciona como método para criar um mercado de eletricidade único e integrado na Europa.

The economic base for power markets in Lincoln County, Oregon /

"January 1946."

The economic base for power markets in Chelan, Douglas, and Okanogan counties, Washington /

"July 1945."

A bidding strategy for minimizing the imbalances costs for renewable generators in Spanish power markets

The aim of this paper is to suggest a simple methodology to be used by renewable power generators to bid in Spanish markets in order to minimize the cost of their imbalances. As it is known, the optimal bid depends on the probability distribution function of the energy to produce, of the probability distribution function of the future system imbalance and of its expected cost. We assume simple methods for estimating any of these parameters and, using actual data of 2014, we test the potential economic benefit for a wind generator from using our optimal bid instead of just the expected power generation. We find evidence that Spanish wind generators savings would be from 7% to 26%.

LMP estimation considering the uncertainty of wind power

One of the impediments to large-scale use of wind generation within power system is its variable and uncertain real-time availability. Due to the low marginal cost of wind power, its output will change the merit order of power markets and influence the Locational Marginal Price (LMP). For the large scale of wind power, LMP calculation can't ignore the essential variable and uncertain nature of wind power. This paper proposes an algorithm to estimate LMP. The estimation result of conventional Monte Carlo simulation is taken as benchmark to examine accuracy. Case study is conducted on a simplified SE Australian power system, and the simulation results show the feasibility of proposed method.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Evaluation and improvement of total transfer capability - A case study

With deregulation, the total transfer capability (TTC) calculation, which is the basis for evaluating available transfer capability (ATC), has become very significant. TTC is an important index in power markets with large volume of inter-area power exchanges and wheeling transactions taking place on an hourly basis. Its computation helps to achieve a viable technical and commercial transmission operation. The aim of the paper is to evaluate TTC in the interconnections and also to improve it using reactive optimization technique and UPFC devices. Computations are carried out for normal and contingency cases such as single line, tie line and generator outages. Base and optimized results are presented, and the results show how reactive optimization and unified power flow controller help to improve the system conditions. In this paper repeated power flow method is used to calculate TTC due to its ease of implementation. A case study is carried out on a 205 bus equivalent system, a part of Indian Southern grid. Parameters like voltage magnitude, L-index, minimum singular value and MW losses are computed to analyze the system performance.

Fluxo de potência ótimo em sistemas multimercados através de um algorítmo evolutivo multiobjetivo

Pós-graduação em Engenharia Elétrica - FEIS

An Experimental Study of Complex-Offer Auctions: Payment Cost Minimization vs. Offer Cost Minimization

A Payment Cost Minimization (PCM) auction has been proposed as an alternative to the Offer Cost Minimization (OCM) auction to be used in wholesale electric power markets with the intention to lower the procurement cost of electricity. Efficiency concerns about this proposal have relied on the assumption of true production cost revelation. Using an experimental approach, I compare the two auctions, strictly controlling for the level of unilateral market power. A specific feature of these complex-offer auctions is that the sellers submit not only the quantities and the minimum prices at which they are willing to sell, but also the start-up fees that are designed to reimburse the fixed start-up costs of the generation plants. I find that both auctions result in start-up fees that are significantly higher than the start-up costs. Overall, the two auctions perform similarly in terms of procurement cost and efficiency. Surprisingly, I do not find a substantial difference between less market power and more market power designs. Both designs result in similar inefficiencies and equally higher procurement costs over the competitive prediction. The PCM auction tends to have lower price volatility than the OCM auction when the market power is minimal but this property vanishes in the designs with market power. These findings lead me to conclude that both the PCM and the OCM auctions do not belong to the class of truth revealing mechanisms and do not easily elicit competitive behavior.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.

Probabilistic cost benefit analysis of generation investment in a deregulated electricity market

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithms

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

Credibility theory-based available transfer capability assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

Application of meta-analytical probabilistic approach for reliability benefits reflective optimal transmission costing – the case of India

In the deregulated Power markets it is necessary to have a appropriate Transmission Pricing methodology that also takes into account “Congestion and Reliability”, in order to ensure an economically viable, equitable, and congestion free power transfer capability, with high reliability and security. This thesis presents results of research conducted on the development of a Decision Making Framework (DMF) of concepts and data analytic and modelling methods for the Reliability benefits Reflective Optimal “cost evaluation for the calculation of Transmission Cost” for composite power systems, using probabilistic methods. The methodology within the DMF devised and reported in this thesis, utilises a full AC Newton-Raphson load flow and a Monte-Carlo approach to determine, Reliability Indices which are then used for the proposed Meta-Analytical Probabilistic Approach (MAPA) for the evaluation and calculation of the Reliability benefit Reflective Optimal Transmission Cost (ROTC), of a transmission system. This DMF includes methods for transmission line embedded cost allocation among transmission transactions, accounting for line capacity-use as well as congestion costing that can be used for pricing using application of Power Transfer Distribution Factor (PTDF) as well as Bialek’s method to determine a methodology which consists of a series of methods and procedures as explained in detail in the thesis for the proposed MAPA for ROTC. The MAPA utilises the Bus Data, Generator Data, Line Data, Reliability Data and Customer Damage Function (CDF) Data for the evaluation of Congestion, Transmission and Reliability costing studies using proposed application of PTDF and other established/proven methods which are then compared, analysed and selected according to the area/state requirements and then integrated to develop ROTC. Case studies involving standard 7-Bus, IEEE 30-Bus and 146-Bus Indian utility test systems are conducted and reported throughout in the relevant sections of the dissertation. There are close correlation between results obtained through proposed application of PTDF method with the Bialek’s and different MW-Mile methods. The novel contributions of this research work are: firstly the application of PTDF method developed for determination of Transmission and Congestion costing, which are further compared with other proved methods. The viability of developed method is explained in the methodology, discussion and conclusion chapters. Secondly the development of comprehensive DMF which helps the decision makers to analyse and decide the selection of a costing approaches according to their requirements. As in the DMF all the costing approaches have been integrated to achieve ROTC. Thirdly the composite methodology for calculating ROTC has been formed into suits of algorithms and MATLAB programs for each part of the DMF, which are further described in the methodology section. Finally the dissertation concludes with suggestions for Future work.