Analysis of the Iberian electricity forward market hedging efficiency

An assessment of the hedging performance in the Iberian Forward Electricity Market is performed. Aggregated data from the Portuguese and Spanish clearing houses for energy derivatives are considered. The hedging performance is measured through the ratio of the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). This hedging ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation.

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Mixed models for short-run forecasting of electricity prices: Application for the Spanish market

Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well

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.

Present and future of photovoltaic solar electricity

Introduction Crystalline silicon technology, from quartz to system Economical and environmental issues Alternatives to cristalline silicon technology Conclusions

Optimal Combined Forecasts for Electricity Prices: Influence of Clean Energies

In this work, an electricity price forecasting model is developed. The performance of the proposed approach is improved by considering renewable energies (wind power and hydro generation) as explanatory variables. Additionally, the resulting forecasts are obtained as an optimal combination of a set of several univariate and multivariate time series models. The large computational experiment carried out using out-of-sample forecasts for every hour and day allows withdrawing statistically sound conclusions

Compatison of S-SI, A-SI and CDTE technologies wording at the same conditions, after the first year of electricity production

Grid connected solar plants are a good opportunity for their use for research as a secondary objective. In countries were feed-in tariffs are still active, it is possible to include in the design of the solar plant elements for its use for research. In the case of the solar plant presented here both objectives are covered. The solar plant of this work is formed by PV modules of three different technologies: Multicrystalline, amorphous and CdTe. In one part of the solar plant, the three technologies are working at the same conditions, not only ambient conditions but also similar voltage and current input to the inverters. Both the commercial and the experimental parts of the solar plant have their own independent inverters with their meters but are finally connected to the same meter to inject. In this work we analyse the results for the first year of operation of the experimental solar plant. Productions of three different technologies in exactly the same conditions are compared and presented. According to the results, all the three technologies have conversion efficiencies dropping when the temperature increases. Amorphous module experiences the lesser reduction, whereas the multicrystalline module suffers the most.

Methodology for estimating building integrated photovoltaics electricity production under shadowing conditions and case study

Building integrated photovoltaic (BIPV) systems are a relevant application of photovoltaics. In countries belonging to the International Energy Agency countries, 24% of total installed PV power corresponds to BIPV systems. Electricity losses caused by shadows over the PV generator have a significant impact on the performance of BIPV systems, being the major source of electricity losses. This paper presents a methodology to estimate electricity produced by BIPV systems which incorporates a model for shading losses. The proposed methodology has been validated on a one year study with real data from two similar PV systems placed on the south façade of a building belonging to the Technical University of Madrid. This study has covered all weather conditions: clear, partially overcast and fully overcast sky. Results of this study are shown at different time scales, resulting that the errors committed by the best performing model are below 1% and 3% in annual and daily electricity estimation. The use of models which account for the reduced performance at low irradiance levels also improves the estimation of generated electricity.

Unit Commitment and Electricity Prices Forecasting for Market Strategy Preparation in Interconnected Systems

In this paper we present a solution for building a better strategy to take part in external electricity markets. For an optimal strategy development, both the internal system costs as well as the future values of the series of electricity prices in external markets need to be known. But in practice, the real problems that must be faced are that both future electricity prices and costs are unknown. Thus, the first ones must be modeled and forecasted and the costs must be calculated. Our methodology for building an optimal strategy consists of three steps: The first step is modeling and forecasting market prices in external systems. The second step is the cost calculation on internal system taking into account the expected prices in the first step. The third step is based on the results of the previous steps, and consists of preparing the bids for external markets. The main goal is to reduce consumers' costs unlike many others that are oriented to increase GenCo's profits.

Economic Impacts of Rules-based vs Risk-based Cybersecurity Regulations in Critical Infrastructure Providers (Bulk Electricity Providers)

Economics of Cybersecurity Part 2. SPSI-2015-01-0024.

Geothermal Electricity Generation in Colorado: Actual and Perceived Obstacles to Greater Implementation

The objective of this paper is to provide an analysis of the potential and obstacles to the development of geothermal energy resources in Colorado. Geothermal energy is the only renewable resource that can provide base-load electricity. While Colorado has significant geothermal energy potential, there are no such power plants. Layers of federal and state laws and regulations represent one barrier to further geothermal development. Transmission constraints represent another major barrier. High exploration and construction costs along with high-risk profiles for geothermal projects form another major barrier. Perceived barriers such as misunderstanding the impacts, risks, and benefits of geothermal energy hinder further development. Recommendations are provided to help overcome these obstacles.

The effect of electricity tariffs over the operating costs of the Spanish wastewater treatments plants

Given the complex structure of electricity tariffs and their steady growth in Spanish, we've studied its effect over the operating costs of the wastewater treatment plants (WWTP), concluding that in the last three years the revisions of electricity rates have meant increases in electricity costs of 64.5% in the rate 3.1.A and 79.1% in the rate 6.1. This has caused the cost of electricity, which was the most important, has increased from a 44% of total operating costs in the year 2009, to more than a 56% in the year 2012.

Electricity infrastructure: more border crossings or a borderless Europe? Bruegel Policy Contribution 2013/05, February 2013

Being able to transport electricity seamlessly across borders is essential for achieving three major European Union energy policy goals: (1) enabling competition between national energy companies, (2) cost-effective roll-out of renewables,and (3) security of supply. However, neither the market design nor the framework for infrastructure investment proposed by the European Commission is adequate for enabling free flows of electricity within the EU.

Electricity without borders: a plan to make the internal market work. Bruegel Blueprint Series 20, 5 September 2013

The most straightforward European single energy market design would entail a European system operator regulated by a single European regulator. This would ensure the predictable development of rules for the entire EU, significantly reducing regulatory uncertainty for electricity sector investments. But such a first-best market design is unlikely to be politically realistic in the European context for three reasons. First, the necessary changes compared to the current situation are substantial and would produce significant redistributive effects. Second, a European solution would deprive member states of the ability to manage their energy systems nationally. And third, a single European solution might fall short of being well-tailored to consumers’ preferences, which differ substantially across the EU. To nevertheless reap significant benefits from an integrated European electricity market, we propose the following blueprint: First, we suggest adding a European system-management layer to complement national operation centres and help them to better exchange information about the status of the system, expected changes and planned modifications. The ultimate aim should be to transfer the day-to-day responsibility for the safe and economic operation of the system to the European control centre. To further increase efficiency, electricity prices should be allowed to differ between all network points between and within countries. This would enable throughput of electricity through national and international lines to be safely increased without any major investments in infrastructure. Second, to ensure the consistency of national network plans and to ensure that they contribute to providing the infrastructure for a functioning single market, the role of the European ten year network development plan (TYNDP) needs to be upgraded by obliging national regulators to only approve projects planned at European level unless they can prove that deviations are beneficial. This boosted role of the TYNDP would need to be underpinned by resolving the issues of conflicting interests and information asymmetry. Therefore, the network planning process should be opened to all affected stakeholders (generators, network owners and operators, consumers, residents and others) and enable the European Agency for the Cooperation of Energy Regulators (ACER) to act as a welfare-maximising referee. An ultimate political decision by the European Parliament on the entire plan will open a negotiation process around selecting alternatives and agreeing compensation. This ensures that all stakeholders have an interest in guaranteeing a certain degree of balance of interest in the earlier stages. In fact, transparent planning, early stakeholder involvement and democratic legitimisation are well suited for minimising as much as possible local opposition to new lines. Third, sharing the cost of network investments in Europe is a critical issue. One reason is that so far even the most sophisticated models have been unable to identify the individual long-term net benefit in an uncertain environment. A workable compromise to finance new network investments would consist of three components: (i) all easily attributable cost should be levied on the responsible party; (ii) all network users that sit at nodes that are expected to receive more imports through a line extension should be obliged to pay a share of the line extension cost through their network charges; (iii) the rest of the cost is socialised to all consumers. Such a cost-distribution scheme will involve some intra-European redistribution from the well-developed countries (infrastructure-wise) to those that are catching up. However, such a scheme would perform this redistribution in a much more efficient way than the Connecting Europe Facility’s ad-hoc disbursements to politically chosen projects, because it would provide the infrastructure that is really needed.