French Electricity Research Articles

Turning contract crises into challenges

Purpose – To describe the use of a learning and development (L&D) program to achieve business transformation through increasing awareness of the company's business model. Design/methodology/approach – Presents a case study setting out the way that this approach was implemented at ERDF, focusing on the way the L&D program helped managers to analyze a complex strategic issue from different perspectives and develop the operational capabilities needed to address the underlying problem. Findings – When Michelle Bellon was appointed as CEO of ERDF in early 2010, she knew it was essential to act quickly to deal with plummeting satisfaction levels among suppliers and customers and declining morale within the company. Up until 2008, ERDF was an integral part of EDF, the main player in the French electricity market and a world leader in the energy sector. But with state-owned utilities giving way to deregulated power generation and supply, the industry was progressively opened up from 1990 onwards. After retail competition for residential customers started in France in 2007, ERDF was separated off from its parent company to operate the electricity distribution networks – it became an interface between the municipalities who owned them and the final customers. As a freestanding organization, ERDF suffered a collapse of business performance and by 2010 it faced institutional, operational and financial crises: municipalities were challenging ERDF's quasi-monopoly of network operation; there were delays in connecting renewable energy producers; and financial problems because local concession contracts were not always consistent with the nationwide tariff fixed by the energy regulator. Practical implications – Outlines the way that ERDF tackled the need to work more effectively with contract partners. Originality/value – Explains how developing and implementing a L&D program can support business transformation.

Individual Nonparametric Load Estimation Model for Power Distribution Network Planning

In this paper, we tackle client load estimation in a smart grid network. For that purpose, we propose an individual model based on nonparametric estimators. The model is designed for power estimations for use in network planning. Completely data-driven, the proposed methodology can be applied to both thermosensitive and nonthermosensitive clients. Real measurements collected in French distribution systems are used to validate our methodology. The proposed approach produces more reliable estimation results than the current model (termed BAGHEERA in this paper) of the French electricity company EDF does on the same data.

Prices stabilization for inexact unit-commitment problems

A widespread and successful approach to tackle unit-commitment problems is constraint decomposition: by dualizing the linking constraints, the large-scale nonconvex problem decomposes into smaller independent subproblems. The dual problem consists then in finding the best Lagrangian multiplier (the optimal “price”); it is solved by a convex nonsmooth optimization method. Realistic modeling of technical production constraints makes the subproblems themselves difficult to solve exactly. Nonsmooth optimization algorithms can cope with inexact solutions of the subproblems. In this case however, we observe that the computed dual solutions show a noisy and unstable behaviour, that could prevent their use as price indicators. In this paper, we present a simple and easy-to-implement way to stabilize dual optimal solutions, by penalizing the noisy behaviour of the prices in the dual objective. After studying the impact of a general stabilization term on the model and the resolution scheme, we focus on the penalization by discrete total variation, showing the consistency of the approach. We illustrate our stabilization on a synthetic example, and real-life problems from EDF (the French Electricity Board).

An overview of electric and solar boats market in France

Electric boats (EBoats)1 have a major role to play for the transportation of passengers, and even goods, into the centre of the cities endowed with seaborne or fluvial paths or in each places to fit the environmental rules decided by local authorities to limit the access to protected water areas. Waterways accessing downtown are identified in many cities as relevant commuting solutions. Three market segments are emerging based on the boat uses: spare-time activities, public transportation services and goods or services applications. These boats have been developed for inland as well as maritime waters: they exist in pure electrical or hybrid versions depending on needs. They use lead acid, NiCad or lithium batteries technology. The French Electric Boats Association (AFBE), including 60 members, has identified to key levers for the development of this market: strengthening the industry position and boosting the governmental incentives. This document offers a description of the most significant electric boats applications in France, while providing the technical key points that allowed such efficient services to be reached.

Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach

We propose a hybrid approach for the modeling and the short-term forecasting of electricity loads. Two building blocks of our approach are (1) modeling the overall trend and seasonality by fitting a generalized additive model to the weekly averages of the load and (2) modeling the dependence structure across consecutive daily loads via curve linear regression. For the latter, a new methodology is proposed for linear regression with both curve response and curve regressors. The key idea behind the proposed methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several ordinary (i.e., scalar) linear regression problems. We illustrate the hybrid method using French electricity loads between 1996 and 2009, on which we also compare our method with other available models including the Électricité de France operational model. Supplementary materials for this article are available online.

CLUSTERING FUNCTIONAL DATA USING WAVELETS

We present two strategies for detecting patterns and clusters in high-dimensional time-dependent functional data. The use on wavelet-based similarity measures, since wavelets are well suited for identifying highly discriminant local time and scale features. The multiresolution aspect of the wavelet transform provides a time-scale decomposition of the signals allowing to visualize and to cluster the functional data into homogeneous groups. For each input function, through its empirical orthogonal wavelet transform the first strategy uses the distribution of energy across scales to generate a representation that can be sufficient to make the signals well distinguishable. Our new similarity measure combined with an efficient feature selection technique in the wavelet domain is then used within more or less classical clustering algorithms to effectively differentiate among high-dimensional populations. The second strategy uses a similarity measure between the whole time-scale representations that is based on wavelet-coherence tools. The clustering is then performed using a k-centroid algorithm starting from these similarities. Practical performance is illustrated through simulations as well as daily profiles of the French electricity power demand.

The NOME law: implications for the French electricity market

In December 2010, France approved the law Nouvelle Organisation du Marche de l'Electricite (or NOME law) to promote competition in the retail electricity market. In practice, the law allows retailers to buy nuclear production from the incumbent, at a regulated access price. This mechanism works up to a ceiling of 100 terawatt hours, which represents one quarter of the incumbent's production from nuclear plants. Each retailer is assigned a share of that amount proportionally to its portfolio of clients. We contribute to the debate raised by the NOME law regarding the evolution of retail market prices. We show that a price decrease results if the ceiling is sufficiently high compared to the market share of the retailers competing with the incumbent. This pro-competitive effect is stronger when the incumbent's rivals take into account the impact of their market strategy on the redistribution rule. Finally, we find that, if the regulated price of the NOME electricity is set above the nuclear cost, the incumbent realizes a gain that may result in strategic withholding, weakening the pro-competitive effects of the law.

Analyzing the impact of futures trading on spot price volatility: Evidence from the spot electricity market in France and Germany

This paper examines the impact of the introduction of electricity futures on the spot-price volatility of the French (Powernext) and German (EEX) electricity markets, as well as the degree of their price correlation over the period 2002–2011. Our working hypotheses were tested based on a bivariate VECM-GARCH model. The results indicate that the introduction of futures contracts in the French electricity market, as well as the launch of the joint futures market in these countries in 2009, has decreased spot price volatility. However, this effect was not as explicit for the German market, due to data specificities. Other interesting results are: the German market dominates and leads the long run price relationship; the impact of cooling needs on demand is greater than the impact of heating needs; there is a substantial systematic pattern of electricity prices and their respective volatilities during weekdays and holidays. Overall, results are supportive of policy making at the European Commission regarding electricity market integration.

Solving the electricity production planning problem by a column generation based heuristic

This paper presents a heuristic method based on column generation for the EDF (Electricite De France) long-term electricity production planning problem proposed as subject of the ROADEF/EURO 2010 Challenge. This is to our knowledge the first-ranked method among those methods based on mathematical programming, and was ranked fourth overall. The problem consists in determining a production plan over the whole time horizon for each thermal power plant of the French electricity company, and for nuclear plants, a schedule of plant outages which are necessary for refueling and maintenance operations. The average cost of the overall outage and production planning, computed over a set of demand scenarios, is to be minimized. The method proceeds in two stages. In the first stage, dates for outages are fixed once for all for each nuclear plant. Data are aggregated with a single average scenario and reduced time steps, and a set-partitioning reformulation of this aggregated problem is solved for fixing outage dates with a heuristic based on column generation. The pricing problem associated with each nuclear plant is a shortest path problem in an appropriately constructed graph. In the second stage, the reload level is determined at each date of an outage, considering now all scenarios. Finally, the production quantities between two outages are optimized for each plant and each scenario by solving independent linear programming problems.

Regulating opportunism in the electricity industry and consumer interests

This article presents evidence on opportunistic behaviour by network operators in the liberalized British, Dutch and French electricity industries. The evidence is supplied by 303 regulatory decisions on dispute resolutions for the period 2002–2010. We observe a significant difference in how the regulators resolve disputes between network operators and producers on the one hand, and between network operators and consumers on the other hand. Consumers are negatively affected by the opportunistic behaviour of network operators, mainly by paying tariffs that are higher than is allowed by law. Policy recommendations focus on the protection of consumer interests in competitive electricity markets.

Management Insights

Management Insights

Incentives, opportunism and behavioral uncertainty in electricity industries

Many theories on the economics of the firm assume that economic actors are opportunistic. The focus of these theories is on the mitigation of the uncertainty that economic actors may behave opportunistically, and on the ability of contracts and governance structures to reduce this behavioral uncertainty. Previous studies did not analyze the properties of behavioral uncertainty in detail, nor did they emphasize the empirical verification of behavioral uncertainty with revealed opportunistic behavior. This article addresses both of these lacunae in the literature by focusing on incentive alignment between parties to information transactions and on empirical proof of opportunistic behavior. When a context aligns incentives, contracting parties do not behave opportunistically. When a context does not align incentives, contracting parties strategically distort or disguise information. A study of 239 regulatory decisions on dispute resolutions and enforcements of energy laws in the Dutch and French electricity industries confirms these propositions.

Assessment and analysis of information quality: a multidimensional model and case studies

Information quality is a complex and multidimensional notion. In the context of information system engineering, it is also a transversal notion and to be fully understood, it needs to be evaluated jointly considering the quality of data, the quality of the underlying conceptual data model and the quality of the software system that manages these data. This paper presents a multidimensional model for exploring information in a multidimensional way, which aids in the navigation, filtering, and interpretation of quality measures, and thus in the identification of the most appropriate actions to improve information quality. Two application scenarios are presented to illustrate and validate the multidimensional approach: the first one concerns the quality of customer information at Electricite de France, a French Electricity Company, and the second concerns the quality of patient records at Curie Institute, a well-known medical institute in France. The instantiation of our multidimensional model in these contexts shows first illustrations of its applicability.

Working conditions and psychosocial risk factors of employees in French electricity and gas company customer support departments

Little is known about the real impact of working conditions on the health of call center employees. The aim of this article is to describe the working conditions of French electricity and gas company customer service teams, especially those spending more than 75% of their working time handling calls in order to determine their subjective experience of their work and identify situations at risk of psychosocial constraints. A cross-sectional study using a self-completion questionnaire was conducted on a representative sample of 2,000 employees working in customer service centers. The questions focused on the variety of tasks performed, the organization of working time, the physical environment of the workstation, violent situations and psychosocial factors (Job Content Questionnaire). Multivariate statistical analyses were performed to identify factors associated with the wish to leave the sector and with a high level of psychosocial constraints. Women made up 66% of the sample. Despite a high educational level, the average socio-professional level of the employees was relatively low. Although the vast majority of employees had chosen this career (74%), just over half would like to leave. The main factors associated with iso-strain were inadequate breaks (odds ratio (OR) = 2.0), low perceived quality of work (OR = 2.4), high proportion of working time spent handling calls (≥75% of working time: OR = 5.9, between 50 and <75%: OR = 5.2), exposure to violence either internally (often or very often: OR = 3.1) or from customers (often or very often: OR = 1.8) and an unsatisfactory workplace (OR = 2.0). Employees who spend more than 75% of their working time on the phone cumulate every factor linked with a high level of constraints, but all employees of the EDF and Gaz de France customer service centers are concerned. These workers share many characteristics with other call centers: predominantly female workforce; high educational level; wish to leave this sector despite the initial choice; high level of psychosocial risk factors.

Implantable cardioverter defibrillator and 50-Hz electric and magnetic fields exposure in the workplace

The operation of implantable cardioverter defibrillators (ICD) can be disrupted by exposure to electromagnetic fields (EMF). In the workplace, some workers can be exposed to EMF higher than in daily life. We present an approach aimed at assessing fitness for work in this type of situation, based on in situ case studies in the absence of clinical and in vivo studies. A risk assessment protocol was developed to measure the 50-Hz electric and magnetic fields in the various places where the worker is likely to be present. These measures are taken in the worker's presence, while monitoring the ICD operation. All cases of implanted ICD workers in EDF, the French electricity company (around 130,000 employees), and potentially exposed to high electric and/or magnetic fields, between 2004 and 2009 are presented. These three cases involved different work circumstances, with exposure to 50-Hz electric and/or magnetic fields. No interference of the ICD was observed. This information provides the basis for the occupational physician to make a decision about fitness for work. This procedure can be extended to other medical implants and to electromagnetic fields frequencies other than 50-Hz.

Price Signals in “Energy-only” Wholesale Electricity Markets: An Empirical Analysis of the Price Signal in France

This paper analyzes the price signals of the French wholesale electricity market. We build a model of electricity prices that takes into account several key features of the French electricity market in order to assess the capacity of the price signal to guide investments. Wholesale prices should reflect the imbalances in the generation mix but the signal can be distorted if monopoly rents and/or “missing money” are present. We simulate over the 2003-2005 period theoretical perfectly competitive prices with the installed capacity and with the optimal mix to estimate the capacity imbalances and scarcity rents. We then compare the investment signal sent by observed electricity prices and the theoretical prices with the installed capacity. Although there are signs of market contestability for the mid-merit load, through market integration with the other continental markets, observed prices are too high for the baseload and too low for the peakload, as a result distorting the signal.

Relationship between occupational exposure to ionizing radiation and mortality at the French electricity company, period 1961–2003

Epidemiological studies in nuclear industry workers can produce relevant information to better appreciate the health risks related to chronic external exposure to low doses of ionizing radiation (IR). This work examined the relations between exposure to IR and mortality in workers at the French Electricity Company (EDF), followed up to year 2003. Permanent staff who had worked for at least 1year at EDF during period 1961-1994 and who had been monitored for exposure to IR were included (n=22,393). One-sided trend tests for mortality according to cumulative dose and relative risks at 100mSv were estimated using Poisson regression. Main analyses were stratified on age, sex, calendar time and education. A total of 874 deaths occurred, and 66 workers were lost to follow-up. Median age at end of follow-up was 48. None of the causes of death investigated increased significantly according to dose, except cerebrovascular diseases (p=0.01), but this last observation was based on only 22 cases. These results do not allow dismissing a possible influence of IR on cancer risk in this population. The cohort is still relatively young and therefore confidence intervals for estimated relative risks remain wide, although they have considerably narrowed since a previous analysis. Chance is a possible explanation for the association between IR and cerebrovascular mortality, due to the low number of cases on which it is based. These results thus need to be stabilized by conducting joint analyses with similar cohorts.

A STRUCTURAL RISK-NEUTRAL MODEL OF ELECTRICITY PRICES

The objective of this paper is to present a model for electricity spot prices and the corresponding forward contracts, which relies on the underlying market of fuels, thus avoiding the electricity non-storability restriction. The structural aspect of our model comes from the fact that the electricity spot prices depend on the dynamics of the electricity demand at the maturity T, and on the random available capacity of each production means. Our model explains, in a stylized fact, how the prices of different fuels together with the demand combine to produce electricity prices. This modeling methodology allows one to transfer to electricity prices the risk-neutral probabilities of the market of fuels and under the hypothesis of independence between demand and outages on one hand, and prices of fuels on the other hand, it provides a regression-type relation between electricity forward prices and forward prices of fuels. Moreover, the model produces, by nature, the well-known peaks observed on electricity market data. In our model, spikes occur when the producer has to switch from one technology to the lowest cost available one. Numerical tests performed on a very crude approximation of the French electricity market using only two fuels (gas and oil) provide an illustration of the potential interest of this model.

Mortality in nuclear workers of the French electricity company: Period 1968–2003

Background We conducted a mortality study on a cohort of French nuclear workers employed at Électricité de France (EDF). A first cancer mortality analysis was based on the 1968–1994 period. This paper presents the results from a mortality analysis including nine additional years of follow-up without consideration of exposure, covering the 1968–2003 period. Methods The cohort includes 22,393 workers, 97% of whom are males. Employment data were updated using the EDF personnel file. Vital status was ascertained using the National Registry of Population and further completed using EDF personnel and pension files. Causes of death were obtained through the National Causes of Death file. Standardized mortality ratios (SMRs) were computed using national rates as references. Variations of all-cause and all-cancer SMRs were studied according to demographic and occupational characteristics. Results At the study end point (31/12/2003), 74% of workers were still in active service. Only 0.3% of workers were lost to follow-up. The median duration of follow-up was 20 years. Causes were ascertained for 96% of deaths. The total number of deaths was 874, 307 of which were cancer deaths. SMRs for all causes and cancers show a significant deficit compared to the French national mortality rates. No significant excess was observed for any of the cancer sites studied. Nonsignificant excesses were observed for pancreatic, pleural, kidney, and brain cancer. Significant variations of all-cause SMRs according to age at study entry and attained age were observed. Significant variations of all-cause and all-cancer SMRs according to education level at employment were observed, with a reduced SMR for a higher level of education. Conclusion There is a significant deficit of mortality compared to the general population, reflecting a strong healthy worker effect. Although nine years of follow-up were added, this cohort is made up of young workers, most of whom are still in active service. Regular updating of the follow-up of this cohort is planned, aiming for an occupational health surveillance of workers occupationally exposed to ionizing radiation in France.

Hedging and Vertical Integration in Electricity Markets

This paper analyzes the interactions between competitive (wholesale) spot, retail, and forward markets and vertical integration in electricity markets. We develop an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares. We point out that forward hedging and vertical integration are two separate mechanisms for demand and spot price risk diversification that both reduce the retail price and increase retail market shares. We show that they differ in their impact on prices and firms' utility because of the asymmetry between production and retail segments. Vertical integration restores the symmetry between producers' and retailers' exposure to demand risk, whereas linear forward contracts do not. Vertical integration is superior to forward hedging when retailers are highly risk averse. We illustrate our analysis with data from the French electricity market.This paper was accepted by Wei Xiong, finance.