Contextual changes in the electricity market. Consumer, Regulator and Society Perspectives

Los recientes cambios en el sector eléctrico están obligando a los agentes a replantearse cuestiones que se consideraban obvias hasta ahora. Por otra parte, estos cambios están modificando las reglas del juego permitiendo, en muchos casos, la entrada de nuevos agentes en el sector. La presente memoria de tesis, que responde al modelo de Tesis con indicios de calidad, presenta en primer lugar una descripción de los principales cambios de contexto que están apareciendo en el sector y que deben ser tenidos en cuenta para redefinir el posicionamiento de cada agente o, al menos, para rediseñar sus modelos de negocio. Al estar presentes en la industria eléctrica casi todas las estructuras del mercado con parte de los negocios involucrados presentando características de monopolio natural, tiene sentido analizar el impacto de estos cambios en el consumidor, en el regulador y en la sociedad en su conjunto. Para ilustrar el efecto sobre el consumidor se ha incluido el artículo de Arcos et. al. (2018) titulado “Economic and environmental analysis of a residential PV system: A profitable contribution to the Paris agreement”, en el que se presenta una metodología de diseño óptimo para la instalación de generación fotovoltaica distribuida en usuarios residenciales. Este análisis, así como la viabilidad de estos dispositivos, ha sido posible gracias a: 1. La reducción de los costes de inversión y de los tamaños eficientes de este tipo de instalaciones que se han alcanzado gracias a los progresos tecnológicos experimentados en los últimos años, 2. La disponibilidad de información de la demanda horaria procedente de los contadores inteligentes, y 3. La conciencia medioambiental de los usuarios, así como su interés en contribuir a los compromisos adoptados en los foros internacionales. El efecto sobre el regulador se analiza partiendo del artículo de Arcos et. al. (2017) titulado “Quality, remuneration and regulatory framework: some evidence on the European electricity distribution”, en el que se analiza el impacto de la retribución de la distribución eléctrica sobre la calidad de servicio, así como la eficiencia de los distintos modelos reguladores. En tercer lugar, se introduce el impacto de estos cambios sobre la sociedad, evaluando la variación del bienestar económico que se obtendrá como consecuencia de la incorporación de nuevas instalaciones fotovoltaicas al mercado mayorista de generación eléctrica. Para ello se incluye el borrador de artículo de Arcos et al. (2019) titulado The impact of photovoltaic energy on economic welfare: an application to the iberian electricity market". También se analiza la distribución de este excedente entre los agentes del mercado, formulando propuestas de asignación que direccionen el sistema a un óptimo e Pareto. Esta memoria termina con un conjunto de conclusiones, y la descripción de posibles líneas de investigación derivadas de este trabajo.Changes in the electricity industry are forcing agents to rethink issues that were considered obvious. At the same time, they are allowing new players into the sector. This thesis report, which responds to the Thesis by compilation of articles scheme, first presents a description of the main context changes that are arising in the industry, and which must be considered to define the positioning of each agent or, at least, to redesign their business models. Since it is an industry where practically all market structures are present, and part of the businesses involved have natural monopoly characteristics, it makes sense to analyze the impact of these changes on the consumer, on the Regulator and on society as a whole. To illustrate the effect on the consumer, the article "Economic and environmental analysis of a residential PV system: A profitable contribution to the Paris agreement" has been included, in which an analysis model for the installation of distributed photovoltaic generation for residential users is described. This analysis, as well as the viability of these devices, has been possible thanks to: 1. The reduction of investment costs and efficient sizes of this type of facilities, because of the technological changes achieved in recent years, 2. The availability of hourly demand information from smart meters, 3. The environmental conscience of the users, and their interest in collaborating with the commitments adopted in international forums. The effect on the Regulator is analyzed in the article "Quality, remuneration and regulatory framework: some evidence on the European electricity distribution", which analyses the impact of electricity distribution tariffs on the quality of service, as well as the efficiency of the different regulatory models. It also assesses the variation in economic welfare that will result from the incorporation of new photovoltaic facilities into the wholesale electricity generation market, including the draft article "The Impact of Photovoltaic Energy on Economic Welfare: An Application to the Iberian Electricity Market". The distribution of this surplus among market agents is also analyzed, formulating some optimization proposals. This report closes with a set of conclusions and a description of possible research derived from this work

Short-term effects of PV integration on global welfare and CO2 emissions. An application to the Iberian electricity market

This work analyses the effect on the daily electricity market of the authorisation of 3,909 MW of new photovoltaic (PV) power in Spain in 2017 –as a contribution to the EU environmental objectives for 2030. To estimate the impact of this additional offer, we use real data from the supply and demand curves of the Iberian (Spain and Portugal) daily electricity market. Our data is available for all the hours of the full year between August 1, 2016 and July 31, 2017. In this period, more than 800 agents have participated in the market, generating more than 15 million operations. In order to calculate the new supply function for each hour, the hourly production of these new facilities is added to the offer at zero price, since their marginal costs are very close to zeroand correspond to the offers that are being made by the current PV bidders. By using static and dynamic (multilevel) analyses, the variations of prices, quantities, emissions and surpluses of buyers and sellers are calculated. As the economic theory foresees, the new supply curve causes a decrease in average prices of 2.7 €/MWh in daylight hours(or 1.5€/MWh considering all the hours of the year), and an8% reduction in the income of the PV plants currently in operation (incumbents). The substitution of combined cycle energy (the technology expulsed) by PV energy brings about a saving of 2.2 million Mt of CO2 eq. In terms of economic welfare, the incorporation of PV power produces an increase in the total surplus of about 300 M€ each year

Robustness of electricity systems with nearly 100% share of renewables: A worst-case study

Several research studies have shown that future sustainable electricity systems, mostly based on renewable generation and storage, are feasible with today's technologies and costs. However, recent episodes of extreme weather conditions, probably associated with climate change, cast shades of doubt on whether the resulting generation portfolios are sufficiently robust to assure, at all times, a suitable balance between generation and demand, when adverse conditions are faced. To address this issue, this work elaborates a methodology intended to determine a sustainable electricity generation system, that can endure extreme weather conditions which are likely to occur. First, using hourly production and demand data from the last decade, along with estimates of new uses of electricity, a worst-case scenario is constructed, including the storage capacity and additional photovoltaic power which are needed to serve the demand on an hourly basis. Next, several key parameters which may have a significant influence on the LCOE are considered, and a sensitivity analysis is carried out to determine their real impact, significance and potential trends. The proposed methodology is then applied to the Spanish system. The results show that, under the hypotheses and conditions considered in this paper, it is possible to design a decarbonized electricity system that, taking advantage of existing sustainable assets, satisfies the long-term needs by providing a reliable supply at an average cost significantly lower than current market prices.Agencia Estatal de Investigación (AEI) PID2020-116433RB-I00Centro para el Desarrollo Tecnológico Industrial (CDTI) España CER-2019101

Optimal Design Model for a Residential PV Storage System an Application to the Spanish Case

Self-consumption of photovoltaic energy is being promoted as an effective way for energy consumption in residential households. The European Directive 944/2019 promotes the use of green energy and battery energy storage systems (BESS) for self-consumption and, in Spain, the 244/2019 Royal Decree of the Spanish electrical regulatory framework allows the self-consumption of energy with a photovoltaic (PV) facility for residential use, as well as the injection of the surplus energy into the grid for which compensation will be received. At the same time, new developments in PV and BESS technologies reduce the costs of facilities, a fact that can increase the profitability of self-consumption through PV energy. This study evaluates the profitability of a household PV facility with BESS using a model based on real market prices, hourly data from user smart meters, and their own location; especially, the model gives the best configuration of PV panels power and BESS capacity. The financial indicators taken as reference for the results and conclusions are the Net Present Value (NPV), Internal Rate of Return (IRR), and Investment Return (IR). Our method examines also the effect of the BESS and PV panel costs on the profitability of the facility. Unlike other studies, our model is based on actual (not simulated) demand and price data, and it can be easily extended to other locations and market prices

Economic and environmental analysis of a residential PV system: A profitable contribution to the Paris agreement

The aim of this paper is to analyze the economic and environmental aspects of installing PV facilities for residential electricity users. This paper explores, in a conservative approach, the installation of a PV capacity to compensate the consumption with the production for each moment, never feeding electricity into the utility network and without storage. The approach proposed is illustrated by applying different power PV capacities in alternative locations (Marseille, Madrid and Seville), using the hourly demand provided for the smart meters. Combining the load curve of each user, the irradiation and PV production of each location, the cost of equipments, the hourly emission in the whole market, the variable price of electricity for residential users and the energy needs to build a PV facility. The model calculates, for each individual the optimal PV power to install and the emissions avoided. The results show that, with the current cost of the PV facilities and variable prices of electricity, the PV are, from an economic and environmental point of view, profitable in all the locations analyzed. This initiative will be more profitable for private investors and, additionally, for the environment in the next three years. A massive installation of these facilities in Spain and France will contribute to achieving their Nationally Determined Contribution (NDC) of the Paris agreement (COP-21), fulfilling, in Spain, the current legal restrictions

Detection of Non-Technical Losses in Smart Distribution Networks: a Review

With the advent of smart grids, distribution utilities have initiated a large deployment of smart meters on the premises of the consumers. The enormous amount of data obtained from the consumers and communicated to the utility give new perspectives and possibilities for various analytics-based applications. In this paper the current smart metering-based energy-theft detection schemes are reviewed and discussed according to two main distinctive categories: A) system statebased, and B) arti cial intelligence-based.Comisión Europea FP7-PEOPLE-2013-IT

On directors’ compensation: a multilevel analysis of Spanish listed companies

This study analyzes the determinants of the annual compensation of directors belonging to the boards of the Spanish companies that constitute the IBEX 35 stock index. We investigate the importance of observed and unobserved heterogeneity in explaining director compensation. Based on a three-level mixed effect model, our analysis includes time-invariant random effects at company and manager level as determinants of director pay. We find that company effects explain 30% of the variation in director pay, while company and director effects taken together explain 77% of that variation. Our findings suggest that the characteristics of the company, in terms of activity sector, size and financial performance, and the professional attributes of the director (especially the role within the board), influence the compensation received. In addition, some directors and companies show random effects (either positive or negative) that significantly separate them from the expected compensation estimated from the fixed part of the model.CDTI - Centro para el Desarrollo Tecnológico IndustrialMinisterio de Economía, Industria y Competitivida

Use of Deep Learning Architectures for Day-Ahead Electricity Price Forecasting over Different Time Periods in the Spanish Electricity Market

The importance of electricity in people’s daily lives has made it an indispensable commodity in society. In electricity market, the price of electricity is the most important factor for each of those involved in it, therefore, the prediction of the electricity price has been an essential and very important task for all the agents involved in the purchase and sale of this good. The main problem within the electricity market is that prediction is an arduous and difficult task, due to the large number of factors involved, the non-linearity, non-seasonality and volatility of the price over time. Data Science methods have proven to be a great tool to capture these difficulties and to be able to give a reliable prediction using only price data, i.e., taking the problem from an univariate point of view in order to help market agents. In this work, we have made a comparison among known models in the literature, focusing on Deep Learning architectures by making an extensive tuning of parameters using data from the Spanish electricity market. Three different time periods have been used in order to carry out an extensive comparison among them. The results obtained have shown, on the one hand, that Deep Learning models are quite effective in predicting the price of electricity and, on the other hand, that the different time periods and their particular characteristics directly influence the final results of the modelMinisterio de Ciencia, Innovación y Universidades TIN2017-88209-C2Junta de Andalucía US-1263341Junta de Andalucía P18-RT-277

SmartFD: A Real Big Data Application for Electrical Fraud Detection

The main objective of this paper is the application of big data analytics to a real case in the field of smart electric networks. Smart meters are not only elements to measure consumption, but they also con stitute a network of millions of sensors in the electricity network. These sensors provide a huge amount of data that, once analyzed, can lead to significant advances for the society. In this way, tools are being developed in order to reach certain goals, such as obtaining a better consumption estimation (which would imply a better production planning), finding better rates based on the time discrimination or the contracted power, or minimizing the non-technical losses in the network, whose actual costs are eventually paid by end-consumers, among others. In this work, real data from Spanish consumers have been analyzed to detect fraud in con sumption. First, 1 TB of raw data was preprocessed in a HDFS-Spark infrastructure. Second, data duplication and outliers were removed, and missing values handled with specific big data algorithms. Third, cus tomers were characterized by means of clustering techniques in different scenarios. Finally, several key factors in fraud consumption were found. Very promising results were achieved, verging on 80% accuracyMinisterio de Economía y Competitividad TIN2014-55894-C2-RMinisterio de Economía y Competitividad TIN2017-88209-C2-

¿Cómo transformar información en ahorro para el consumidor doméstico? El caso del contador eléctrico inteligente en España

El cliente doméstico era el gran olvidado del sistema eléctrico. A pesar de su peso en el consumo total, hasta hace pocos años su poder de intervenir en el mercado era extremadamente limitado. La aparición de las nuevas tecnologías permiten, por un lado obtener datos de consumo horarios individuales y, por otro lado, analizarlos de manera agregada. En este trabajo, se han analizado los consumos agregados de clientes domésticos de tres grandes ciudades españolas. El objetivo es intentar caracterizar sus curvas de demanda y preguntarnos si sería posible un ahorro de costes sin necesidad de variar sus patrones de consumo. Los resultados mostrados confirman esta hipótesis, siendo tremendamente rentable para los consumidores el tratamiento de los datos masivos a los que se han tenido acceso gracias a las nuevas tecnologías