Improving wind power forecasts: combination through multivariate dimension reduction techniques

Wind energy and wind power forecast errors have a direct impact on operational decision problems involved in the integration of this form of energy into the electricity system. As the relationship between wind and the generated power is highly nonlinear and time-varying, and given the increasing number of available forecasting techniques, it is possible to use alternative models to obtain more than one prediction for the same hour and forecast horizon. To increase forecast accuracy, it is possible to combine the different predictions to obtain a better one or to dynamically select the best one in each time period. Hybrid alternatives based on combining a few selected forecasts can be considered when the number of models is large. One of the most popular ways to combine forecasts is to estimate the coefficients of each prediction model based on its past forecast errors. As an alternative, we propose using multivariate reduction techniques and Markov chain models to combine forecasts. The combination is thus not directly based on the forecast errors. We show that the proposed combination strategies based on dimension reduction techniques provide competitive forecasting results in terms of the Mean Square ErrorThe second author, Pilar Poncela, acknowledges financial support from the Spanish Government, Ministry of Science, contract grant PID2019-108079GB-C22/AEI/10.13039/50110001103

Nuevos modelos de predicción eólica basados en series temporales

El trabajo desarrollado en esta tesis se centra en la mejora de los modelos estadísticos presentes en herramientas de predicción eólica actualmente existentes. Las principales aportaciones son, en primer lugar, partiendo de los modelos basados en el filtro de Kalman, la estimación de las matrices del sistema por máxima verosimilitud. De esta manera se incorporan las características del parque eólico a la predicción y se adapta la herramienta de predicción a cada parque. En segundo lugar, se estudia la aplicación de técnicas multivariantes que permitan captar, a través de las correlaciones entre parámetros, relaciones no recogidas explícitamente en los modelos. Se plantean distintas alternativas multivariantes de reducción de datos como estrategia de combinación de predicciones para la obtención de la predicción final, así como métodos basados en cadenas de Markov. La aplicación práctica de las estrategias planteadas se muestran para el parque eólico de SotaventoDepartamento de Ingeniería de Sistemas y Automática2012-11-2

SMART GRIDS LABORATORIES INVENTORY 2015

A smart electricity grid opens the door to a myriad of new applications aimed at enhancing security of supply, sustainability and market competitiveness. Gathering detailed information about smart grid laboratories activities represents a primary need. In order to obtain a better picture of the ongoing Smart Grid developments, after the successful smart grid project survey initiated in 2011, we recently launched a focused on-line survey addressed to organisations owning or running Smart Grid laboratory facilities. The main objective is to publish aggregated information on a regular basis in order to provide an overview of the current facilities, to highlight trends in research and investments and to identify existing gaps.JRC.F.3-Energy Security, Systems and Marke

The immediate impacts of COVID-19 on European electricity systems: a first assessment and lessons learned

The worldwide spread of the COVID-19 pandemic in 2020 forced most countries to intervene with policies and actions—including lockdowns, social-distancing and smart working measures—aimed at mitigating the health system and socio-economic disruption risks. The electricity sector was impacted as well, with performance largely reflecting the changes in the industrial and commercial sectors operations and in the social behavior patterns. The most immediate consequences concerned the power demand profiles, the generation mix composition and the electricity price trends. As a matter of fact, the electricity sectors experienced a foretaste of the future, with higher renewable energy penetration and concerns for security of supply. This paper presents a systemic approach toward assessing the impacts of the COVID-19 pandemic on the power sector. This is aimed at supporting decision making—particularly for policy makers, regulators, and system operators—by quantifying shorter term effects and identifying longer term impacts of the pandemic waves on the power system. Various metrics are defined in different areas—system operation, security, and electricity markets—to quantify those impacts. The methodology is finally applied to the European power system to produce a comparative assessment of the effects of the lockdown in the European context

Market Integration Scheme of a Multi-Terminal HVDC Grid in the North Seas

The development of a Multi-Terminal (MT) High Voltage DC (HVDC) Grid based on Voltage Source Converter (VSC) technology has been envisaged as a key development for harnessing the vast offshore wind production potential of the North Seas. In this paper, market integration of a Centrally Dispatched MT HVDC Grid based on droop control is examined. Particular emphasis is given on the management of onshore imbalance volumes due to offshore wind power forecast errors. The economic importance of the control choices of the Operator of such an active transmission grid is highlighted, and regulatory implications are briefly discussed. The main contribution of the paper is the coherent development of a droop-controlled MT HVDC Grid scheme that integrates Optimal Power Flow (OPF) dispatch, and imbalance volume management.JRC.F.3-Energy Security, Systems and Marke

Pan-European analysis on power system flexibility

Ongoing deployments of intermittent non-synchronous power generators (i.e., wind turbines and photovoltaics) challenge power (electricity) system security in terms of matching power generation and demand. Higher flexibility in the future generation fleet and power demand are likely to play an essential role in maintaining secure operation of the power system. This paper proposes a stepwise methodology based on a set of indicators for future power system flexibility analysis through assessing (i) flexibility requirements, (ii) available flexibility resources, and (iii) power system adequacy. The proposed methodology is applied to a European case for 2020 and 2025 scenarios. The insights gained from this study can be used as input in distributing power balancing resources and to introduce new balancing products in a power market. Benefits of the integrated energy market are presented.JRC.C.3-Energy Security, Distribution and Market

Sustainable Services to Enhance Flexibility in the Upcoming Smart Grids

Global efforts are already focusing on future targets for even more increases in renewable energy sources contribution, greater efficiency improvements and further greenhouse gas emission reductions. With the fast-paced changing technologies in the context of sustainable development, new approaches and concepts are needed to cope with the variability and uncertainty affecting generation, transmission and load demand. The main challenge remains in developing technologies that can efficiently make use of the available renewable resources. Alternatives in the form of microgrids or virtual power plants along with electricity storage are potential candidates for enhancing flexibility. However, intelligence must be added at all levels in the grid and among all the equipment comprising each subsystem, in order to achieve two-way communications and bidirectional flow of power. Then, the concept of smart grid can be realized and, relying upon software systems, it can remotely and automatically dispatch and optimize generation or storage resources in a single, secure and Web-connected way. Deploying smart configurations and metering promises new possibilities for self-managed energy consumption, improved energy efficiency among final consumers and transition to more consumer-centric energy systems via demand response and demand-side management mechanisms