Optimal wind reversible hydro offering strategies for midterm planning

A coordinated strategy between wind and reversible hydro units for the midterm planning that reduces the imbalance of wind power and improves system efficiency is proposed. A stochastic mixed integer linear model is used, which maximizes the joint profit of wind and hydro units, where conditional value at risk (CVaR) is used for model risk. The offering strategies studied are 1)separate wind and hydro pumping offer, where the units work separately without a physical connection and 2)a single wind and hydro pumping offer with a physical connection between them to store wind energy for future use. The effects of a coordinated wind-hydro strategy for midterm planning are analyzed, considering CVaR and the future water value. The future water value in the reservoirs is analyzed hourly for a period of 1 week and 2 months, in two realistic case studies.Es la versión aceptada del artículo. Se puede consultar la versión final en el DOI 10.1109/TSTE.2015.243797

Evaluation of load-following reserves for power systems with significant RES penetration considering risk management

In this study a novel two-stage stochastic programming based day-ahead joint energy and reserve scheduling model is developed. Demand-side as a reserve resource is explicitly modeled through responsive load aggregations, as well as large industrial consumers that directly participate in the scheduling procedure. Furthermore, a risk-hedging measure is introduced, namely the Conditional Value-at-Risk (CVaR), to analyze the behavior of energy and reserve scheduling by both the generation and the demand-side for a risk-averse ISO. The proposed methodology is tested on the practical non-interconnected insular power system of Crete, Greece, which is characterized by a significant penetration of Renewable Energy Sources (RES).Es la versión aceptada del documento. Se puede consultar la versión final en el DOI 10.1109/SEGE.2015.732457

Optimal generic energy storage system offering in day-ahead electricity markets

This paper models the offers and bids of a generic storage system in an electricity market through stochastic mixed integer linear programming. The objective function aims at maximizing the profit from buying or selling energy for a general storage system. Some parameters such as storage system efficiency, losses of the energy stored and marginal costs are parameterized to evaluate the offers and bids. Market prices are forecasted for 24 hours using AR, MA and ARIMA time series models. The problem is tested for a case study, analyzing the behaviour of the offers and bids. Also, the results obtained are studied and relevant conclusions are presented.Es la versión aceptada del documento. Se puede consultar la versión final en el DOI 10.1109/PTC.2015.723244

Integrated Transmission and Distribution System Expansion Planning Under Uncertainty

The increased deployment of distributed generation calls for the coordination and interaction between the transmission and distribution levels. This requirement is particularly relevant for planning purposes when renewable-based generation is involved. Unfortunately, in current industry practice, transmission and distribution network planners solve their problems independent of each other, thereby leading to suboptimal solutions. Within this context, this paper addresses the integrated expansion planning problem of transmission and distribution systems where investments in network and generation assets are jointly considered. Several alternatives are available for the installation of lines as well as conventional and renewable-based generators at both system levels. Thus, the optimal expansion plan identifies the best alternative for the candidate assets under the uncertainty associated with demand and renewable-based power production. The proposed model is an instance of stochastic programming wherein uncertainty is characterized through a set of scenarios that explicitly capture the correlation between the uncertain parameters. The resulting stochastic program is driven by the minimization of the expected total cost, which comprises the costs related to investment decisions and system operation. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed. Numerical results show the effective performance of the proposed approachEl mayor despliegue de generación distribuida exige la coordinación e interacción entre los niveles de transmisión y distribución. Este requisito es particularmente relevante a efectos de planificación cuando se trata de generación basada en energías renovables. Desafortunadamente, en la práctica actual de la industria, los planificadores de redes de transmisión y distribución resuelven sus problemas de forma independiente, lo que conduce a soluciones subóptimas. En este contexto, este documento aborda el problema de la planificación integrada de la expansión de los sistemas de transmisión y distribución donde se consideran conjuntamente las inversiones en activos de red y generación. Hay varias alternativas disponibles para la instalación de líneas y generadores convencionales y renovables en ambos niveles del sistema. De este modo, el plan de expansión óptimo identifica la mejor alternativa para los activos candidatos bajo la incertidumbre asociada con la demanda y la producción de energía renovable. El modelo propuesto es una instancia de programación estocástica donde la incertidumbre se caracteriza a través de un conjunto de escenarios que capturan explícitamente la correlación entre los parámetros inciertos. El programa estocástico resultante está impulsado por la minimización del costo total esperado, que comprende los costos relacionados con las decisiones de inversión y la operación del sistema. El equivalente determinista basado en escenarios asociado se formula como un programa lineal de enteros mixtos para el que se garantiza una convergencia finita a la optimización. Los resultados numéricos muestran el desempeño efectivo del enfoque propuest

Responding to the challenges of Water and Global Warming: Environmental Hydrogeology and Global Change Research Group (HYGLO-Lab)

[EN] The current Global Warming of planet Earth is probably the most important geological phenomenon in the last 20,000 years of its history and for human race. This process is having nowadays notable effects on the climate, ecosystems and natural resources. Possibly the most important renewable geological resource is water. One of the most strategic phases of the water cycle is groundwater. Despite its low visibility, quantitatively (and qualitatively too) it is essential for life on Planet Earth. Foreseeable consequences on groundwater due to climate change and sea level rise will be very significant. Hydrogeology can provide answers to many of the questions that are beginning to be raised in relation to these impacts and their effects. Environmental hydrogeology is a way of understanding the set of disciplines mixed in Hydrogeology as a Science of Nature. The HYGLO-Lab Research Group of the IGME-CSIC National Center attempts, through its lines of research, with a double global and local component, to provide answers to some of these questions.Peer reviewe

Instrumentos de gestión de riesgos para centrales eólicas.

La tesis titulada "Instrumentos de gestion de riesgos para centrales eolicas" tiene por objeto desarrollar una estrategia de gestion de riesgos de un productor eolico en el mercado electrico español. Para implementar la estrategia de gestion de riesgos se realizaran modelos de prediccion de precios y vientos, modelos de optimizacion media-varianza y otros modelos, como el Valor en Riesto, Value at Risk (VaR) y el Valor Condicional del Riesgo, Conditional Value at Risk (CVaR). Los riesgos se estiman sobre un modelo mixto de cartera que incluye tanto el mercado diario tipo "pool" como los contratos de futuros electricos. Ademas de eso, se considera el impacto de aunar la produccion eolica con la hidraulica, incluyendo bombeo, para mitigar los riesgos derivados de la incertidumbre en la produccion y en los precios de mercado

Impact of the future water value on wind-reversible hydro offering strategies in electricity markets

A coordinated offering strategy between a wind farm and a reversible hydro plant can reduce wind power imbalances, improving the system efficiency whilst decreasing the total imbalances. A stochastic mixed integer linear model is proposed to maximize the profit and the future water value FWV of the system using Conditional Value at Risk (CVaR) for risk-hedging. The offer strategies analyzed are: (i) single wind-reversible hydro offer with a physical connection between wind and hydro units to store spare wind energy, and (ii) separate wind and reversible hydro offers without a physical connection between them. The effect of considering the FWV of the reservoirs is studied for several time horizons: one week (168 h) and one month (720 h) using an illustrative case study. Conclusions are duly drawn from the case study to show the impact of FWV in the results.Es la versión aceptada del artículo. Se puede consultar la versión final en https://doi.org/10.1016/j.enconman.2015.07.06

Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming

Deregulated electricity markets encourage firms to compete, making the development of renewable energy easier. An ordinary parameter of electricity markets is the electricity market price, mainly the day-ahead electricity market price. This paper describes a new approach to forecast day-ahead electricity market prices, whose methodology is divided into two parts as: (i) forecasting of the electricity price through autoregressive integrated moving average (ARIMA) models; and (ii) construction of a portfolio of ARIMA models per hour using stochastic programming. A stochastic programming model is used to forecast, allowing many input data, where filtering is needed. A case study to evaluate forecasts for the next 24 h and the portfolio generated by way of stochastic programming are presented for a specific day-ahead electricity market. The case study spans four weeks of each one of the years 2014, 2015 and 2016 using a specific pre-treatment of input data of the stochastic programming (SP) model. In addition, the results are discussed, and the conclusions are drawn

Participation of photovoltaic power producers in short-term electricity markets based on rescheduling and risk-hedging mapping

Optimal bidding that considers different electricity market floors can increase the financial gains of photovoltaic (PV) power producers. However, the current approach to trading PV power essentially consists of committing to sell the forecasted PV generation. To analyze profits and investigate new business opportunities for PV power producers, this paper proposes two novel stochastic programming-based methods for scheduling and rescheduling for trading the PV generated energy in day-ahead and intraday electricity markets. Risk-hedging is also considered in terms of co-optimizing the expected profit with the Conditional Value-at-Risk (CVaR) metric. As a consequence of the structure and organization of the market floors and due to different market windows, rescheduling is necessary to exploit the most recent information. Updated rescheduling progressively reveals actual profits or losses, risk-hedging possible engagement in business transactions, and the final effect of strategic bidding. A case study in the Spanish electricity market based on actual data is presented. The analysis of the case study shows the influence of the three market floors (day-ahead, intraday, and imbalance), the participation in multiple intraday sessions, risk-hedging, and rescheduling on the profits of the PV producer