The paper reviews different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power. We consider both supply and demand side measures. In addition to presenting energy system flexibility measures, their importance to renewable electricity is discussed. The flexibility measures available range from traditional ones such as grid extension or pumped hydro storage to more advanced strategies such as demand side management and demand side linked approaches, e.g. the use of electric vehicles for storing excess electricity, but also providing grid support services. Advanced batteries may offer new solutions in the future, though the high costs associated with batteries may restrict their use to smaller scale applications. Different “P2Y”-type of strategies, where P stands for surplus renewable power and Y for the energy form or energy service to which this excess in converted to, e.g. thermal energy, hydrogen, gas or mobility are receiving much attention as potential flexibility solutions, making use of the energy system as a whole. To “functionalize” or to assess the value of the various energy system flexibility measures, these need often be put into an electricity/energy market or utility service context. Summarizing, the outlook for managing large amounts of RE power in terms of options available seems to be promising.

https://research.aalto.fi/files/6557604/lund_et_al_review.pdf

Review of energy system flexibility measures to enable high levels of variable renewable electricity

Review of photovoltaic power forecasting

http://coimbra.ucsd.edu/publications/papers/2013_Inman_Pedro_Coimbra.pdf

Solar forecasting methods for renewable energy integration

The Global Energy Assessment (GEA) brings together over 300 international researchers to provide an independent, scientifically based, integrated and policy-relevant analysis of current and emerging energy issues and options. It has been peer-reviewed anonymously by an additional 200 international experts. The GEA assesses the major global challenges for sustainable development and their linkages to energy; the technologies and resources available for providing energy services; future energy systems that address the major challenges; and the policies and other measures that are needed to realize transformational change toward sustainable energy futures. The GEA goes beyond existing studies on energy issues by presenting a comprehensive and integrated analysis of energy chalenges, opportunities and strategies, for developing, industrialized and emerging economies. This volume is a invaluable resource for energy specialists and technologists in all sectors (academia, industry and government) as well as policymakers, development economists and practitioners in international organizations and national governments.

Global Energy Assessment: Toward a Sustainable Future

Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

The contribution of power production by photovoltaic (PV) systems to the electricity supply is constantly increasing. An efficient use of the fluctuating solar power production will highly benefit from forecast information on the expected power production. This forecast information is necessary for the management of the electricity grids and for solar energy trading. This paper presents an approach to predict regional PV power output based on forecasts up to three days ahead provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Focus of the paper is the description and evaluation of the approach of irradiance forecasting, which is the basis for PV power prediction. One day-ahead irradiance forecasts for single stations in Germany show a rRMSE of 36%. For regional forecasts, forecast accuracy is increasing in dependency on the size of the region. For the complete area of Germany, the rRMSE amounts to 13%. Besides the forecast accuracy, also the specification of the forecast uncertainty is an important issue for an effective application. We present and evaluate an approach to derive weather specific prediction intervals for irradiance forecasts. The accuracy of PV power prediction is investigated in a case study.

Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems

The contribution of power production from PV systems to the electricity supply is constantly increasing. An efficient use of the fluctuating solar power production will highly benefit from forecast information on the expected power production, as a basis for management of the electricity grids and trading on the energy market. We present and evaluate the regional PV power prediction system of University of Oldenburg and Meteocontrol GmbH providing forecasts of up to 2 days ahead with hourly resolution. The proposed approach is based on forecasts of the global model of the European Centre for Medium-Range Forecasts (ECMWF). It includes a post-processing procedure to derive optimised, site-specific irradiance forecasts and explicit physical modelling steps to convert the predicted irradiances to PV power. Finally, regional power forecasts are derived by up-scaling from a representative set of PV systems. The investigation of proper up-scaling is a special focus of this paper. We introduce a modified up-scaling approach, modelling the spatial distribution of the nominal power with a resolution of 1° × 1°. The operational PV power prediction system is evaluated in comparison to the modified up-scaling approach for the control areas of the two German transmission system operators ‘transpower’ and ‘50 Hertz’ for the period 2.7.2009–30.4.2010. rmse values of the operational forecasts are in the range of 4–5% with respect to the nominal power for intra-day and day-ahead forecast horizons. Further improvement is achieved with the modified up-scaling approach. Copyright © 2010 John Wiley & Sons, Ltd.

Regional PV power prediction for improved grid integration

The contribution of power production by Photovoltaic (PV) systems to the electricity supply is constantly increasing. An efficient use of the fluctuating solar power production will highly benefit from forecast information on the expected power production. This forecast information is necessary for the management of the electricity grids and for energy trading. This paper presents an approach to predict regional PV power output based on irradiance forecasts provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). In the first part of the paper we introduce and evaluated different approaches to refine the irradiance forecasts. The second part of the paper addresses the power prediction for ensembles of PV systems. Here, in view of the data handling problems associated with the high number of individual systems contributing to the total PV generation within a region, the identification of representative subsets and representative system characterizations reflecting the power characteristics of the total ensemble is discussed.

/pdf/qualified-forecast-of-ensemble-power-production-by-spatially-2v1bwuk9ry.pdf

Qualified Forecast of Ensemble Power Production by Spatially Dispersed Grid-Connected PV Systems

Our energy production increasingly depends on renewable energy sources, which impose new challenges for distributed and decentralized systems. One problem is that the availability of renewable energy sources such as wind and solar is not continuous as it is affected by meteorological factors. The challenge is to develop forecast methods capable of determining the level of power generation in near real-time in order to control power plants for optimal energy production. Another scenario is the identification of optimal locations for such power plants. In our collaborative project, these tasks are investigated in the domain of energy meteorology. For that purpose large data sources from many different sensors (e.g., satellites and ground stations) are the base for complex computations. The idea is to parallelize these computations in order to obtain significant speedup. This paper reports on an ongoing project employing Grid technologies in that context. Our approach to processing large data sets from a variety of heterogeneous data sources as well as ideas for parallel and distributed computing in energy meteorology are presented. Preliminary experience with several Grid middleware systems in our application scenario is discussed.

/pdf/wisent-e-science-for-energy-meteorology-3qj7qxnm9w.pdf

Johannes Hurka

Papers

Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems

Regional PV power prediction for improved grid integration

Qualified Forecast of Ensemble Power Production by Spatially Dispersed Grid-Connected PV Systems

WISENT: e-Science for Energy Meteorology