Quantifying residential PV feed-in power in low voltage grids based on satellite-derived irradiance data with application to power flow calculations

A scheme using satellite-derived irradiance measurements to model the feed-in power of residential photovoltaic (PV) systems in a low voltage distribution grid is described. It is validated against smart meter measurements from a test site with 12 residential PV systems in the city of Ulm, Germany, during May 2013 to December 2014. The PV feed-in power is simulated in a 15-min time resolution based on irradiance data derived from Meteosat Second Generation satellite images by the physically based retrieval scheme Heliosat-4. The PV simulation is based on the nominal power and location of the PV systems as provided by the distribution system operator. Orientation angles are taken from high resolution aerial laser-scan data. The overall average mean error of PV feed-in power is 4.6% and the average root-mean-squared error is 12.3% for the individual systems. Relative values are given with respect to the total installed power of 152.3 kWp. Sensitivity studies discuss the need for knowing the exact orientation angles of each individual PV system or the usefulness of a single ground-based measurement as alternative to satellite observations. As an application of the scheme, the modelling of the effect of the power flow from the residential PV on the load flow of the low voltage distribution grid transformer is described and illustrates the advantage of the discussed approach for distribution system operators

The project ENDORSE: exploiting EO data to develop pre-market services in renewable energy

International audienceThe ENDORSE project is co-funded by the FP7 programme of the European Commission, from 2011 to 2013. It exploits the atmosphere service MACC of the European GMES programme (Global Monitoring for Environment and Security) together with other Earth Observation (EO) data and modelling. It aims at providing public authorities and private investors with accurate evaluation and forecasts of renewable resources. The focus is on the devel-opment of downstream services that create added-value information. We present here the achievements of the first period. A very accurate though fast algorithm describing the position of the sun in the sky has been developed. A series of recommendations for quality control of meteorological data have been issued. All algorithms are available as code sources and are being implemented as Web processing services (WPS). Support vector machine techniques prove successful to map the air temperature at 2-m height from satellite images and a few measurements at ground level. The next development of ENDORSE is a portfolio of pre-market downstream services, serving as precursors and examples of best practices for similar services. The resulting services will be described using the INSPIRE metadata and declared in an existing Catalog Service for the Web (CSW) dedicated to energy. Finally, we discuss the mutual benefits between GEOSS (Global Earth Observation System of Systems) and ENDORSE

Self-Consumption of Electricity by Households, Effects of PV System Size and Battery Storage

We present a study of the possible self-consumption of PV electricity by individual households. The study is based on electricity consumption time series data from 144 households in Ulm, Germany. PV power estimates using solar radiation data from satellite are used to calculate the instantaneous PV power self-consumption for each household under a number of scenarios. The results show that with a PV system producing 1/3 of the total annual electricity consumption, the self-consumption may reach 60-90% of the PV electricity while for a PV system producing the same annual energy as the consumption, the self-consumption is reduced to 20-40%. Adding battery storage may significantly increase PV self-consumption. For a PV system producing half the annual consumption, the percentage of self-consumption increases from 40-60% to 70-85%, with a storage size of 3kWh per kWp of PV system.JRC.F.7-Renewables and Energy Efficienc

N°: 2009 ENAM XXXX École doctorale n°432: “Science des Métiers de l’Ingénieur”

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Implementation and Test of an IEC 61850-Based Automation Framework for the Automated Data Model Integration of DES (ADMID) into DSO SCADA

As a result of the energy transition, an increasing number of Decentralized Energy Systems (DES) will be installed in the distribution grid in the future. Accordingly, new methods to systematically integrate the growing DES in distribution power systems must be developed utilizing the constantly evolving Information and Communication Technologies (ICT). This paper proposes the Automated Data Model Integration of DES (ADMID) approach for the integration of DES into the ICT environment of the Distribution System Operator (DSO). The proposed ADMID utilizes the data model structure defined by the standard-series IEC 61850 and has been implemented as a Python package. The presented two Use Cases focus on the Supervisory Control and Data Acquisition (SCADA) on the DSO operational level following a four-stage test procedure, while this approach has enormous potential for advanced DSO applications. The test results obtained during simulation or real-time communication to field devices indicate that the utilization of IEC 61850-compliant data models is eligible for the proposed automation approach, and the implemented framework can be a considerable solution for the system integration in future distribution grids with a high share of DES. As a proof-of-concept study, the proposed ADMID approach requires additional development with a focus on the harmonization with the Common Information Model (CIM), which could significantly improve its functional interoperability and help it reach a higher Technology Readiness Level (TRL)

Usage of earth observation for solar energy market development - lessons learnt

Within the Earth Observation Market Development (EOMD) program of the European Space Agency (ESA) the ENVISOLAR project aims at an intensified usage of earth observation based information products in the solar energy industries. Existing services for investment decision, plant management, load forecasting, and science and consulting rely on high quality surface solar irradiance measurements and reliable processing chains to deliver such information regularly. Requirements for earth observation data as well as blockages preventing their use have been identified. In consequence, existing data processing chains are analyzed as to their conformity with the needs of the solar industry. The paper focuses on how earth observation itself can contribute to the market development of solar energy technologies. Issues like quality of irradiance data for planning and managing solar energy systems, reliability and availability of earth observation information, requirements as to temporal, spatial and spectral resolution of earth observation data, and the cost-effectiveness of satellite based information compared to maintenance costs for a large set of on-site measurement devices are addressed