Profiling residential PV output based on weekly weather forecast for home energy management system

Niimura, T.; Ozawa, Kazuhiro; Yamashita, Daisuke; Yoshimi, K.; Osawa, M.

doi:10.1109/pesgm.2012.6345020

Cited by 14 publications

(8 citation statements)

References 12 publications

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“…Monocrystalline PV have the highest nominal conversion rate whereas thin film amorphous silicon systems have the lowest. The maximum power of an array characterized by an area A is given by equation (16) [50]. (16) The temperature affects current and voltage considered individually [5]:…”

Section: Further Considerations Of the Pv Modelmentioning

confidence: 99%

“…For example, a day-ahead or week-ahead PV power output profile can be obtained with a classification of simple daily weather patterns such as rainy, cloudy, sunny (clear sky) and foggy days. Historical data of solar irradiance (for an indirect forecasting approach) [50] or PV output (for a direct forecasting approach) [26,70] and meteorological forecasts are used as input data on this purpose. These two frequently used PV output forecasting methods can play a pivotal role to size the storage batteries required to complete the PV system under consideration.…”

Section: Weather Classification For Mid-term Pv Output Forecastingmentioning

confidence: 99%

“…As an illustration, the case study of a sun-powered house in the Tokyo area, Japan, within the government supported smart city project, as described by Niimura et al (2012) the text weather forecast from 9 years of historical data has been used to establish the classification. Table 16 [50] is an example of how the weather conditions can be reinterpreted in simple terms, based on various key words that may appear within the descriptive text of a weather forecast. Such a simplification of weather patterns is very suitable to forecast the power generation from a day to a week ahead.…”

Section: Weather Classification For Mid-term Pv Output Forecastingmentioning

confidence: 99%

See 2 more Smart Citations

Very short-term photovoltaic power forecasting with cloud modeling: A review

Barbieri

Rajakaruna

Ghosh

2017

Renewable and Sustainable Energy Reviews

220

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This paper endeavors to provide the reader with an overview of the various tools needed to forecast photovoltaic (PV) power within a very short-term horizon. The study focuses on the specific application of a large scale grid-connected PV farm. As a matter of fact, the solar resource is largely underexploited worldwide whereas it exceeds by far humans' energy needs. In the current context of global warming, PV energy could potentially play a major role to substitute fossil fuels within the main grid in the future. Indeed, the number of utility-scale PV farms is currently fast increasing globally, with planned capacities in excess of several hundred megawatts. This makes the cost of PV-generated electricity quickly plummet and reach parity with non-renewable resources. However, like many other renewable energy sources, PV power depends highly on weather conditions. This particularity makes PV energy difficult to dispatch unless a properly sized and controlled energy storage system (ESU) is used. An accurate power forecasting method is then required to ensure power continuity but also to manage the ramp rates of the overall power system. In order to perform these actions, the forecasting timeframe also called horizon must be first defined according to the grid operation that is considered. This leads to define both spatial and temporal resolutions. As a second step, an adequate source of input data must be selected. As a third step, the input data must be processed with statistical methods. Finally, the processed data are fed to a precise PV model. It is found that forecasting the irradiance and the cell temperature are the best approaches to forecast precisely swift PV power fluctuations due to the cloud cover. A combination of several sources of input data like satellite and land-based sky imaging also lead to the best results for very-short term forecasting.

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Section: Further Considerations Of the Pv Modelmentioning

confidence: 99%

Section: Weather Classification For Mid-term Pv Output Forecastingmentioning

confidence: 99%

Section: Weather Classification For Mid-term Pv Output Forecastingmentioning

confidence: 99%

See 1 more Smart Citation

Very short-term photovoltaic power forecasting with cloud modeling: A review

Barbieri

Rajakaruna

Ghosh

2017

Renewable and Sustainable Energy Reviews

220

View full text Add to dashboard Cite

show abstract

“…For the simulation scenario the 24 hours simulation of HRES system was chosen. According to [49,50] two of the most significant probability amplitude profiles (PAP) for the PV production were chosen. They represent a sunny and a cloudy day for the high and low daily solar insolation conditions respectively [51].…”

Section: Simulation Processmentioning

confidence: 99%

Control and Restrictions of a Hybrid Renewable Energy System Connected to the Grid: A Battery and Supercapacitor Storage Case

et al. 2019

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This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the high-frequency component of the storage system reference for the supercapacitor from the low-frequency component for the batteries system. This solution greatly increases the reliability and durability of the HRES.

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“…This strategy uses load and weather forecast data to adjust the charging power and feed-in power to get a fully charged battery at the end of the day and/or avoid over-voltage and asset over-loading ( (iii) Studies based on external weather-based forecast from meteorological services [170,171,161,172] (iv) Studies that base their forecast on a persistence method based on values measured by the PVsystem [167,125,173] Obviously, no prediction errors apply to a perfect forecast. The only difference is the time resolution, which in the case of [152] is 1 min and in the case of [166] is 15 min.…”

Section: (D) Prognosis Based Strategymentioning

confidence: 99%

Impact of operation strategies of large scale battery systems on distribution grid planning in Germany

Resch

Bühler

Klausen

et al. 2017

Renewable and Sustainable Energy Reviews

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Due to the increasing penetration of fluctuating distributed generation electrical grids require reinforcement, in order to secure a grid operation in accordance with given technical specifications. This grid reinforcement often leads to over-dimensioning of the distribution grids. Therefore, traditional and recent advances in distribution grid planning are analysed and possible alternative applications with large scale battery storage systems are reviewed. The review starts with an examination of possible revenue streams along the value chain of the German electricity market. The resulting operation strategies of the two most promising business cases are discussed in detail, and a project overview in which these strategies are applied is presented. Finally, the impact of the operation strategies are assessed with regard to distribution grid planning.Postprint (author's final draft

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Profiling residential PV output based on weekly weather forecast for home energy management system

Cited by 14 publications

References 12 publications

Very short-term photovoltaic power forecasting with cloud modeling: A review

Very short-term photovoltaic power forecasting with cloud modeling: A review

Control and Restrictions of a Hybrid Renewable Energy System Connected to the Grid: A Battery and Supercapacitor Storage Case

Impact of operation strategies of large scale battery systems on distribution grid planning in Germany

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