Proposal of a regressive model for the hourly diffuse solar radiation under all sky conditions

Ruiz‐Arias, José A.; Alsamamra, Husain; Tovar‐Pescador, J.; Pozo‐Vázquez, D.

doi:10.1016/j.enconman.2009.11.024

Cited by 130 publications

(76 citation statements)

References 31 publications

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“…Finally, two enhancement are formed by projecting the solar radiation onto a vertical surface tracking the solar azimuth angle. The projection to vertical is carried out by first splitting the global radiation into a direct and a diffuse component as in [23] and onto a vertical surface with the Hay and Davies model [24], see also [25]. The effect of the projections is first of all an increase in the level of solar radiation when the sun elevation is low, i.e.…”

Section: Step Four: Enhancement Of the Solar Model Partmentioning

confidence: 99%

Short-term heat load forecasting for single family houses

Bacher

Madsen

Nielsen³

et al. 2013

Energy and Buildings

100

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This paper presents a method for forecasting the load for space heating in a single-family house. The forecasting model is built using data from sixteen houses located in Sønderborg, Denmark, combined with local climate measurements and weather forecasts. Every hour the hourly heat load for each house the following two days is forecasted. The forecast models are adaptive linear time-series models and the climate inputs used are: ambient temperature, global radiation and wind speed. A computationally efficient recursive least squares scheme is used. The models are optimized to fit the individual characteristics for each house, such as the level of adaptivity and the thermal dynamical response of the building, which is modeled with simple transfer functions. Identification of a model, which is suitable for all the houses, is carried out. The results show that the one-step ahead errors are close to white noise and that practically all correlation to the climate variables are removed. Furthermore, the results show that the forecasting errors mainly are related to: unpredictable high frequency variations in the heat load signal (predominant only for some houses), shifts in resident behavior patterns and uncertainty of the weather forecasts for longer horizons, especially for solar radiation.

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Section: Step Four: Enhancement Of the Solar Model Partmentioning

confidence: 99%

Short-term heat load forecasting for single family houses

Bacher

Madsen

Nielsen³

et al. 2013

Energy and Buildings

100

View full text Add to dashboard Cite

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“…(notice that models requiring further information besides global radiation and astronomical parameters are excluded from the analysis, to ensure a wider applicability of the results). Following [18], the validation of the different decomposition algorithms was carried out, excluding observations with h < 7 • or those affected by orographic shadows, when the measured radiation is mostly composed of diffuse radiation. A total number of 10,310 valid GHI, DHI, and DNI observations was finally selected for the analysis.…”

Section: Validation and Calibration Of The Decomposition Modelsmentioning

confidence: 99%

“…For the calibration of local data, the two sigmoid functions proposed by [18] and the BRL logistic formulation with five predictors were chosen. These models present the advantage of being based on a simple single-expression function, which does not require the arbitrary definition of sub-intervals of k t .…”

Section: Validation and Calibration Of The Decomposition Modelsmentioning

confidence: 99%

Estimating Hourly Beam and Diffuse Solar Radiation in an Alpine Valley: A Critical Assessment of Decomposition Models

et al. 2018

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Accurate solar radiation estimates in Alpine areas represent a challenging task, because of the strong variability arising from orographic effects and mountain weather phenomena. These factors, together with the scarcity of observations in elevated areas, often cause large modelling uncertainties. In the present paper, estimates of hourly mean diffuse fraction values from global radiation data, provided by a number (13) of decomposition models (chosen among the most widely tested in the literature), are evaluated and compared with observations collected near the city of Bolzano, in the Adige Valley (Italian Alps). In addition, the physical factors influencing diffuse fraction values in such a complex orographic context are explored. The average accuracy of the models were found to be around 27% and 14% for diffuse and beam radiation respectively, the largest errors being observed under clear sky and partly cloudy conditions, respectively. The best performances were provided by the more complex models, i.e., those including a predictor specifically explaining the radiation components' variability associated with scattered clouds. Yet, these models return non-negligible biases. In contrast, the local calibration of a single-equation logistical model with five predictors allows perfectly unbiased estimates, as accurate as those of the best-performing models (20% and 12% for diffuse and beam radiation, respectively), but at much smaller computational costs.

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“…Solar radiation data was simulated for Nice, France for the year 2012 by analyzing the global irradiation collected by HelioClim 3 [31]. The PV system production was calculated based on a statistical distribution of direct and diffuse irradiation [32]. This data is then integrated into a projection model to calculate the percentage of direct and diffuse irradiation exposed to the panels [33].…”

Section: Generation and Load Profilesmentioning

confidence: 99%

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm. Applied Energy, Elsevier, 2018Elsevier, , 219, pp.385-393. <10.1016Elsevier, /j.apenergy.2017 .008>. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm Etta Grover-Silva 1,2 , Robin Girard 1 , George Kariniotakis 1 AbstractThe high variability and uncertainty introduced into modern electrical distribution systems due to decentralized renewable energy generators requires new solutions for grid management and power quality assurance. One of these possible solutions includes grid integrated energy storage. The appropriate size and placement of decentralized storage is highly dependent on purpose of the battery system and expected operational strategy. However, battery operational strategies are difficult to simulate simultaneously during a sizing and placement planning calculation. The motivation of this paper is to propose an algorithm that is capable of integrating sizing, placement and operational strategies of batteries into an Optimal Power Flow (OPF) distribution grid planning tool. The choice of the OPF approach permits to account for grid constraints which is more adapted for grid-connected storage devices compared to other approaches in the state of the art that are based only on an email balance analysis. This paper presents an alternating current (AC) multi-temporal OPF algorithm that uses a convex relaxation of the power flow equations to guarantee exact and optimal solutions with high algorithmic performance. The algorithm is unique and innovative due to the fact that it combines the simultaneous optimization of placement and sizing of storage devices taking into account load curves, photovoltaic (PV) production profiles, and distribution grid power quality constraints. The choice to invest in battery capacity is highly sensitive to the price of battery systems. The investment in battery systems solely for reducing losses an operational costs was proven not to be cost effective, however when battery systems are allowed to buy and sell electricity based on variable market prices they become cost effective. The assumptions used for this study shows that current battery system prices are too high to be cost effective even when allowing battery system market participation.Keywords: Optimal power flow, storage, smart grids, renewable energy, distribution grid planning Nomenclature Parameters η st Charging and discharging efficiency of the battery system P pv,j,t Ideal PV production for node j at time step t S pv,j,t PV maximum apparent power flow at node j V j Voltage maximum at node n V j Voltage minimum at node n c inv stInvestment costs of the battery system for the nominal capacity in e/MWh-day Operations and maintenance costs of using the battery system for the power use in e/MWh-day c e,tPrice of electricity at time step t I max Total capital cost limit of project P ld,j,t Active power load at n...

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Proposal of a regressive model for the hourly diffuse solar radiation under all sky conditions

Cited by 130 publications

References 31 publications

Short-term heat load forecasting for single family houses

Short-term heat load forecasting for single family houses

Estimating Hourly Beam and Diffuse Solar Radiation in an Alpine Valley: A Critical Assessment of Decomposition Models

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

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