Solar Power Shaping: An Analytical Approach

Ghiassi-Farrokhfal, Yashar; Keshav, Srinivasan; Rosenberg, Catherine; Ciucu, Florin

doi:10.1109/tste.2014.2359795

Cited by 38 publications

(18 citation statements)

References 22 publications

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“…Ramakrishna et al [8] introduced a regime-switching approach by utilizing different models for different weather conditions to improve overall precision. Ghiassi-Farrokhfal et al [9] combined different time spans, where the basic interday irradiance was modeled in larger time slots to represent the basic trend with a peak at midday.…”

Section: Pv Power-generation Forecastsmentioning

confidence: 99%

A Heuristics-Based Policy to Reduce the Curtailment of Solar-Power Generation Empowered by Energy-Storage Systems

Basmadjian

Meer

2018

Electronics

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Renewable energy sources, on one hand, are environmentally friendly, but on the other, they suffer from volatility in power generation, which endangers power-grid stability. A viable solution to circumvent the intermittent behavior of renewables is the usage of energy-storage systems. In this paper, we study the energy management of a proof-of-concept system consisting of solar panels, energy-storage systems, a power grid, and household loads. Using neural networks, we identify the most relevant parameters impacting the power generation of solar panels, and then train the corresponding network to derive forecasts. We also go one step further, and propose a heuristics-based energy-management policy for the purpose of reducing curtailments. We show that our proposed policy outperforms the naive policy by 8%, which does not consider any power-generation forecasts.

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Section: Pv Power-generation Forecastsmentioning

confidence: 99%

A Heuristics-Based Policy to Reduce the Curtailment of Solar-Power Generation Empowered by Energy-Storage Systems

Basmadjian

Meer

2018

Electronics

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“…To near-optimally size a storage system, they develop in [5] a new envelope model for the generated power. In the general envelope model, the solar power is characterized by a statistical sample path lower envelope such that the probability of having the maximum of the distance envelopesolar energy exceed a given value is upper bound by a characteristic bounding function evaluated at the given value.…”

Section: Related Workmentioning

confidence: 99%

“…In the general envelope model, the solar power is characterized by a statistical sample path lower envelope such that the probability of having the maximum of the distance envelopesolar energy exceed a given value is upper bound by a characteristic bounding function evaluated at the given value. Inspired by the findings of [7], the authors of [5] adapt the general envelope model to enable a separate characterization of the three underlying processes of solar power (diurnal, long-term, and short-term variations).…”

Section: Related Workmentioning

confidence: 99%

Stochastic Models for Solar Power

Politaki

Alouf

2017

Lecture Notes in Computer Science

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In this work we develop a stochastic model for the solar power at the surface of the earth. We combine a deterministic model of the clear sky irradiance with a stochastic model for the so-called clear sky index to obtain a stochastic model for the actual irradiance hitting the surface of the earth. Our clear sky index model is a 4-state semi-Markov process where state durations and clear sky index values in each state have phase-type distributions. We use per-minute solar irradiance data to tune the model, hence we are able to capture small time scales fluctuations. We compare our model with the on-off power source model developed by Miozzo et al. (2014) for the power generated by photovoltaic panels, and to a modified version that we propose. In our on-off model the output current is frequently resampled instead of being a constant during the duration of the "on" state. Computing the autocorrelation functions for all proposed models, we find that the irradiance model surpasses the on-off models and it is able to capture the multiscale correlations that are inherently present in the solar irradiance. The power spectrum density of generated trajectories matches closely that of measurements. We believe our irradiance model can be used not only in the mathematical analysis of energy harvesting systems but also in their simulation. keywords: Solar power · Semi-Markov process · Photovoltaic panel

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“…Hence, consideration of solar PV power resource while analyzing electric grid operations is gaining great significance. Accurate models that can not only provide solar power forecasts, but also capture the uncertainty in the random process are necessary to address decision problems such as stochastic optimal power flow (SOPF) [1], probabilistic power flow studies [2], designing microgrids [3], solar power shaping [4] and reserve planning.…”

Section: Introductionmentioning

confidence: 99%

A Model for Joint Probabilistic Forecast of Solar Photovoltaic Power and Outdoor Temperature

Ramakrishna

Scaglione

Vittal

et al. 2019

IEEE Trans. Signal Process.

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In this paper, a stochastic model with regime switching is developed for solar photo-voltaic (PV) power in order to provide short-term probabilistic forecasts. The proposed model for solar PV power is physics inspired and explicitly incorporates the stochasticity due to clouds using different parameters addressing the attenuation in power. Based on the statistical behavior of parameters, a simple regime-switching process between the three classes of sunny, overcast and partly cloudy is proposed. Then, probabilistic forecasts of solar PV power are obtained by identifying the present regime using PV power measurements and assuming persistence in this regime. To illustrate the technique developed, a set of solar PV power data from a single rooftop installation in California is analyzed and the effectiveness of the model in fitting the data and in providing short-term point and probabilistic forecasts is verified. The proposed forecast method outperforms a variety of reference models that produce point and probabilistic forecasts and therefore portrays the merits of employing the proposed approach.

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Solar Power Shaping: An Analytical Approach

Cited by 38 publications

References 22 publications

A Heuristics-Based Policy to Reduce the Curtailment of Solar-Power Generation Empowered by Energy-Storage Systems

A Heuristics-Based Policy to Reduce the Curtailment of Solar-Power Generation Empowered by Energy-Storage Systems

Stochastic Models for Solar Power

A Model for Joint Probabilistic Forecast of Solar Photovoltaic Power and Outdoor Temperature

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