{"id":3483,"date":"2026-08-03T14:43:14","date_gmt":"2026-08-03T12:43:14","guid":{"rendered":"http:\/\/s603816833.onlinehome.fr\/?page_id=3483"},"modified":"2026-08-05T11:44:34","modified_gmt":"2026-08-05T09:44:34","slug":"developpement-photovoltaique","status":"publish","type":"page","link":"https:\/\/www.calibsun.com\/fr\/pv-development\/","title":{"rendered":"Market | PV development"},"content":{"rendered":"\t\t
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  • \n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\tCalibsun | Markets<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t
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    PV Development<\/span>
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    From solar resource assessment to optimized storage sizing<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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    For\u00a0<\/span>solar PV assets’<\/span> development, accurately estimating the solar resource of a future site is the critical first step of any photovoltaic project. From feasibility studies to financial close, every downstream decision depends on the quality of this initial assessment. <\/span>Satellite-based irradiance databases carry a systematic bias of \u00b15% on GHI estimates, a level of uncertainty that directly affects P50 and P90 production estimates and the bankability of the project.<\/strong><\/p>\n

    FUTURE, CalibSun’s solar resource assessment service combines on-site GHI measurement with satellite database calibration to reduce this uncertainty to 0.5%, producing reliable yield reports supported by ground-truth data. <\/span>Enabling to obtain the precise TMY needed to size storage capacity and build dispatch strategy.\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Solar<\/span> resource assessment<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    =From \u00b15% Satellite Bias to 0.5% Site-Specific Accuracy <\/span>\n<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    For any given site, the systematic error on GHI estimates derived from satellite databases typically reaches \u00b15%. In complex climates,\u00a0 islands, monsoon regions, high-altitude locations,\u00a0 this bias can be significantly larger. Without on-site pyranometer measurements, this error cannot be identified or corrected. It propagates directly into the yield report, affecting every P50 and P90 production figure presented to lenders and investors. <\/span><\/p>

    For PV developers seeking financial close, this unquantified uncertainty represents a direct bankability risk that satellite data alone cannot resolve.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    CalibSun collects data on site to minimize the gap <\/span> \nbetween estimate and reality \n<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    Installing a temporary <\/span>weather monitoring station<\/b> directly at the location of the future solar PV site enables us to capture <\/span>global horizontal irradiance (GHI) and other key parameters (temperature, wind, humidity, etc.) over a significant period. This data collection provides a reliable basis for calibrating the reference satellite database. The systematic difference between on-site and satellite observation is qualified in order to correct the bias and obtain a yield ratio as close as possible to reality.<\/strong><\/span><\/p>

    This step is essential for any effective solar asset optimization strategy: without accurate resource data, energy production tracking and power generation forecasting lack the solid foundation they require.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    FUTURE refines the P50 and reduces the P50\/P90 ratio for a secure investment<\/span><\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    After a 12-month field measurement campaign conducted by CalibSun, the systematic bias is eliminated. The calibrated satellite databases now have an uncertainty of<\/span> 0.5% instead of +\/- 5% without calibration. <\/b>Data availability is maximized, the estimated solar resource is reliable, and the economic model for the photovoltaic power plant project becomes significantly more robust. Beyond debt optimization, this on-site dataset becomes the training foundation for forecasting algorithm and for optimizing BESS sizing.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    BESS<\/span> sizing optimisation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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    Matching storage capacity <\/span> to the actual site\u2019s solar resource\n\n<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    For PV developers integrating battery energy storage systems, sizing decisions directly affect long-term project profitability and battery lifespan. The choice between a 2-hour and a 4-hour BESS, for example, depends on the temporal distribution of solar electricity generation across all seasons and not on a regional average. Under- or over-sizing storage capacity over a 20 to 25-year plant life has measurable consequences on both revenues and CAPEX efficiency.<\/strong><\/span><\/p>

    CalibSun’s solar resource assessment captures GHI at 5-minute resolution over a 12-month campaign, enabling the construction of a precise Typical Meteorological Year (TMY) and forward-looking energy production scenarios. This level of granularity characterises the actual distribution of solar generation, peak hours, variability patterns, low-irradiance periods, and informs storage sizing decisions that remain profitable across all climate scenarios considered. By grounding BESS sizing in measured site data rather than satellite estimates, developers can anticipate cycling strategy, protect battery warranty compliance, and secure the long-term performance of hybrid PV + BESS power plants<\/strong>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    1 year on-site measurement<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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    Providing the insights you need to optimize debt financing for solar assets, BESS sizing, and PV forecasting<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Bankable Data<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    Bankable Yield with calibrated TMY, reducing satellite bias from \u00b15% to 0.5% for optimal debt financing.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Forecast-Ready Asset <\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    On-site data collected during assessment used to train machine learning forecasting algorithm for day-one operational accuracy.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Optimized BESS Sizing<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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    GHI data at 5-minute resolution builds the precise TMY needed to size storage capacity and build dispatch strategy. <\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Our related resources<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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    Accurate forecasting is the key to unlocking the full financial benefits of solar investments and maximizing returns on every grid-connected solar power system in the portfolio.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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