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Hybridization without storage in Mali
HYBRID GOLD MINE: PV & GENERATORS
BARRICK GOLD, in partnership with AFRICAN POWER SERVICES and SPIE Industrie, has integrated photovoltaic energy to power its Loulo mining site in Mali.
This integration was made possible by SKY, CalibSun's innovative cloud detection service.
BARRICK Gold, the world's second-largest gold producer, has reduced its greenhouse gas emissions by several hundred tons and its operating costs since 2020 by incorporating photovoltaic energy into its energy mix. A success that justifies doubling the share of photovoltaics at its Loulo site in Mali in 2024.
Located in the Sahel desert, without access to the electrical grid, the mining operation requires 65 MW of electrical power, initially produced by generators running on heavy fuel oil and diesel. Fully committed to reducing its environmental impact, BARRICK Gold integrated 24MWp of solar energy through the construction of a photovoltaic plant, supplementing the generators. In one year, the group reduced its fossil fuel usage by 15.6 megaliters, equivalent to 42,050 tons of CO2 emissions.
The introduction of photovoltaics to power the Loulo gold mine was initiated in August 2020 by African Power Services and SPIE industrie. This hybridization did not include storage, thus raising major technological challenges to ensure a constant power supply and stable voltage on the micro-grid. These challenges were resolved thanks to CalibSun's SKY service, developed in partnership with the O.I.E. research laboratory of MINES Paris – PSL and with the support of ARMINES.
HYBRIDIZATION WITHOUT STORAGE
SKY enabled the anticipation of power drops through advanced analytical and artificial intelligence algorithms to eliminate the need for storage investment.
Necessary for maintaining activity, SKY, the cloud detection service, required the installation of several hemispherical cameras, installed and operated by SPIE Industrie & Tertiaire, at the Loulo site.
This network of hemispherical cameras observing the sky, strategically placed in the immediate vicinity of the photovoltaic plant, provides updated information on cloud formation within a radius of 50 km around the photovoltaic plant and detects clouds not visible by satellite imagery or irradiation sensors.
These images are transmitted to algorithms based on geometric and machine learning approaches that predict the decrease or increase in the performance of the photovoltaic plant to the second. The production forecasts of the photovoltaic plant are transmitted to the energy management system, operated by AFRICAN POWER SERVICES. They prepare the thermal plant for startup or reduction of its generators to compensate for the insufficient electrical energy provided by the photovoltaic system. This solution, anticipating electrical power drops by 15 minutes, allowed for the exclusion of storage solutions, costly and constantly improving technology.