Forecasting PV production in the Dominican Republic


Published: 2. May 2019

PV parc Monte Christ in the Dominican Republic PV parc Monte Christ in the Dominican Republic In the north-west of the Dominican Republic, F&S Solar, solar project planner and client of Next Kraftwerke, has built the largest solar park in the Caribbean. On an area of the size of more than 280 football fields, 215,000 modules were installed to build the Montecristi solar park. With a total capacity of 116 MW (phase I - 58 MW, phase II - 58 MW), the solar park will be able to provide energy for more than 50,000 households. It feeds its power into the island's high-voltage grid via inverters and a newly-built substation.

Next Kraftwerke forecasts the feed-in of the power production for F&S Solar on a daily basis. Taking into account several data such as the system parameters and coordinates, the Virtual Power Plant operator uses automated processes to estimate the production of the park. F&S Solar, then, provides the forecast to Transmission System Operator (TSO) Organismo Coordinador del Sistema Eléctrico Nacional Interconectado (OC-SENI). “It is a substantial amount of power that the park feeds into the grid. An accurate forecast, therefore, is quite important for the TSO. Being the largest direct marketer of PV in Germany, we are happy to bring in our experience also for assets on the other side of the world,” says Jonas Linke, Software Developer at Next Kraftwerke.

Credit: F&S solar concept GmbH / www.fs-sun.de


Next Kraftwerke
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Next Kraftwerke operates one of the biggest Virtual Power Plants in Europe. By utilizing the full potential of digitalization, the company networks thousands of energy-producing and energy-consuming units in the Virtual Power Plant “Next Pool”. Through its technology and trading, clients are able to produce and consume electricity when prices are best for them. By trading their aggregated power 24/7 on different energy spot markets the Virtual Power Plant also makes a substantial contribution to stabilizing the grid by smartly distributing the power generated and consumed by the individual units in times of peak load.