Why is my renewable generation park not producing as planned? - Reverse energy losses

Perhaps the operation of the fleet is not correct and there are unexpected plant shutdowns, either due to errors in the machines or to external factors such as environmental, social or even electrical network conditioning factors, known as 'curtailment' due to overproduction. You don't know if the performance of the equipment is optimal or if it could be improved. Maybe the estimated resource, wind or radiation, has not been finally produced because its prediction has failed. The first step in making the right decision is to know what is causing the drop in production in order to successfully tackle a new operating model. But how to find the reason quickly, reliably, without affecting or affecting as little as possible the operation of the wind farm?   

Models based on artificial intelligence

Models based on algorithms created with artificial intelligence are a very powerful solution to quantify the loss of production and identify the cause why the plant is not operating at its optimum. In this way, entities such as CIRCE are able to detect the problem without affecting the daily operation of the plant, in an agile way and with the independent guarantee of a third party.  But not just any model will do. It must be based on the experience of having analyzed large volumes of data over a long period of time and on extensive knowledge of both the data and the plants in operation. In this sense, knowing how to identify the different factors that trigger machine alarms is crucial to properly manage all the information provided by data mining models.    

Reverse energy losses by up to 25%

Analyzing the situation with a good model, at the CIRCE technology center we have observed that it is possible to identify energy production losses of up to 25% and reverse them for the most part by offering tools to help make the necessary changes in operating policies, so that your renewable generation plant achieves its optimal generation. In this way, renewable plant owners improve their competitiveness without the need to invest in new equipment, only by optimizing what they have already acquired.