Did you know that it is possible to improve power forecast deviations up to 5% just by combining energy forecast systems with energy monitoring systems? Energy Studio Pro® open, flexible and secure platform and SMARTWATT’s intelligent forecasting provide the best A.I. tools to optimize your portfolio.

BaxEnergy and SMARTWATT have joined forces to provide the first integrated solution for real-time power monitoring and forecasting, which is the base for any modern energy management system. The intelligent solution maximizes the value of every KWh produced and sold in the market, overall boosting productivity.

Generally, electricity generation is traded through competitive market platforms which require the productions schedule to be defined hours or even days prior the energy delivery. The schedule predicts deviations, which represent the difference between the estimated power demand and the energy which is actually produced and released on the market. Deviations from contracted power generation cause financial penalties for market agents and, consequently, for the producers. Market agents and renewable energy producers can hedge such penalties by optimally exploiting the forecast information available.

The electricity market framework can be both a day ahead or an intraday market. A forecast with at least 36 hours lag is required for the former. Instead, to adjust deviations from the days ahead market, agents have to bid adjustments in the intraday market which requires an updated forecast with 6 hours lag. These are the most relevant time framework forecast, essential to participate in the market. On the other hand, to plan market strategic decision, agents might need more time, thus a 7 to 10 ahead days forecast may be required. In addition, the 7 to 10 days ahead forecast is used as redundancy information to cover potential lack in the forecast delivery.

Energy forecast clients are not only agents who directly bid in the market. Some of them have business models that share the risk of deviation with the producers, thus forcing the latter to provide forecast and receive payment penalized by the deviations.

The operator computes deviations by combining information about the programmed power which has been bided by the market agent and data gathered from the network, measured in the output generation in the power plant. Market agents have their own strategy to bid in the market: usually they use the energy forecast as a proposal for programmed power or, in some cases, they bid with some bias to optimize the revenue of the deviation. Most agents aggregate generation in order to reduce the relative uncertainty of the forecast. The aggregation of different types of renewables as well as the aggregation of generation in large geographical regions has more success in forecast error cancelation, with important advantage in the deviation reduction.

Each kind of renewable source provides different types of power generation forecast models. Wind forecast represents the most developed algorithm, typically forecasting for each wind farm. The errors from wind forecasting may vary between 18% to 30%, depending on the level of aggregation, meteorological conditions and geographical characteristics. Regarding photovoltaic forecast, errors may vary between 8% and 20%, errors are more significant in cloudy days and follow a seasonal pattern. Hydropower forecast is the most infrequent forecast model, in fact very few providers have this service. Also, hydropower forecast depends on the dimension of the power source and errors typically vary between 8% to 15%. More recently, producers have started to own storage capacity; in this case the control strategy benefits from forecast in terms of deviation minimization. 

In electricity market, the typical average value of deviation is about 20€/MWh, this represents 40% of the average market electricity price. A market agent who only utilizes naïve strategies usually loses 20% of his revenue. In average, with typical forecasts error, the average cost of deviation is 22%*20€/MWh for wind power generation, 12%*20€/MWh for photovoltaic and 10%*20€/MWh for hydro. An improvement of 1% in the forecast represent approximately 0.1% in revenue. Thus, the forecast is a core issue in the business models of renewable energy and electricity market.

“The combination of BaxEnergy and Smartwatt’s technologies will enable our customer to make the most revenue possible from every KWh of energy produced by their power plant”, says Dr. Massaro, CEO of BaxEnergy.

Jun 26, 2020 – Smartwatt


Smartwatt’s core competiences are energy systems optimization, from project to installation and to the asset management in real-time, covering the value chain from top to bottom. The company has a culture of future. The SMARTWATT team develops solutions that increase the efficiency of their customers’ business processes. The company mission is empowering their partner’s energy systems with the most advanced tools and processes for optimizing energy consumption, renewable energy production and maintenance operations, making energy simple, safe, affordable and sustainable. For additional info, please visit www.smartwatt.pt

About BaxEnergy

BaxEnergy develops turn-key solutions for industrial data collection and analysis and has 10 years of experience in the monitoring of the production cycle of renewable power plants. In addition to the core data collection and analysis, the company’s products integrate intelligent modules for power forecasting, energy trading and price prediction, and support for industrial-level battery storage management. The monitoring platform is being extended well outside the space of renewable energy to cover monitoring of e-vehicle charging stations and other critical segments of the national infrastructure such as transport and telecommunications.