Transitioning electricity grids to renewable sources of energy involves building more solar and wind farms, but also requires new mathematical tools to plan around the unpredictably intermittent nature of sun and wind, according to researchers recently awarded a $3.5-million grant from the U.S. Department of Energy to develop such tools.
Transitioning electricity grids to renewable sources of energy involves building more solar and wind farms, but also requires new mathematical tools to plan around the unpredictably intermittent nature of sun and wind, according to researchers recently awarded a $3.5-million grant from the U.S. Department of Energy to develop such tools.
"Everybody wants to move to renewables, but these technologies introduce new complications and uncertainties," said Ronnie Sircar, chair of Princeton University's Department of Operations Research and Financial Engineering. Quantifying that uncertainty will not only help grid operators deploy renewables more efficiently, but will allow creation of financial tools, such as insurance products, that minimize risks and spur investments, Sircar said.
Conventional forecasting methods make it difficult for renewable energy suppliers to know exactly how much to charge for their electricity and difficult for grid operators to choose what energy sources to buy. Other markets, such as stocks, oil and housing, have well-established methods to quantify uncertainty. That allows investors to offer insurance that smooths out risks and encourages more investment.
"We are bringing financial thinking, risk quantification into this area," Sircar said.
Read more at Princeton University
Image: A Princeton research team was among 11 research groups nationwide selected by the Energy Department to develop methods to manage risk and optimize markets for renewable energy. CREDIT: Princeton University
