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The increasing attention to environmental issues is forcing theimplementation of novel energy models based on renewable sources, fundamentallychanging the configuration of energy management and introducing newcriticalities that are only partly understood. In particular, renewableenergies introduce fluctuations causing an increased request of conventionalenergy sources oriented to balance energy requests on short notices. In orderto develop an effective usage of low-carbon sources, such fluctuations must beunderstood and tamed. In this paper we present a microscopic model for thedescription and the forecast of short time fluctuations related to renewablesources and to their effects on the electricity market. To account for theinter-dependencies among the energy market and the physical power dispatchnetwork, we use a statistical mechanics approach to sample stochasticperturbations on the power system and an agent based approach for theprediction of the market players behavior. Our model is a data-driven; itbuilds on one day ahead real market transactions to train agents behaviour andallows to infer the market share of different energy sources. We benchmark ourapproach on the Italian market finding a good accordance with real data.

Green power grids: how energy from renewable sources affects network and markets