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Fig. 3 | Energy Informatics

Fig. 3

From: Reinforcement learning in local energy markets

Fig. 3

The Degree of Local Sufficiency of sensitivity analysis of all the scenarios. Figure 3 refers to the sensitivity analysis of the degree of Local Sufficiency for all the combination of technical and regulatory scenarios. The undesirable sensitivity i.e low DLS is denoted in red color, and as the DLS increases through the heat map, the desirable DLS i.e a high DLS in demonstrated in green color with intermediate values denoted with a color transition from red to green with increasing DLS. It can be observed that the DLS increases with both increasing the local PV production and also by increasing the degree of DR. In the Public Network scenarios without DR, the DLS increases by 6,1% from 22.1% to 28,2% as we increase the PV installation from 5kWp to 25kWp because more energy generation leads to more self-consumption. The implementation of trading in Favorable Regulation scenario provides a bigger window for trading which leads to increase in consumption of electricity generated locally in the LEM, which in turn, increases the DLS by 9,3% for 5kWp installation to 26,9% for 25kWp installation in comparison to the corresponding base case scenarios. In the Microgrid scenario, the DLS increases by 19,1% for 5kWp and 27,4% for 25kWp installation and in Favorable regulation scenario, the DLS increases by 15,2% for 5kWp and 24,1% for 25kWp as we increase DR% from 0%–50%. For the cases where purchase of local generation is enforced, the Public Network scenario shows the increment of DLS without trading to 41,2% for 5kWp PV installation to 57,4% for 25kWp installation. The effect of trading can be visualized in case of the Microgrid scenario in combination with Upper bound scenario where the DLS increases by 13% for 5kWp to 25,9% for 25kWp installation. However, a further relation of regulations does not increase the DLS as can be observed in Favorable regulation cases in comparison with the corresponding Microgrid cases

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