Article révisé par les pairs
| Résumé : | This paper explores why energy-sharing communities need policy support via network tariff adjustments and how to optimally design that support. Findings from a case study indicate that, even with high self-consumption, the energy-sharing model may not ensure participants reach break-even. Counterfactual analyses, using machine-learning techniques, indicate that capacity-term adjustments alone had minimal impact on peak consumption. Policy recommendations suggest limiting capacity-term adjustments to communities capable of actively managing peak loads through real-time data and flexible assets. |
