Further integration of distributed renewable energy sources in distribution systems requires a paradigm change in grid management by the distribution system operators (DSO). DSOs are currently moving to an operational planning approach based on activating flexibility from distributed energy resources in day/hour-ahead stages. This paper follows the DSO trends by proposing a methodology for active grid management by which robust optimization is applied to accommodate spatial-temporal uncertainty. The proposed method entails the use of a multi-period AC-OPF, ensuring a reliable solution for the DSO. Wind and PV uncertainty is modeled based on spatial-temporal trajectories, while a convex hull technique to define uncertainty sets for the model is used. A case study based on real generation data allows illustration and discussion of the properties of the model. An important conclusion is that the method allows the DSO to increase system reliability in the real-time operation. However, the computational effort grows with increases in system robustness.

Wind power generation is to play an important role in supplying electric power demand, and will certainly impact the design of future energy and reserve markets. Operators of wind power plants will consequently develop adequate offering strategies, accounting for the market rules and the operational capabilities of the turbines, e.g., to participate in primary reserve markets. We consider two different offering strategies for joint participation of wind power in energy and primary reserve markets, based on the idea of proportional and constant splitting of potentially available power generation from the turbines. These offering strategies aim at maximizing expected revenues from both market floors using probabilistic forecasts for wind power generation, complemented with estimated regulation costs and penalties for failing to provide primary reserve. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of these offering strategies. An important conclusion is that, even though technically possible, it may not always make sense for wind power to aim at providing system services in a market environment.

The energy sector transition to more decentralized and renewable structures requires greater participation by local consumers, which may be enabled by innovative models such as the setup of renewable energy communities (RECs). To maximize the self-consumption of local renewable energy generated by assets normally connected to the low voltage distribution grid, these RECs typically involve jointly owned assets such as collective photovoltaic solar panels (CPVs) and collective energy storage systems (CESS). This work proposes a novel mathematical model for a REC, accounting for three distinct economic approaches to the redistribution of collective benefits among community members. The main objective of this study is to understand how the participation of community members in collective assets (CAs) can help increase the fairness and equity of RECs. An illustrative REC case comprising members with individual and collective ownership of the assets is used to assess the proposed economic approaches. Extracting several answers, among them that the most advantageous configuration comes from agents with quotas in the CESS and CPV. An important conclusion is that depending on the selected economic approach, the social welfare and agent’s revenue vary significantly. In any case, CESSs increase equity among REC members.