Distributed energy resources (DERs) are transforming power networks, challenging traditional operational methods, and requiring new coordination mechanisms. To address this challenge, this paper introduces SecuLEx (Secure Limit Exchange), a market-based paradigm for allocating and trading power injection and withdrawal limits, known as dynamic operating envelopes (DOEs). Under this paradigm, distribution system operators (DSOs) first assign initial DOEs to customers through a fair allocation mechanism. These limits can be exchanged afterward through a market, allowing customers to reallocate them according to their needs while ensuring network operational constraints. We formalize SecuLEx and illustrate DOE allocation and market exchanges on a small-scale low-voltage (LV) network. In this case study, SecuLEx reduces renewable curtailment and improves grid utilization and social welfare compared to traditional approaches.
Achieving universal electricity access remains a global challenge, particularly in remote rural areas where grid extension is technically or economically unfeasible. Existing approaches provide cost-optimal and technically feasible solutions for decentralized energy system design, but often fall short in delivering context-sensitive electrification strategies that combine microgrids and stand-alone systems while accounting for social and operational constraints. This paper proposes a socially informed optimisation framework for rural electrification planning, capable of generating alternative system configurations across different electricity consumption scenarios. The framework integrates solar PV generation, battery energy storage, and diesel backup, and incorporates hourly demand profiles together with socially informed constraints to enhance system manageability and reflect the electricity adoption process in rural areas. Methodologically, the proposed planning framework is built around a Mixed-Integer Linear Programming (MILP) optimization model, integrated within a heuristic procedure to efficiently generate near-optimal electrification layouts and system designs under different social and operational preferences. The approach is applied to the rural community of Molle Orcko in Raqaypampa, Bolivia. Results demonstrate the framework's ability to adapt electrification strategies to varying community priorities and highlight the importance of jointly considering technical and social dimensions in decentralized energy planning.
Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes.
