Assessing the Scalability and Privacy of Energy Communities by Using a Large-Scale Distributed and Parallel Real-Time Optimization

Abstract

In the context of the energy transition, energy communities are gaining increasing attention all over the world, in recent years. By participating in an energy community, prosumers may take a leading role in the energy transition and improve the self-consumption of renewable energy produced inside the community. Prosumers can carry out energy exchanges inside the energy community and provide ancillary services to the system operators, thus contributing to improve the efficiency and stability of the grid. A novel scalable, privacy-preserving, and real-time distributed parallel optimization is proposed to manage a largescale energy community, considering energy exchanges inside the community according to the model of virtual self-consumption and the provision of ancillary services. The proposed method preserves the privacy of prosumers and allows the assessment of the impact of energy exchanges on the ancillary services provided by an energy community. Simulation results confirmed that the proposed method is superior in terms of privacy if compared with the equivalent centralized optimization and that it has a convergence rate higher than that of the splitting conic solver (SCS).

Construction and Application of Distributed Power Storage System

“…The power supply LAN is composed of power grids, substations, etc., which connects power plants and power companies for load transmission through satellite positioning equipment [11][12].…”

Cloud Energy Storage Investment by Collaboration of Microgrids for Profit and Reliability Enhancement Considering a TSO-DSO Yearly Reward

“…This paper considers a yearly reward mechanism for supporting the CES project. As mentioned in [39], even a prosumer inside an energy community can increase its profit by providing ancillary services for DSO and TSO. Hence, it is normal that we assume that a grid-scale CES project can receive a yearly reward.…”

“…Also, the reliability of each investment scenario is analyzed based on the energy not supplied (ENS) index as one of the main criteria for the decision-making of MGs. Following the CES investment scenario block, DSO assesses each scenario based on peak shaving and the impact on the total cost reduction of the distribution system and assigns yearly rewards (𝑅 𝑖 𝐷 ) to each of the CES investment scenarios according to equation (39).…”

“…It should be noted that this relaxation had no effect on the optimal solution obtained. In other words, the best answer to the microgrid scheduling problem will be the same when both the equality requirement (38) and the inequality constraint (39) are taken into consideration. This is because reducing the objective function also minimizes the magnitude of the current flow in distribution lines (𝑓 𝑚𝑛,𝑡 𝐿 ), which includes the cost of energy losses.…”

“…The mathematical model can be made more tractable by using the relaxation mentioned. As can be observed, the model changed into a convex non-linear problem when (39) was expressed as the second-order conic constraint.…”