A Scalable Privacy Preserving Distributed Parallel Optimization for a Large-Scale Aggregation of Prosumers With Residential PV-Battery Systems

Abstract

A novel scalable and privacy-preserving distributed parallel optimization that allows the participation of large-scale aggregation of prosumers with residential PV-battery systems in the market for the ancillary service (ASM) is proposed in this paper. To consider both reserve capacity and reserve energy, day-ahead and real-time stages in the ASM are considered. A method, based on hybrid Variable Neighborhood Search (VNS) and distributed parallel optimization is designed for the day ahead and realtime optimization. Different distributed optimization methods are compared and designed and a new distributed optimization method based on Linear Programming (LP) is designed that overcomes previous methods based on integer and Quadratic programming (QP). The proposed LP-based optimization can be easily coded up and implemented on microcontrollers and connected to a designed Internet of Things (IoT) based architecture. As confirmed by simulation results, carried out considering different realistic case studies, both day-ahead and real-time proposed optimization methods, by allocating the computational effort among local resources, are highly scalable and fulfil the privacy of prosumers.

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

“…Centralized methods, however, involve a central coordinator and may suffer in some cases as in [4], from the issue of privacy. Considering the benefits, objectives, and challenging issues related to the management of the energy community and the scalability and privacy requirements, distributed optimization methods for energy management have recently gained a growing interest [12]- [13]. Column generation and Dantzig-Wolfe decomposition is considered in [12] where a Mixed-Integer Linear Programming (MILP) optimization model is proposed to optimally coordinate Distributed Energy Resources (DERs).…”

Cascade computing model to optimize energy exchanges in prosumer communities

“…The authors of [10] , [11] , [12] cover several topics regarding the management of prosumer communities, including the analysis of prosumers' energy behavior profiles, the development of a framework to manage multiple goals, and a methodology to form the PCGs. In [13] , innovative scalable and privacy-preserving optimization methods are proposed, which allow large-scale energy communities to offer ancillary services through the sharing of residential PV-battery systems. In [14] , the authors focus on the issue of optimally exploiting the energy storage systems deployed in a PCG, where the objective is to reduce the energy consumption and the carbon emissions.…”

Impact assessment framework of PV‐BES systems to active distribution networks

“…These CSs have been employed to demonstrate the application of the proposed assessment framework under specific network operating conditions. Nevertheless, the proposed framework is generalized, thus different types of BES control schemes, management strategies (aggregated or individual) and optimization techniques for BES utilization [34–36] can be incorporated to evaluate their effectiveness and applicability under different cases. The examined CSs are further discussed in detail: BES CS1: This CS is widely used by prosumers to maximize their self‐consumption.…”