Centralised and Distributed Optimization for Aggregated Flexibility Services Provision

Abstract

The recent deployment of distributed battery units in prosumer premises offer new opportunities for providing aggregated flexibility services to both distribution system operators and balance responsible parties. The optimization problem presented in this paper is formulated with an objective of cost minimization which includes energy and battery degradation cost to provide flexibility services. A decomposed solution approach with the alternating direction method of multipliers (ADMM) is used instead of commonly adopted centralised optimization to reduce the computational burden and time, and then reduce scalability limitations. In this work we apply a modified version of ADMM that includes two new features with respect to the original algorithm: first, the primal variables are updated concurrently, which reduces significantly the computational cost when we have a large number of involved prosumers; second, it includes a regularization term named Proximal Jacobian (PJ) that ensures the stability of the solution. A case study is presented for optimal battery operation of 100 prosumer sites with real-life data. The proposed method finds a solution which is equivalent to the centralised optimization problem and is computed between 5 and 12 times faster. Thus, aggregators or large-scale energy communities can use this scalable algorithm to provide flexibility services.

A Study on Distributed Optimization over Large-Scale Networked Systems

“…ere are many early studies done on the method of multipliers and ADMM [63,64]. Some recent studies done on ADMM can be found in [65][66][67][68][69]. In [65], Erseghe has proposed a fully distributed algorithm for optimal power flow using ADMM.…”

“…In this paper, the author has introduced another variation on ADMM Algorithm 1 with assumptions such as g(y) � 0, where y is contained in a linear space with associated orthogonal projector and also with certain assumptions on initial choices. In the study [66], authors have presented a decomposed solution approach with ADMM to solve a cost minimization problem, where the objective consists of energy and battery degradation cost. is work has used a modified version of ADMM, which helps to reduce the computations cost and ensures the stability of the solution.…”

Towards Flexibility Trading at TSO-DSO-Customer Levels: A Review

“…Prosumers could also trade their flexibility with an upstream entity such as an aggregator. Reference [82] proposed a method to provide flexibility services for aggregators in large-scale energy communities. A bottom-up decentralized approach has been used for trading energy among customers and aggregators in [83][84][85].…”

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

“…Even if a centralized optimization offers the best optimality assurances [7], it comes to be intractable for a high number of batteries, mainly due to the high number of discrete variables and to requirements related to the memory and computational time [10]. Some authors also consider the requirement to not disclose the local private information of each user participating in the aggregation [10][11][12] The authors in [10] propose a distributed methodology for the optimal coordination of Distributed Energy Resources (DERs). The proposed MILP approach is based on Dantzig-Wolfe decomposition and column generation.…”

“…Other researches propose methods to achieve the scalability of a large number of storage devices [12,13] and assume that the system operator evaluates, also based on operating costs, the required flexibility to solve a problem in the distribution or transmission system and that it is supported by an aggregator. In [12] the alternating direction method of multipliers (ADMM) is proposed for furnishing energy flexibility to the DSO considering the optimal operation of one hundred prosumers. Flexibility requests are sent by the DSO to the aggregator that should determine the best solutions for achieving the flexibility request while reducing the operational costs.…”