Optimal participation of prosumers in energy communities through a novel stochastic-robust day-ahead scheduling model. (May 2023)

• Record Type: Journal Article
• Authors: Tostado-Véliz, Marcos; Rezaee Jordehi, Ahmad; Icaza, Daniel; Mansouri, Seyed Amir; Jurado, Francisco
• Is Part Of: International journal of electrical power & energy systems. Volume 147(2023)
• Publication Date: 2023-05
• Subjects: Energy community -- Peer-to-peer -- Prosumer -- Smart home -- Smart grid; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108854
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A novel home energy management tool for optimal integration of prosumers in energy communities is developed. The new proposal is based on a novel stochastic-robust formulation to account for heterogeneous uncertainties. Trading with different agents within communities is modelled and analysed. Storage assets are of vital importance to increment the exportable capacity of the dwelling. Trading with the community and other peers are normally preferable but highly affected by uncertainties. Abstract: With the advent of smart grids, novel businesses like energy communities are becoming more frequent, thus enabling alternative energy transactions for smart prosumers like peer-to-peer mechanisms, that may increment the efficiency of residential installations while reducing the electricity bill. However, the optimal participation in such frameworks is a formidable challenge because the multiple uncertainties involved and energy paths enabled, which increments the number of decision variables and pricing mechanisms. This paper addresses this issue by developing a novel day-ahead scheduling model for prosumers integrated in energy communities based on a stochastic-robust approach. The developed formulation contemplates energy transactions with the utility grid, the community and other peers, besides the intrinsic uncertainties that arise from these processes. The heterogeneity of the unknown parameters is effectively addressed by using different uncertainty models, thus, while the predictable parameters are modelled using robust formulation, the highly volatile uncertainties are treated via scenarios. A case study is presented with the aim of validating the new tool as well as analyse the different energy transactions and their monetary implications. The obtained results evidence the important role of storage assets in reducing the electricity bill by 86 %, which is achieved by incrementing the exportable capacity of the dwelling by 84 %. The impact of uncertainties is also studied, expecting more pessimistic profiles at expenses of incrementing the monetary cost in 0.37-$.