Day‐ahead electricity pricing mechanism considering the conflict between distribution network congestion and renewable produce. (23rd November 2021)

• Record Type: Journal Article
• Authors: Zhao, Zhenghui; Cai, Wenliang; Wang, Yang; Xiong, Jun; Liu, Wenliang
• Is Part Of: International transactions on electrical energy systems. Volume 31:Number 12(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-23
• Subjects: controllable appliance -- day‐ahead pricing -- distribution use of system charge -- nonlinear optimization -- renewable resources; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.13218
• Languages: English
• ISSNs: 2050-7038

Abstract

Abstract: There is practically no published work that considers distribution network use of system (DUoS) charges as a price signal in the day ahead‐market, thus failing to establish a trade‐off between the DUoS charges and the energy procurement costs. This paper presents a new approach to optimal design of a day‐ahead pricing mechanism for managing distribution network congestion caused by renewable generation. The proposed concept of day‐ahead pricing is designed to minimize customer electricity bills taking account of line power constraints resulting from increased penetration of renewable generation. It is assumed that each user is equipped with controllable appliances and a smart meter enabling two‐way communications between suppliers and their customers. Suppliers employ an hourly demand side management strategy which considers the price signal from distribution network operators (DNOs), distributed generations (DGs) and wholesale market. A weighted average DUoS charge approach is applied in this paper, allowing DNOs to send a cost reflective use of system charge to electricity users in different locations based on their hourly predicted day‐ahead power consumption. An optimum day‐ahead pricing mechanism has been developed for DGs to manage their renewable resources to achieve revenue reconciliation and maximize generation output. Finally, power suppliers can optimally manage the controllable appliances that installed in each end user and balance the energy consumption from the main grid and DGs to minimize the electricity price. Several case studies have been conducted with a modified IEEE‐33 bus distribution network, where a large‐scale nonlinear optimization programming algorithm is applied to solve the problem. Abstract : This paper presents a new approach to optimal design of a day‐ahead pricing mechanism for managing distribution network congestion caused by renewable generation. The proposed concept of day‐ahead pricing is designed to minimize customer electricity bills taking account of line power constraints resulting from increased penetration of renewable generation.In contrast to fixed or two‐rates (peak and off‐peak) DUoS charge approaches which are applied in the current electricity market, the proposed day‐ahead charging method could provide more accurate and precise time‐varying price signals of the network usage.