Optimal midterm peak shaving cost in an electricity management system using behind customers' smart meter configuration. (1st February 2021)

• Record Type: Journal Article
• Authors: Nieta, Agustín A. Sánchez de la; Ilieva, Iliana; Gibescu, Madeleine; Bremdal, Bernt; Simonsen, Stig; Gramme, Eivind
• Is Part Of: Applied energy. Volume 283(2021)
• Publication Date: 2021-02-01
• Subjects: Electricity management system -- Energy storage system -- Local load -- Decentralised PV production -- Peak shaving service -- Prosumer -- Stochastic mixed-integer linear problem; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.116282
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: This paper analyses a local electricity system (LES) comprising photovoltaic production (PV), a connection to the distribution network, local loads and an energy storage system (ESS). Given the flexibility of the ESS, the LES can provide a peak shaving service (PSS) to the grid operator based on the actual monthly power tariff. This paper proposes a stochastic mixed-integer linear programming problem that maximises the expected operating profit of the LES midterm. Assuming a behind customers' smart meter configuration, income is derived from selling the energy of prosumers to other external electrical areas. If the costs are higher than the income, the net profit will be negative, i.e. a net loss. The cost component of the objective function can be reduced through the management of local resources and by providing PSS to the distribution network operator to minimise the power cost of the monthly power tariff. The model is tested for 720 h (considering a month of 30 days) in three cases: (i) without PV and ESS; (ii) with PV and ESS, where losses are 0%; (iii) with PV and ESS, where losses are 18%. Due to the monthly power tariff, the net loss of the LES is reduced through the optimal management of local resources when the ESS losses are lower than 18%. To assess seasonal implications about the LES, the 12 months of the year are also tested. The month of October indicated the highest peak shaving, while the lowest peak shaving depended on the ESS losses. Highlights: Local energy system behind customers' smart meter configuration. Smart energy management system of local PV production, load and energy storage. Midterm peak shaving service to minimise the distribution network cost. A stochastic programming model to evaluate the new smart energy management system. Seasonal study of the operation of the local energy system.