Comparison of economic model predictive control and rule‐based control for residential energy storage systems. Issue 5 (6th October 2020)

• Record Type: Journal Article
• Authors: Banfield, Brendan; Robinson, Duane A.; Agalgaonkar, Ashish P.
• Is Part Of: IET smart grid. Volume 3:Issue 5(2020)
• Page Start: 722
• Page End: 729
• Publication Date: 2020-10-06
• Subjects: predictive control -- tariffs -- battery storage plants -- distributed power generation -- photovoltaic power systems -- demand side management -- distribution networks -- energy storage; economic model predictive control -- rule‐based control -- residential energy storage systems -- residential solar PV -- time‐of‐use demand tariff -- battery life‐cycle costs -- control system -- residential load -- EMPC controller -- rule‐based controller -- annual economic performance -- battery energy throughput -- 10 residential customers -- 30 residential customers; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2020.0090
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : This study quantifies the benefits of implementing model predictive control on residential solar PV and energy storage systems considering a time‐of‐use demand tariff, feed‐in tariff and varying PV system sizes and battery life‐cycle costs. The control system analysed makes use of economic model predictive control (EMPC) whereby the objective function is directly tied to the economics of the system. Using residential load and PV data from an Australian distribution network service provider, the EMPC controller is compared to a rule‐based controller, highlighting the benefits of EMPC in regards to annual economic performance and battery energy throughput. The EMPC algorithm is then tested using 10 residential customers at the low voltage feeder level showing the capacity for the EMPC controller to shift peak demand and flatten the aggregated load profile of 30 residential customers.