Load Leveling and Dispatchability of a Medium Voltage Active Feeder through Battery Energy Storage Systems: Formulation of the Control Problem and Experimental Validation

Emil Namor, Mario Paolone, Fabrizio Sossan
2016
Article de conférence

This paper proposes and experimentally validates a control algorithm for a grid-connected battery energy storage system (BESS) to level the consumption of a group of prosumers and dispatch their aggregated operation. The control strategy is layered in a two-stage procedure: day-ahead and intra-day operation. During day-ahead operation, the load leveled power consumption profile is determined by applying a scenario-based robust optimization using historical measurements of the aggregated feeder power consumption. In the intra-day phase, the operation of the group of prosumers is dispatched according to the profile defined during the day-ahead stage, which becomes the so-called dispatch plan. The dispatch plan is tracked in real-time by properly adjusting the injections of the BESS using model predictive control (MPC). The proposed control process is experimentally validated using a 750 kW/500 kWh BESS.

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Emil Namor, Mario Paolone, Fabrizio Sossan
2016
Article de conférence

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https://infoscience.epfl.ch/record/217992?ln=fr

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Control of a Battery Energy Storage System Accounting for the Charge Redistribution Effect to Dispatch the Operation of a Medium Voltage Feeder

Emil Namor, Mario Paolone, Fabrizio Sossan, Dimitri Torregrossa

We describe a process to dispatch the operation of a medium voltage distribution feeder and improve its quality-of-service using a battery energy storage system (BESS). It is organized according to a day-ahead and intra-day structure to allow the integration with electricity markets. In the former stage, the average power transit on a 5-minute resolution is determined for the next day of operation using adaptive black-box forecasting. In the latter stage, the feeder operation is dispatched according to the previously determined trajectory. The resulting tracking problem is accomplished by using the BESS to compensate for deviations from the dispatched plan, which are likely to occur due to forecasting errors. For the first time in the literature, the control strategy is realized using model predictive control (MPC) accounting for the battery charge redistribution effect. This phenomena is described using a state-of-the-art lithium battery model. A simulated proof-of-concept is given.

IEEE2015

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Achieving the Dispatchability of Distribution Feeders Through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage

Emil Namor, Mario Paolone, Fabrizio Sossan

We propose and experimentally validate a process to dispatch the operation of a distribution feeder with heterogeneous prosumers according to a trajectory with 5 min resolution, called dispatch plan, established the day before the operation. The controllable element is a utility-scale grid-connected battery energy storage system (BESS) integrated with a minimally pervasive monitoring infrastructure. The process consists of two stages: day-ahead, where the dispatch plan is determined by using forecast of the aggregated consumption and local distributed generation (prosumption), and real-time operation, where the mismatch between the actual prosumption realization and dispatch plan is compensated for thanks to adjusting the real power injections of the BESS with model predictive control (MPC). MPC accounts for BESS operational constraints thank to reduced order dynamic grey-box models identified from online measurements. The experimental validation is performed by using a grid-connected 720 kVA/500 kWh BESS to dispatch the operation of a 20-kV distribution feeder of the École Polytechnique Fédérale de Lausanne campus with both conventional consumption and distributed photo-voltaic generation.

Ieee-Inst Electrical Electronics Engineers Inc2016

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Battery Storage System Optimal Exploitation Through Physics-Based Model Predictive Control

Emil Namor, Mario Paolone, Fabrizio Sossan, Dimitri Torregrossa

Traditionally, the safe operation of a battery energy storage system (BESS) is achieved by imposing conservative constraints on its DC bus current and voltage. By using a computationally efficient single particle model (SPM), we propose to replace these constraints with the battery internal ion concentrations and electrical potentials in order to avoid these quantities to exceed hazardous limits. Indeed, the in-depth knowledge of the BESS internal states provided by the SPM, enhances the awareness of a control action and allows for a better exploitation of the BESS energy and power capabilities, while maintaining safe operational conditions. The target application is composed by a model predictive control (MPC) applied to a MW-class grid-connected BESS responsible to dispatch the operation of a medium voltage (20 kV) feeder interfacing heterogeneous loads and distributed generation. The performance of the proposed MPC are assessed and compared with respect to a traditional approach constraining the BESS DC bus current and voltage.

IEEE2017

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