Abstract-We propose and experimentally validate a process to dispatch the operation of a distribution feeder with heterogeneous prosumers according to a trajectory with 5 minutes 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 thanks 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 EPFL campus with both conventional consumption and distributed photo-voltaic generation.

In this paper, we propose a control framework for a battery energy storage system to provide simultaneously multiple services to the electrical grid. The objective is to maximise the battery exploitation from these services in the presence of uncertainty (load, stochastic distributed generation, grid frequency). The framework is structured in two phases. In a period-ahead phase, we solve an optimization problem that allocates the battery power and energy budgets to the different services. In the subsequent real-time phase the control set-points for the deployment of such services are calculated separately and superimposed. The control framework is first formulated in a general way and then casted in the problem of providing dispatchability of a medium voltage feeder in conjunction to primary frequency control. The performance of the proposed framework are validated by simulations and real-scale experiments, performed with a grid-connected 560 kWh/720 kVA Li-ion battery energy storage system.

Abstract-We propose and experimentally validate a process to dispatch the operation of a distribution feeder with heterogeneous prosumers according to a trajectory with 5 minutes 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 thanks 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 EPFL campus with both conventional consumption and distributed photo-voltaic generation.

Abstract-This paper presents a set of experimental investigations related to the dynamic behavior of supercapacitors (SCs). The experimentally observed results are then used as inputs for the development of an improved version of one of the most common SC RC-equivalent circuit models. The key improvement concerns the accurate modeling of the diffusion phenomenon of the SC residual charge during charging/discharging and rest phases. The experimental procedure needed for evaluating the parameters of the proposed model is also given. The accuracy of the obtained model is then experimentally validated for different cycles characterized by different dynamics.

In this paper, we consider the provision of primary frequency control by using battery energy storage systems (BESSs). In particular, we use a standard droop-based frequency control for a BESS where the control action (i.e. the BESS power output) consists in the contribution of two additive terms: the regulating power, proportional to the frequency deviations, and an offset term computed to manage the BESS State-of-Energy (SOE). In the context of such a control scheme, we propose a method to forecast the BESS energy for regulation needs and we show that the inclusion of such a forecast can increase the regulating power provision. Finally, we demonstrate the performance of the proposed approach by means of a real-scale experimental setup composed by a grid-connected 720 kVA/560 kWh BESS installed at the EPFL campus in Lausanne, Switzerland.