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

We propose and experimentally validate a control strategy to dispatch the operation of a distribution feeder interfacing heterogeneous prosumers by using a grid-connected battery energy storage system (BESS) as a controllable element coupled with a minimally invasive monitoring infrastructure. It consists in a two-stage procedure: day-ahead dispatch planning, where the feeder 5-minute average power consumption trajectory for the next day of operation (called \emph{dispatch plan}) is determined, and intra-day/real-time operation, where the mismatch with respect to the \emph{dispatch plan} is corrected by applying receding horizon model predictive control (MPC) to decide the BESS charging/discharging profile while accounting for operational constraints. The consumption forecast necessary to compute the \emph{dispatch plan} and the battery model for the MPC algorithm are built by applying adaptive data driven methodologies. The discussed control framework currently operates on a daily basis to dispatch the operation of a 20~kV feeder of the EPFL university campus using a 750~kW/500~kWh lithium titanate BESS.Comment: Submitted for publication, 201

Advanced models and algorithms to provide multiple grid services with battery storage systems

Battery energy storage systems (BESSs) are expected to play a major role in the power grid of the near future. These devices, capable of storing and returning electrical energy, are valuable assets to a grid that integrates more and more distributed, intermittent and renewable generation. Compared to renewable energy sources, however, battery storage systems are still in an early stage of deployment and the way to exploit them in an optimal way is still subject of research. In this respect, this thesis develops two lines of investigation to reach an optimal utilisation of these devices. In its first part, the thesis proposes a control framework to operate a utility-scale BESS connected to a distribution feeder. This control framework allows to provide a set of services: dispatch of the operation of such feeder, load levelling, frequency response. It is structured in a period-ahead and a real-time phase. The former plans the BESS operation for a given time horizon through the solution of optimization problems. These take into account the BESS state of energy as well as forecast scenarios of quantities such as the feeder prosumption and of the BESS energy needs due to the frequency response service. The real-time phase determines the BESS power injections a resolution as fast as 1 second and, in the case of the dispatch, relies on model predictive control. Moreover, the thesis proposes the formulation of a framework for the simultaneous deployment of multiple services. The objective of this is to maximise the BESS exploitation in the presence of uncertainty. All the proposed methods are validated experimentally, on the 560 kWh/720 kVA BESS installed on EPFL campus. This extensive validation demonstrates their effectiveness and deployability. In its second part, the thesis discusses the integration of electrochemical models in the control of BESSs. Such models, compared to more conventional equivalent circuits or empirical ones, can provide deeper insight in the processes occurring within Li-ion cells - the founding elements of BESSs - and by consequence a more effective operation of BESSs. The thesis proposes a method to identify the parameters of one of such models - the single particle model - and, again, validates it experimentally. Moreover, in its final chapter, the thesis provides a proof-of-concept by simulations of the advantages of the integration of electrochemical models in the control framework proposed in its first part and, in general, in BESS control

Quantification of Primary Frequency Control Provision from Battery Energy Storage Systems Connected to Active Distribution Networks

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

Assessment of Battery Ageing and Implementation of an Ageing Aware Control Strategy for a Load Leveling Application of a Lithium Titanate Battery Energy Storage System

The manuscript describes a method to embed into a battery energy storage system (BESS) control strategy the performance degradation associated with the battery operation. In particular, the proposed method aims at minimizing the degra- dation of the BESS electrochemical cells. A load leveling strategy is described as a case study and the ageing effects associated with the battery current extraction are embedded as constraints into the optimization problem. The main contributions of the work, compared to the existing literature are: i) the degradation process is formulated as a weighted energy throughput, thus taking into account the C-rate effect on the degradation phenomena; ii) the performance of the proposed control strategy has been applied to a large scale lithium-titanate BESS of 280 kWh interfaced to a 20 kV active distribution network

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

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

Improvement of Dynamic Modeling of Supercapacitor by Residual Charge Effects Estimation

The paper presents a set of experimental investigations related to the dynamic behavior of supercapacitors. The experimentally observed results are then used as inputs for the development of an improved version of one of the most common supercapacitor RC-equivalent circuit models. The key improvement concerns the accurate modeling of the diffusion phenomenon of the supercapacitor 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

A Receding Horizon Control Approach For Re-Dispatching Stochastic Heterogeneous Resources Accounting for Grid and Battery Losses

In this paper, we propose a re-dispatch scheme for radial distribution grids hosting stochastic Distributed Energy Resources (DERs) and controllable batteries. At each re-dispatch round, the proposed scheme computes a new dispatch plan that modifies and extends the existing one. To do so, it uses the CoDistFlow algorithm and applies a receding horizon control principle, while accounting for hard time computation constraints that impact on the instantaneous update of a dispatch plan. CoDistFlow handles stochastic DERs and prosumers uncertainties via scenario-based optimization and the non-convexity of the AC Optimal Power Flow by iteratively solving suitably defined convex problems until convergence. We perform numerical evaluations based on real-data, obtained from a real Swiss grid. We show that, with our proposed re-dispatch scheme, the daily dispatch tracking error can decrease more than 80%, even for small battery capacities, and if re-dispatch is frequent enough, it can be eliminated. Finally, we show that re-dispatch should be performed as often as the market allows and the performance continues to improve

Dispatching active distribution networks through electrochemical storage systems and demand side management

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. In particular, the main objective is to track a 5-minute resolution trajectory, called the \textit{dispatch plan} that is computed one day before the beginning of operation. During real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan. This is achieved by modulating the power consumption of a grid-connected battery energy storage system (BESS) and of the HVAC system of a commercial controllable building (CB). To this end, a hierarchical multi-time-scale controller is designed to coordinate the two entities while requiring a minimal communication infrastructure. The effectiveness of the proposed control framework is demonstrated by means of a set of full-day experimental results on the 20kV distribution feeder of the EPFL campus that is comprised of: 1) a set of uncontrollable resources represented by 5 office buildings (350kWp) and a roof-top PV installation (90kWp) 2) a set of controllable resources, namely, a grid-connected BESS (720kVA-500kWh), and a fully-occupied multi-zone office building (45 kWp)

Coordinamento dell'isolamento di una sottostazione ibrida a 220kV - Confronto tra analisi analitica secondo norma IEC e simulazioni numeriche

L'elaborato analizza il coordinamento dell'isolamento della sottostazione elettrica di una centrale idroelettrica. Tale analisi viene svolta applicando i metodi descritti nella norma IEC 60071. In seguito è sviluppato un modello numerico della sottostazione per valutare più nel dettaglio le sovratensioni. Attraverso il confronto tra questi due studi è analizzato l'apporto che l'esecuzione di simulazioni numeriche può dare nello studio del coordinamento dell'isolamento di un impiant