Enhancing the dispatchability of distribution networks through utility-scale batteries and flexible demand

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan, which is computed the day before the beginning of operation. In this paper, we propose a method to optimally compute the dispatch plan so as to optimize the operation of the feeder while making sure to allocate enough local reserves to absorb deviations of the realizations. Indeed, 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 utility-scale battery energy storage system and of the heating, ventilation and air conditioning system of a commercial controllable building. To this end, a hierarchical controller is designed to coordinate these two controllable entities while requiring a minimal communication infrastructure. Due to the inherent different response times of these systems, the power injection of the electrical battery is controlled at a sub-minute time-scale so as to absorb high-frequency tracking errors and, therefore, deliver the dispatch service. At a slower time-scale, the controllable building is controlled to maintain the state of charge for the electrical battery at a scheduled level by means of a model predictive controller. The model predictive controller is designed in order to account for both comfort and operational constraints of the controllable building, as well as power limits for the electrical storage. The effectiveness of the proposed control framework is demonstrated by means of both an extensive simulation analysis, as well as a set of 12 full day experimental results on the 20 kV distribution feeder in the campus of the Swiss institute of technology in Lausanne, that is comprised of: 1) A set of uncontrollable resources represented by five office buildings (350 kWp) and a roof-top photovoltaic installation (90 kWp), 2) a set of controllable resources, namely, a grid-connected electrical storage (720 kVA–500 kWh), and a fully-occupied multi-zone office building (45 kWp).

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

Luca Fabietti, Tomasz Tadeusz Gorecki, Colin Neil Jones, Emil Namor, Mario Paolone, Fabrizio Sossan

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).

2017

Real-Time Control Framework for Active Distribution Networks Theoretical Definition and Experimental Validation

Lorenzo Enrique Reyes Chamorro

The great challenge of massively integrating the volatile distributed power-generation into the power system is strongly related to the evolution of their operation and control. The literature of the last decade has suggested two models for such an evolution: (i) the supergrid model, based on enhanced continental/intercontinental network interconnections (mainly DC) for bulk transmission, (ii) the microgrid mode, where small medium/low voltage networks interfacing heterogeneous resources, such as local generation, energy storage and active customers, are intelligently managed so that they are operated as independent cells capable of providing different services from each other and operate in islanded mode. Irrespective of the model that will eventually emerge, the control of heterogeneous distributed resources represents a fundamental challenge for both supergrid and microgrid models. This requires the definition of scalable and composable control methods that guarantee the optimal and feasible operation of distribution grids in order to satisfy local objectives (e.g., distribution grid power balance), as well as the provision of ancillary services to the external bulk transmission (e.g., primary and secondary frequency supports). Several control methodologies have been proposed to achieve these goals, and the majority of them have been inspired by the classic time-layered approach traditionally adopted in power systems that are associated with different time-scales and extension of the controlling area, i.e. primary, secondary and tertiary controls, ranging from sub-seconds to hours, respectively. In the context of microgrids, these three levels of control can be associated with a decision process that can be centralized (i.e., a dedicated central controller decides on the operation of the system resources) and/or decentralized (each element decides based on its own rules). In the current literature, the former is used for long-term, whereas the latter for short-term decisions. In particular, primary controls are typically deployed through fully decentralized schemes mainly relying on the use of droop control. With this in mind, in this thesis we propose, and experimentally validate, a novel control framework called COMMELEC â A Composable Framework for Real-Time Control of Active Distribution Networks, Using Explicit Power Set-Points. It controls a power grid in real-time based on a multi-agent structure, using a simple and low-bandwidth communication protocol. Such a framework enables a controller to easily steer an entire network as an equivalent energy resource, thus making an entire system able to provide grid support by exploiting the flexibility of its components in real-time. The main features of the framework are (i) that it is able to indirectly control the reserve of the storage systems, thus maximizing the autonomy of the islanding operation, (ii) that it keeps the system in feasible operation conditions and better explores, compared to traditional techniques, the various degrees of freedom that characterize the system, and (iii) that it maintains the system power-equilibrium without using the frequency as a global variable, even being able to do so in inertia-less systems. Our framework has been extensively validated, first by simulations but, more importantly, in a real-scale microgrid laboratory specially designed and setup for this goal. This is the first real-scale experiment that proves the applicability of a droop-less explicit power-flow control mechanism in microgrids.

EPFL2016

Model Predictive Control Strategies for Polygeneration systems and microgrids

Ramanunni Parakkal Menon

Increasing electricity and thermal demand in all sectors, an increasing focus on the reduction in carbon emissions and use of nuclear power, advent of distributed generation and greater use of renewable technologies on an aging electrical and thermal grid system has necessitated the need for modern control and management systems. These new control and management systems need to be able to integrate new technologies, stochasticities and maximise the utilisation of the existing infrastructure while satisfying demands, without requiring complete overhaul of the pre-existing centralised grid system and the transmission and distribution systems. A model predictive control system has been proposed and demonstrated here which is able to create strategies for thermal and electrical systems such that the grid efficiency and security is maintained while minimising resource usage and emissions, while, simultaneously reducing the operating costs in the grid. The model predictive control(MPC) utilises a fully energetic approach for low-voltage microgrids and houses in the residential and commercial sector which comprises of CHP units, heat pumps, storage systems(electric and thermal) and stochastic renewable resources, while accounting for the varying dynamics of the electrical and thermal systems. Finally, validation of the MPC is performed on a testbed with physical units and building emulators which have access to meteorological and resource market data. The capability of the MPC to provide strategies for systems with photovoltaics (PV), heat pumps and CHP units is demonstrated. The MPC implementation developed is input into an optimal system design algorithm based on a multi-objective optimisation genetic algorithm developed for microgrids and urban systems/grids with end-users and polygeneration systems and storage devices. The optimal design of the system is so that the optimal sizes of the polygeneration systems can be identified. This will help in maximising the utilisation of heat pumps, storage devices and other systems in a LV microgrid equipped with an MPC-based thermo-electric energy management system. The work also aims to compare the cost effectiveness versus ability of thermal storage devices compared to electrical storage devices for the same grid in question.