In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous resources while respecting the local grid constraints on nodal voltages and lines ampacities. The framework consists of two algorithmic layers. In the first one (day-ahead scheduling), we determine an aggregated dispatch plan. In the second layer (real-time control), a distributed model predictive control (MPC) determines the active and reactive power set-points of the DERs so that their aggregated contribution tracks the dispatch plan while obeying to DERs operational constraints as well as the grids ones. The proposed framework is experimentally validated on a real-scale microgrid that reproduces the network specifications of the CIGRE microgrid benchmark system.
Stochastic Model Predictive Control has proved to be an efficient method to plan trajectories in uncertain environments, e.g., for autonomous vehicles. Chance constraints ensure that the probability of collision is bounded by a predefined risk parameter. However, considering chance constraints in an optimization problem can be challenging and computationally demanding. In this paper, we present a grid-based Stochastic Model Predictive Control approach. This approach allows to determine a simple deterministic reformulation of the chance constraints and reduces the computational effort, while co…
In this paper, a neural network predictive controller is proposed to regulate the active and the reactive power delivered to the grid generated by a three-phase virtual inertia-based inverter. The concept of the conventional virtual synchronous generator (VSG) is discussed, and it is shown that when the inverter is connected to non-inductive grids, the conventional PI-based VSGs are unable to perform acceptable tracking. The concept of the neural network predictive controller is also discussed to replace the traditional VSGs. This replacement enables inverters to perform in both inductive and …
Formulation and Experimental Validation of Price-Based Control of Flexible Prosumers in Distribution Grids with the Alternating Direction Method of Multipliers
We study a smart grid with wind power and battery storage. Traditionally, day-ahead planning aims to balance demand and wind power, yet actual wind conditions often deviate from forecasts. Short-term flexibility in storage and generation fills potential gaps, planned on a minutes time scale for 30-60 minute horizons. Finding the optimal flexibility deployment requires solving a semi-infinite non-convex stochastic program, which is generally intractable to do exactly. Previous approaches rely on sampling, yet such critical problems call for rigorous approaches with stronger guarantees. Our meth…
This paper proposes and experimentally validates a joint control and scheduling framework for a grid-forming converter-interfaced BESS providing multiple services to the electrical grid. The framework is designed to dispatch the operation of a distribution feeder hosting heterogeneous prosumers according to a dispatch plan and provide frequency containment reserve and voltage control as additional services. The framework consists of three phases. In the day-ahead scheduling phase, a robust optimization problem is solved to compute the optimal dispatch plan and frequency droop coefficient, acco…
Model Predictive Control for Smart Grids with Multiple Electric-Vehicle Charging Stations
University of Technology Sydney（悉尼科技大学）；The University of New South Wales Sydney（新南威尔士大学）；Queen’s University Belfast（贝尔法斯特女王大学）；Princeton University（普林斯顿大学）
Advanced Testing Chain Supporting the Validation of Smart Grid Systems and Technologies
Fraunhofer Institute for Energy Economics and Energy System Technology（弗劳恩霍夫能源经济学与能源系统技术研究所）；NTUA National Technical University of Athens（雅典国立技术大学）；AIT Austrian Institute of Technology（奥地利技术研究院）
Managing supply and demand in the electricity grid is becoming more challenging due to the increasing penetration of variable renewable energy sources. As significant end-use consumers, and through better grid integration, buildings are expected to play an expanding role in the future smart grid. Predictive control allows buildings to better harness available energy flexibility from the building passive thermal mass. However, due to the heterogeneous nature of the building stock, developing computationally tractable control-oriented models, which adequately represent the complex and nonlinear …
In Part I, a method for the Harmonic Power-Flow (HPF) study of three-phase power grids with Converter-Interfaced Distributed Energy Resources (CIDERs) is proposed. The method is based on generic and modular representations of the grid and the CIDERs, and explicitly accounts for coupling between harmonics. In Part II, the HPF method is validated. First, the applicability of the modeling framework is demonstrated on typical grid-forming and grid-following CIDERs. Then, the HPF method is implemented in Matlab and compared against time-domain simulations with Simulink. The accuracy of the models a…
Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；elena international GmbH（elena国际有限公司）
Model predictive control (MPC) is a method to formulate the optimal scheduling problem for grid flexibilities in a mathematical manner. The resulting time-constrained optimization problem can be re-solved in each optimization time step using classical optimization methods such as Second Order Cone Programming (SOCP) or Interior Point Methods (IPOPT). When applying MPC in a rolling horizon scheme, the impact of uncertainty in forecasts on the optimal schedule is reduced. While MPC methods promise accurate results for time-constrained grid optimization they are inherently limited by the calculat…
Off-grid systems have emerged as a sustainable and cost-effective solution for rural electrification. In sub-Sarahan Africa (SSA), a great number of solar-hybrid microgrids have been installed or planned, operating stand-alone or grid-tied to a weak grid. Presence of intermittent energy sources necessitates the provision of energy storage for system balancing. Reliability and economic performance of those rural microgrids strongly depend on specific control strategies. This work develops a predictive control framework dedicated to rural microgrids incorporating a temperature-dependent battery …
We consider the problem of controlling the voltage of a distribution feeder using the reactive power capabilities of inverters. On a real distribution grid, we compare the local Volt/VAr droop control recommended in recent grid codes, a centralized dispatch based on optimal power flow (OPF) programming, and a feedback optimization (FO) controller that we propose. The local droop control yields suboptimal regulation, as predicted analytically. The OPF-based dispatch strategy requires an accurate grid model and measurement of all loads on the feeder in order to achieve proper voltage regulation.…
In this paper, we present the first experimental results of data-driven predictive control for connected and autonomous vehicles (CAVs) in dissipating traffic waves. In particular, we consider a recent strategy of Data-EnablEd Predicted Leading Cruise Control (DeeP-LCC), which bypasses the need of identifying the driving behaviors of surrounding vehicles and directly relies on measurable traffic data to achieve safe and optimal CAV control in mixed traffic. We present the implementation details of DeeP-LCC, including data collection, equilibrium estimation, and control execution. Based on a mi…
Simulation-based Validation of Smart Grids - Status Quo and Future Research Trends
OFFIS e.V.（OFFIS）；HAW Hamburg University of Applied Sciences（汉堡应用科技大学）；AIT Austrian Institute of Technology（奥地利技术研究所）；Delft University of Technology（代尔夫特理工大学）；Technical University of Denmark（丹麦技术大学）；University of Strathclyde（思克莱德大学）；Fraunhofer Inst. of Wind Energy and Energy System Technology（弗劳恩霍夫风能及能源系统技术研究所）；European Distributed Energy Resources Lab. (DERlab) e.V.（欧洲分布式能源资源实验室）；Commissariat à l’énergie atomique et aux énergies alternatives（法国原子能和替代能源委员会）
Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-I: Day-ahead and Numerical Validation
Due to the fluctuating nature of the wind and the increasing use of wind energy as a power source, wind power will have an increasing negative influence on the stability of the power grid. In this paper, a model predictive control strategy is introduced that not only stabilizes the power produced by wind farms, but also creates the possibility to perform power reference tracking with wind farms. With power reference tracking, it is possible for grid operators to adapt the power production to a change in the power demand and to counteract fluctuations that are introduced by other power generato…
Wind turbine (WT) controllers are often geared towards maximum power extraction, while suitable operating constraints should be guaranteed such that WT components are protected from failures. Control strategies can be also devised to reduce the generated power, for instance to track a power reference provided by the grid operator. They are called down-regulation strategies and allow to balance power generation and grid loads, as well as to provide ancillary grid services, such as frequency regulation. Although this balance is limited by the wind availability and grid demand, the quality of win…
In this paper, we consider a stochastic Model Predictive Control able to account for effects of additive stochastic disturbance with unbounded support, and requiring no restrictive assumption on either independence nor Gaussianity. We revisit the rather classical approach based on penalty functions, with the aim of designing a control scheme that meets some given probabilistic specifications. The main difference with previous approaches is that we do not recur to the notion of probabilistic recursive feasibility, and hence we do not consider separately the unfeasible case. In particular, two p…
In this paper, an improved multi-step finite control set model predictive current control (FCS-MPCC) strategy with speed loop disturbance compensation is proposed for permanent magnet synchronous machine (PMSM) drives system. A multi-step prediction mechanism is beneficial to significantly improve the steady-state performance of the motor system. While the conventional multi-step prediction has the defect of heavy computational burden, an improved multi-step finite control set model predictive current control (IM MPCC) strategy is proposed by developing a new multi-step prediction mechanism. F…
Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-II: Intra-day and Experimental Validation
Loads that can vary their power consumption without violating their Quality of service (QoS), that is flexible loads, are an invaluable resource for grid operators. Utilizing flexible loads as a resource requires the grid operator to incorporate them into a resource allocation problem. Since flexible loads are often consumers, for concerns of privacy it is desirable for this problem to have a distributed implementation. Technically, this distributed implementation manifests itself as a time varying convex optimization problem constrained by the QoS of each load. In the literature, a time invar…
A novel centralized model predictive control (MPC) is proposed for comfort and energy management in a residential building. The residential setup used here is equipped with a photovoltaic (PV) solar system and a stationary home battery unit. An air-to-air multi-split heat pump (HP) is used as the primary heating system. The electric baseboard (BB) unit in each zone is used as a secondary system. The MPC is simultaneously responsible for controlling the heating inputs of the HP and BB units for comfort management, as well as for the control of energy flow between the PV, the home battery and th…
This paper proposes an adaptive human pilot model that is able to mimic the crossover model in the presence of uncertainties. The proposed structure is based on the model reference adaptive control, and the adaptive laws are obtained using the Lyapunov-Krasovskii stability criteria. The model can be employed for human-in-the-loop stability and performance analyses incorporating different types of controllers and plant types. For validation purposes, an experimental setup is employed to collect data and a statistical analysis is conducted to measure the predictive power of the pilot model.
