Microgrids (MGs) are seen today as the solution to the challenge of meeting the ever-increasing demand of energy which is clean. A variety of challenges need to be overcome for these MGs to be successful varying from stability, power quality to protection, and management. Since the various control strategies are actively being researched and emerging challenges still being addressed, there has been a lot of interest related to the aspect of testing. The ever-increasing complexity of control mechanisms invokes the need for safer, faster yet reliable testing methods, which do not compromise on the degree of detail and at the same time are economical and require the minimum testing time. Off-line simulation, real-time (RT) simulation, hardware in the loop simulation, RT emulation, hardware test beds, pilot plants, and other integrated approaches are the major methods for testing in MGs. This paper gives an overview of the testing techniques and discusses the trends in the various technologies employed for testing MGs. First, the various methods are briefly discussed and a comparison is provided. Next, the various research efforts carried out on the aspect of MG testing are categorized and presented one-by-one. Furthermore, new methodologies and emerging approaches for the testing have also been highlighted, and the challenges and future research avenues have been presented.

Real-Time Testing Approaches for Microgrids

Power hardware-in-the-loop (PHIL) technology allows for the testing of physical equipment in a real-time simulation environment. An important role is attributed to the power interface (PI). This PI connects a power system model, which is implemented on a digital computer, to physical hardware under test, such as a power electronic converter. Several hardware-in-the-loop (HIL) test setups with distinct PIs are proposed and compared. Based on detailed modeling of the different interfaces, system analysis is performed for each HIL test setup with respect to overall stability and accuracy. To verify stability for PHIL simulation systems, transfer function representations of the entire PHIL simulation processes are developed, and all involved time delays are quantified. The Nyquist stability criterion is applied to analyze all considered interfacing methods to enhance PHIL simulation stability, and the accuracy is evaluated. Moreover, experimental test results are given to demonstrate both the applicability and the functioning of the proposed interfacing methods. A particular focus is laid on the interfacing of physical power electronic inverters tested as part of a network in a PHIL real-time simulation.

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Accurate and Stable Hardware-in-the-Loop (HIL) Real-Time Simulation of Integrated Power Electronics and Power Systems

The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions.

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Advanced laboratory testing methods using real-time simulation and hardware-in-the-loop techniques: a survey of smart grid international research facility network activities

Required functions of a microgrid become divers because there are many possible configurations that depend on the location. In order to effectively implement the microgrid system, which consists of a microgrid controller and components with distributed energy resources (DERs), thorough tests should be run to validate controller operation for possible operating conditions. Power-hardware-in-the-loop (PHIL) simulation is a validation method that allows different configurations and yields reliable results. However, PHIL configuration for testing the microgrid controller that can evaluate the communication between a microgrid controller and components as well as the power interaction among microgrid components has not been discussed. Additionally, the difference of the power rating of microgrid components between the deployment site and the test lab needs to be adjusted. In this paper, we configured the PHIL environment, which integrates various equipment in the laboratory with a digital real-time simulation (DRTS), to address these two issues of microgrid controller testing. The test in the configured PHIL environment validated two main functions of the microgrid controller, which supports the diesel generator set operations by controlling the DER, regarding single function and simultaneously activated multiple functions.

https://www.mdpi.com/1996-1073/13/8/2044/pdf

Microgrid Controller Testing Using Power Hardware-in-the-Loop

The ideas in this paper are motivated by an increased need for systematic data-enabled resource management of large-scale electric energy systems. The basic control objective is to manage uncertain disturbances, power imbalances in particular, by optimizing available power resources. To that end, we start with a centralized optimal control problem formulation of system-level performance objective subject to complex interconnection constraints and constraints representing highly heterogeneous internal dynamics of system components. To manage spatial complexity, an inherent multi-layered structure is utilized by modeling interconnection constraints in terms of unified power variables and their dynamics. Similarly, the internal dynamics of components and sub-systems (modules), including their primary automated feedback control, is modeled so that their input–output characterization is also expressed in terms of power variables. This representation is shown to be key to managing the multi-spatial complexity of the problem. In this unifying energy/power state space, the system constraints are all fundamentally convex, resulting in the convex dynamic optimization problem, for typically utilized quadratic cost functions. Based on this, an interactive multi-layered modeling and control method is introduced. While the approach is fundamentally based on the primal–dual decomposition of the centralized problem, this is formulated for the first time for the couple real-reactive power problem. It is also is proposed for the first time to utilize sensitivity functions of distributed agents for solving the primal distributed problem. Iterative communication complexity typically required for convergence of point-wise information exchange is replaced by the embedded distributed optimization by the modules when creating these functions. A theoretical proof of the convergence claim is given. Notably, the inherent multi-temporal complexity is managed by performing model predictive control (MPC)-based decision making when solving distributed primal problems. The formulation enables distributed decision-makers to value uncertainties and related risks according to their preferences. Ultimately, the distributed decision making results in creating a bid function to be used at the coordinating market-clearing level. The optimization approach in this paper provides a theoretical foundation for next-generation Supervisory Control and Data Acquisition (SCADA) in support of a Dynamic Monitoring and Decision Systems (DyMonDS) for a multi-layered interactive market implementation in which the grid users follow their sub-objectives and the higher layers coordinate interconnected sub-systems and the high-level system objectives. This forms a theoretically sound basis for designing IT-enabled protocols for secure operations, planning, and markets.

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Unified value-based feedback, optimization and risk management in complex electric energy systems

This article provides a unique benchmark to integrate and systematically evaluate advanced functionalities of microgrid and downstream device controllers. The article describes Banshee, a real-life power distribution network. It also details a real-time controller hardware-in-the-loop (HIL) prototyping platform to test the responses of the controllers and verify decision-making algorithms. The benchmark aims to address power industry needs for a common basis to integrate and evaluate controllers for the overall microgrid, distributed energy resources (DERs), and protective devices. The test platform will accelerate microgrid deployment, enable standard compliance verification, and further develop and test controllers' functionalities. These contributions will facilitate safe and economical demonstrations of the state-of-the-possible while verifying minimal impact to existing electrical infrastructure. All aspects of the benchmark and platform development including models, configuration files, and documentation are publicly available via the electric power HIL controls collaborative (EPHCC).

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2018.5174

Banshee distribution network benchmark and prototyping platform for hardware-in-the-loop integration of microgrid and device controllers

We describe a framework for model identification and model order reduction (MOR) of highly dynamic microgrids based on a high fidelity hardware-in-the-loop (HIL) platform. A synchronous generator that is connected in different configurations is analyzed to analytically obtain small-signal linearized models which are compared against HIL-obtained data. The framework is applied to a small microgrid consisting of a synchronous generator, inverter-based distributed energy resource (DER), and linear loads, and provides insights into the estimated machine transfer functions. We propose that HIL based framework could be a suitable tool for model identification, MOR, and controller optimization of complex dynamic microgrids.

Model identification of dynamic microgrids and controller optimization with high fidelity hardware-in-the-loop platform

This paper provides an example of implementing ship power system modules on different digital real time simulator (DRTS) platforms utilizing model description document. Power Generation Module (PGM) was selected as the candidate for this process. The module was implemented on three different DRTS platforms: Real Time Digital Simulator (RTDS), Typhoon HIL and Opal-RT. A common set of scenarios were simulated on each platform. Results from DRTS platforms were cross-verified for their operation. Difficulties in implementation due to either lack of information or documentation are highlighted to provide an understanding of document based model implementation.

An Exercise on Model Description Document based Implementation of Shipboard Power System Modules on DRTS Platforms

We have found that the synchronous generator in standalone operation can have unstable equilibrium points in the open loop at realistic operating conditions, a finding which has not been shared before to the best of our knowledge. In contrast, a grid-tied generator with the same parameters will be open loop stable for the same operating points. Starting from a 7th order two-axis (dq) model of the machine, we have employed a combination of techniques such as: small signal analysis, time domain simulation, large signal trajectory analysis and model order reduction to study this phenomenon. Knowledge of the system dynamics, in particular the plant stability, is important for controls and systems engineers to design more suitable control mechanisms.

Murilo Almeida

Papers

Banshee distribution network benchmark and prototyping platform for hardware-in-the-loop integration of microgrid and device controllers

Model identification of dynamic microgrids and controller optimization with high fidelity hardware-in-the-loop platform

An Exercise on Model Description Document based Implementation of Shipboard Power System Modules on DRTS Platforms

Unstable Equilibrium Points in Standalone Synchronous Generator