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.

/pdf/unified-value-based-feedback-optimization-and-risk-1ztdpb2yud.pdf

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

The smart-grid era is characterized by a progressive penetration of distributed energy resources into the power systems. To ensure the safe operation of the system, it is necessary to evaluate the interactions that those devices and their associated control algorithms have between themselves and the pre-existing network. In this regard, Hardware-in-the-Loop (HIL) testing approaches are a necessary step before integrating new devices into the actual network. However, HIL is a device-oriented testing approach with some limitations, particularly considering the possible impact that the device under test may have in the power system. This paper proposes the Power System Hardware-in-the-Loop (PSHIL) concept, which widens the focus from a device- to a system-oriented testing approach. Under this perspective, it is possible to evaluate holistically the impact of a given technology over the power system, considering all of its power and control components. This paper describes in detail the PSHIL architecture and its main hardware and software components. Three application examples, using the infrastructure available in the electrical engineering laboratory of the University of Sevilla, are included, remarking the new possibilities and benefits of using PSHIL with respect to previous approaches.

Power system hardware in the loop (PSHIL): A holistic testing approach for smart grid technologies

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

Thrung Ham Ha

Papers

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