During the last decade, utility companies around the world have experienced a significant increase in the occurrences of either planned or unplanned blackouts, and microgrids have emerged as a viable solution to improve grid resiliency and robustness. Recently, power converters with grid-forming capabilities have attracted interest from researchers and utilities as keystone devices enabling modern microgrid architectures. Therefore, proper and thorough testing of Grid-Forming Inverters (GFMIs) is crucial to understand their dynamics and limitations before they are deployed. The use of closed-loop real-time Power Hardware-in-the-Loop (PHIL) simulations will facilitate the testing of GFMIs using a digital twin of the power system under various contingency scenarios within a controlled environment. So far, lower to medium scale commercially available GFMIs are difficult to interface into PHIL simulations because of their lack of a synchronization mechanism that allows a smooth and stable interconnection with a voltage source such as a power amplifier. Under this scenario, the use of the well-known Ideal Transformer Method to create a PHIL setup can lead to catastrophic damages of the GFMI. This paper addresses a simple but novel method to interface commercially available GFMIs into a PHIL testbed. Experimental results showed that the proposed method is stable and accurate under standalone operation with abrupt (step) load-changing dynamics, followed by the corresponding steady state behavior. Such results were validated against the dynamics of the GFMI connected to a linear load bank.
IEEE Journal of Emerging and Selected Topics in Power Electronics
Augustine, Sijo; Reno, Matthew J.; Brahma, Sukumar M.; Lavrova, Olga
This report presents a novel fault detection, characterization, and fault current control algorithm for a standalone solar-photovoltaic (PV) based dc microgrids. The protection scheme is based on the current derivative algorithm. The overcurrent and current directional/differential comparison based protection schemes are incorporated for the dc microgrid fault characterization. For a low impedance fault, the fault current is controlled based on the current/voltage thresholds and current direction. Generally, the droop method is used to control the power-sharing between the converters by controlling the reference voltage. In this article, an adaptive droop scheme is also proposed to control the fault current by calculating a virtual resistance R droop , and to control the converter output reference voltage. For a high impedance fault, differential comparison method is used to characterize the fault. These algorithms effectively control the converter pulsewidth and reduce the flow of source current from a particular converter, which helps to increase the fault clearing time. Additionally, a trip signal is sent to the corresponding dc circuit breaker (DCCB), to isolate the faulted converter, feeder or a dc bus. The dc microgrid protection design procedure is detailed, and the performance of the proposed method is verified by simulation analysis.
Sikeridis, Dimitrios; Bidram, Ali; Devetsikiotis, Michael; Reno, Matthew J.
Distribution and transmission protection systems are considered vital parts of modern smart grid ecosystems due to their ability to isolate faulted segments and preserve the operation of critical loads. Current protection schemes increasingly utilize cognitive methods to proactively modify their actions according to extreme power system changes. However, the effectiveness and robustness of these information-driven solutions rely entirely on the integrity, authenticity, and confidentiality of the data and control signals exchanged on the underlying relay communication networks. In this paper, we outline a scalable adaptive protection platform for distribution systems, and introduce a novel blockchain-based distributed network architecture to enhance data exchange security among the smart grid protection relays. The proposed mechanism utilizes a tiered blockchain architecture to counter the current technology limitations providing low latency with better scalability. The decentralized nature removes singular points of failure or contamination, enabling direct secure communication between smart grid relays. We also present a security analysis that demonstrates how the proposed framework prohibits any alterations on the blockchain ledger providing integrity and authenticity of the exchanged data (e.g., realtime measurements/relay settings). Finally, the performance of the proposed approach is evaluated through simulation on a blockchain benchmarking framework with the results demonstrating a promising solution for secure smart grid protection system communication.
Siratarnsophon, Piyapath; Hernandez, Miguel; Peppanen, Jouni; Deboever, Jeremiah; Rylander, Matthew; Reno, Matthew J.
Distribution system modelling and analysis with growing penetration of distributed energy resources (DERs) requires more detailed and accurate distribution load modelling. Smart meters, DER monitors, and other distribution system sensors provide a new level of visibility to distribution system loads and DERs. However, there is a limited understanding of how to efficiently leverage the new information in distribution system load modelling. This study presents the assessment of 11 methods to leverage the emerging information for improved distribution system active and reactive power load modelling. The accuracy of these load modelling methods is assessed both at the primary and the secondary distribution levels by analysing over 2.7 billion data points of results of feeder node voltages and element phase currents obtained by performing annual quasi-static time series simulations on EPRI's Ckt5 feeder model.
The energy grid becomes more complex with increasing penetration of renewable resources, distributed energy storage, distributed generators, and more diverse loads such as electric vehicle charging stations. The presence of distributed energy resources (DERs) requires directional protection due to the added potential for energy to flow in both directions down the line. Additionally, contingency requirements for critical loads within a microgrid may result in looped or meshed systems. Computation speeds of iterative methods required to coordinate loops are improved by starting with a minimum breakpoint set (MBPS) of relays. A breakpoint set (BPS) is a set of breakers such that, when opened, breaks all loops in a mesh grid creating a radial system. A MBPS is a BPS that consists of the minimum possible number of relays required to accomplish this goal. In this paper, a method is proposed in which a minimum spanning tree is computed to indirectly break all loops in the system, and a set difference is used to identify the MBPS. The proposed method is found to minimize the cardinality of the BPS to achieve a MBPS.
Timeseries power and voltage data recorded by electricity smart meters in the US have been shown to provide immense value to utilities when coupled with advanced analytics. However, Advanced Metering Infrastructure (AMI) has diverse characteristics depending on the utility implementing the meters. Currently, there are no specific guidelines for the parameters of data collection, such as measurement interval, that are considered optimal, and this continues to be an active area of research. This paper aims to review different grid edge, delay tolerant algorithms using AMI data and to identify the minimum granularity and type of data required to apply these algorithms to improve distribution system models. The primary focus of this report is on distribution system secondary circuit topology and parameter estimation (DSPE).
Accurate distribution secondary low-voltage circuit models are needed to enhance overall distribution system operations and planning, including effective monitoring and coordination of distributed energy resources located in the secondary circuits. We present a full-scale demonstration across three real feeders of a computationally efficient approach for estimating the secondary circuit topologies and parameters using historical voltage and power measurements provided by smart meters. The method is validated against several secondary configurations, and compares favorably to satellite imagery and the utility secondary model. Feeder-wide results show how much parameters can vary from simple assumptions. Model sensitivities are tested, demonstrating only modest amounts of data and resolutions of data measurements are needed for accurate parameter and topology results.
Successful system protection is critical to the performance of the DC microgrid system. This paper proposes an adaptive droop based fault current control for a standalone low voltage (LV) solar-photovoltaic (PV) based DC microgrid protection. In the proposed method, a DC microgrid fault is detected by the current and voltage thresholds. Generally, the droop method is used to control the power sharing between the converters by controlling the reference voltage. In this paper, this scheme is extended to control the fault current by calculating an adaptive virtual resistance Rdroop, and to control the converter output reference voltage. This effectively controls the converter pulse width, and reduces the flow of source current from a particular converter which helps to increase the fault clearing time. Additionally, a trip signal is sent to the corresponding DC circuit breaker (DCCB), to isolate the faulted converter, feeder or a DC bus. The design procedure is detailed, and the effectiveness of proposed method is verified by simulation analysis.
Distribution system analysis requires yearlong quasi-static time-series (QSTS) simulations to accurately capture the variability introduced by high penetrations of distributed energy resources (DER) such as residential and commercial-scale photovoltaic (PV) installations. Numerous methods are available that significantly reduce the computational time needed for QSTS simulations while maintaining accuracy. However, analyzing the results remains a challenge; a typical QSTS simulation generates millions of data points that contain critical information about the circuit and its components. This paper provides examples of visualization methods to facilitate the analysis of QSTS results and to highlight various characteristics of circuits with high variability.
The Ideal Transformer Method (ITM) and the Damping Impedance Method (DIM) are the most widely used techniques for connecting power equipment to a Power-Hardware-in-the-Loop (PHIL) real-time simulation. Both methods have been studied for their stability and accuracy in PHIL simulations, but neither have been analyzed when the hardware is providing grid-support services with volt-var, frequency-watt, and fixed power factor functions. In this work, we experimentally validate the two methods of connecting a physical PV inverter to a PHIL system and evaluate them for dynamic stability and accuracy when operating with grid-support functions. It was found that the DIM Low Pass Lead Filter (LPF LD) method was the best under unity and negative power factor conditions, but the ITM LPF LD method was preferred under positive power factor conditions.