WECC Composite Load Model Parameter Identification Using Deep Learning Approach

The growing integration of inverter-based resources (IBRs) introduces new challenges to power system stability. In this context, virtual synchronous machine control-based IBRs (VSMIBRs) are anticipated to replace some conventional synchronous generators (SGs) and reshape future power systems. In such grids, IBRs must provide stability services such as dynamic voltage recovery (DVR). Accordingly, this paper presents a comprehensive analysis of the impact of VSM-based IBR integration on DVR and load shedding amount, considering the western electricity coordinating council (WECC) voltage recovery criteria (as protection constraints) across various penetration levels. Furthermore, the influence of DC-link voltage limitations on the DVR performance of VSM-IBRs is examined, and a dedicated algorithm is proposed for calculating their spinning reserve to enhance DC-link stability. For the simulations in this study, the IBR and its controllers are accurately modeled in the DSL (dynamic simulation language) environment of DIgSILENT PowerFactory software. The IEEE 39-Bus test system is utilized for time-domain simulations to demonstrate the effectiveness of the proposed method.

Inverter-based resources (IBRs) such as solar and wind plants are being connected in large numbers to the power grid. Additionally, fossil fuel-based generation is being phased out, resulting in the loss of rotor inertia, a key contributor to the transient stability. Unlike a synchronous generator (SG), an IBR’s response to a disturbance depends on its controls, involving factors such as operating mode, current limits, and grid code requirements. Therefore, the large-signal behavior of IBRs and their impact on transient stability must be studied. This paper presents hypotheses rooted in the physics of the transient stability phenomenon, choosing the most accurate models for IBRs to study the phenomenon, and documents simulation results on the IEEE 9-bus test system. The simulation results corroborate the hypotheses and highlight the impact of different control designs and operating modes on the critical clearing time (CCT), the metric considered for transient stability in this paper.

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions.Many existing models do not fully incorporate new inverter control functions, which can affect system stability.The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids.Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited.Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations.There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration.The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses.This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently.The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability.Several milestones were reached by the end of the project.A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected.EPRI and NREL tested various inverters, conforming to IEEE standards.Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses.The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter.That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard.The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements.They can also support interconnection screens and conformity assessments of IBR plants, including solar PV.The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses.The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems.New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid.Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity.Proof-of-concept field demonstration was 2.4.4.1.

The mechanism of UHVDC Emergency DC Power Support (EDCPS) to enhance transient stability of multi-machine system is analyzed briefly based on EEAC (Extended Equal Area Criteria), and the influence of load model characteristic including ZIP static load model and IM (Induction Motor) model on UHVDC EDCPS effect after heavy disturbance is further studied, and the corresponding UHVDC EDCPS Strategies should be modified with different load models to keep system stable. Studies reveal that the influence of sending-grid ZIP characteristic on post-fault EDCPS effect is completely opposite to that of receiving-grid. Under heavy disturbance IM load absorbs more active power than that of ZIP load and the influence of sending-grid IM load on post-fault EDCPS angel stability is completely opposite to that of receiving-grid. As for the influence on EDCPS effect between synthesis load and ZIP load, total load of both sending-grid and receiving-grid should be weighed first. If total load of sending-grid is smaller than that of receiving-grid, synthesis load model with IM will deteriorate post-fault EDCPS effect, and □P should be increaseed or T should be advanced appropriately.

In order to derive more realistic load models in stability studies, suitable methods for building load models are presented in this thesis. Load types studied here are static and induction motor loads. Models for individual loads are developed are then put them together to a composite load. A computer program is developed for representing steady state and dynamic characteristics of loads due to voltage and frequency variations. Results obtained from the proposed models are compared with the conventional models such as constant impedance, constant current etc. Differences are found from the comparison results, especially when loads consist of induction motors. This is because the conventional models neglect the dynamic behavior of loads while the proposed models consider these effects, which should be more accurate.

This paper presents an update on the load model development undertaken by the utilities and grid operators in the Western Electricity Coordinating Council (WECC). The paper describes the driving forces for accurate load modeling in WECC. The structure of the proposed composite load model is presented. The paper also discusses the need for special modeling of compressor motors in single-phase air-conditioners and refrigerators. The paper describes the data requirements for the new composite load model and outlines the structure of the load model data tool. The issues related to load model validation are discussed. Finally, the paper provides expectations of the impact that the load model will have on the system performance studies

Load model has significant impact on power system simulation. Current load modeling approaches are inadequate on revealing the accuracy and time-variation of load compositions. The application of wireless sensors dispersed in power distribution networks provides further opportunities for load modeling. In this article, a data-driven online aggregated load modeling approach is proposed systematically. First, all the electricity consumers are clustered according to big data of power consumption behaviors. In each cluster, typical users are designated to stand for the characteristics of the cluster, and intrusive measurement is adapted to capture these typical users’ time-varying information by employing wireless intelligent terminals, which can identify the composition of static load and induction motor load online. Second, the load models of other users in each cluster are assumed identical to typical users, including static impedance–current–power models and induction motor models. Finally, the composite load model is achieved by hierarchical aggregation and bottom-to-up stepwise equivalence. Simulations demonstrate that the load model built by proposed approach reflects higher accuracy and adaptability in power system.

An increased integration of distributed generators into microgrids presents a technical challenge to maintain voltage and frequency stability, especially in islanded or autonomous operation. For stability assessment of the microgrid, a proper initialization is particularly needed to get the right steady-state operating point when the widely used induction motor (IM) loads are mainly considered. Since a conventional power-flow approach is not straightforward and suitable for initializing the IM loads in the isolated microgrid network due to an unavoidable discrepancy between initial-bus scheduled and actual values of IM’s reactive powers. To eliminate this mismatch, this paper presents a precise power-flow initialization using a unified Newton–Raphson approach. The correct steady-state initializations are demonstrated using 6bus and 13bus microgrid systems. IEEE standard 33, 38, and 69bus distribution networks are employed to explore computational performances of the proposed algorithm for the case where a large number of IM loads are incorporated via distribution feeder loads.

The primary objective of this work is to develop practical and robust technologies for detecting anomalies associated with solar inverters and other inverter-based resources (IBRs). As IBRs become more prevalent in modern power systems, their interactions with the grid pose critical challenges, particularly regarding grid stability during the transition from traditional radial-fed power systems to distributed generation. While phasor measurement units (PMUs) are used in some distribution systems, they lack the granularity to capture transients and phasor metrics of individual IBRs. To address this limitation, the work focused on bridging this visibility gap by designing tools capable of precise monitoring and management of IBR-induced grid dynamics. The solution aimed to strike a balance between technical capability and cost-effectiveness, aligning with the needs of the power community. The ideal approach involves continuous analysis of voltage waveforms from each IBR by a central server to detect anomalies in magnitude, phase, frequency, and harmonics. However, bandwidth and hardware cost constraints necessitated the development of a more practical solution. This included event-detection methods to identify anomalies, compression and data-transmission techniques to deliver high-resolution event data, and continuous basic waveform data outside event windows. Prototype hardware was designed using modern, cost-efficient components, and system costs, including data transmission and storage, were carefully estimated to ensure feasibility. Collaboration with industrial partners Convault Energy, Inc., and DigiCollect played a crucial role in refining the system’s design and identifying commercialization pathways. Input from potential customers shaped the system's features, ensuring alignment with industry needs. Rigorous field tests were conducted with grid-edge devices deployed at multiple distributed energy resource (DER) sites. These tests validated the technology's performance, successfully detecting and capturing transient events. The results demonstrate the system's reliability, highlighting its potential to significantly enhance grid monitoring and stability in the evolving energy landscape.

The increasing adoption of inverter-based resources (IBRs) in power systems has prompted the need for controllable virtual inertia provision to stabilize frequency. Therefore, it is imperative to conduct a comprehensive analysis and estimation of inertia in the IBR-penetrated power system to ensure adequate dispatchable inertia capacity in real time. This paper presents a comparative analysis of system identification methods for estimating inertia of inverter-based resources (IBRs) under continuous, real-time operating conditions. In addition, a stability-constrained dispatch framework has been adopted to optimize the virtual inertia provision of IBRs. Meanwhile, an inertia estimation is performed after each dispatch period to validate the virtual inertia provided by IBRs. Inertia estimation approaches are validated using the IEEE-39 bus system. The results demonstrate higher accuracy in inertia estimation when using the least-squares method with the exact measurement window size. Consequently, this technique is integral to procure adaptive virtual inertia from IBRs in the stability-constrained economic dispatch framework.

In worldwide, the day to day usage of electric power is increasing expeditiously which results in the increase of both real and reactive losses and reduction in voltage in a distribution network. The integration of distributed or dispersed generation (DG) to the distribution network greatly decreases the power loss and improves the voltage level. In order to extract maximum advantages from the DG, it should be placed at an optimum location with optimum size. In this paper, the performance of different DG technologies has been analyzed. Combined loss sensitivity (CLS) is used to identify the optimal location and whale optimization is used for the optimal size of DG. In order to test and validate the performance of proposed technique two standard test cases, IEEE 33-bus test system and 69-bus test systems have been considered.

In recent years, continuous efforts have been made on the modeling and stability analysis of converter-dominated grids (CDGs) to guarantee efficient, stable and resilient operations. The literature has tried to reveal the mechanism behind abnormal instability and resonances caused by the interaction between multiple time-scale control loops within a single converter, different types of converters and power networks. It is commonly assumed that CDGs are three-phase balanced systems and supply only passive loads. In reality, CDGs can experience imbalance caused by asymmetric networks, loads or faults. Moreover, induction motor (IM) loads, which exhibit highly nonlinear couplings between dynamics of power, voltage and frequency, typically account for a large portion of electric loads. Ignoring the impact of imbalance and dynamic loads in the modeling and stability analysis of CDGs can lead to unrealistic stability assessment results. To fill the gap, this paper presents a general small-signal modeling framework for CDGs in the presence of IM loads. Linear time-periodic (LTP) eigenvalue analysis is performed to investigate the impact of the interaction between IM loads, grid-following (GFL) converters and virtual synchronous generator (VSG) converters on the system stability. The time-domain simulation and experimental results validate the theoretical analysis.

With the development of distributed energy resources (DERs) and advancements in technology, microgrids (MGs) appear primed to become an even more integral part of the future distribution grid. In order to transition to the smart grid of the future, MGs must be properly managed and controlled. This paper proposes a microgrid energy management system (MGEMS) based on a hybrid control algorithm that combines Transactive Control (TC) and Model Predictive Control (MPC) for an efficient management of DERs in prosumer-centric networked MGs. A locally installed home energy management system (HEMS) determines a charge schedule for the battery electric vehicle (BEV) and a charge–discharge schedule for the solar photovoltaic (PV) and battery energy storage system (BESS) to reduce residential customers’ operation cost and to improve their overall savings. The proposed networked MGEMS strategy was implemented in IEEE 33-bus test system and evaluated under different BEV and PV-BESS penetration scenarios to study the potential impact that large amounts of BEV and PV-BESS systems can have on the distribution system and how different pricing mechanisms can mitigate these impacts. Test results indicate that our proposed MGEMS strategy shows potential to reduce peak load and power losses as well as to enhance customers’ savings.

With advances in renewable energy (RE)technologies and the promotion of restructuring, distributed energy (DG)sources play a vital role in today's power sector. From the technical and economic point of view, DG sources provide a no of benefits such as lesser system losses, better system voltage profile and lower line congestion. The aim of this work is to determine the voltage stability of a distribution system at different levels of DG compensation determined as a percentage of the total load on the system. The objective function is formulated to minimize the real power loss. At first, the locations are chosen based on strategy using Loss Sensitivity Factors (LSF)and the optimal sizing of multiple units of DG sources is optimized using Particle Swarm Optimization (PSO)algorithm. The simulations are performed on standard IEEE 33-bus and 69-bus test systems and the results validate the importance of placing appropriately sized DG sources at suitable locations to achieve improved voltage stability and reduced distribution losses.

In this thesis, a transfer function-based load model is determined for commercial and industrial load. This model is derived from the composite load model which consist of an induction motor and static load. This developed model is compared to composite load model by considering two cases: 1) a small motor composition load or commercial load and 2) higher motor composition load or industrial load. The research is conducted through MATLAB/Simulink simulation. In order to compare the dynamic response of developed model, a comparative study has been done between the two models. In addition, the influence of voltage and frequency dependency terms on the overall model accuracy for developed model has been evaluated through several case studies considering both voltage and frequency dependency disturbances. A short-term load forecast model is developed for an electrically heated house. This research work is based on experimental data collected by installing current sensors in a house in St. Johns, Newfoundland, Canada. The data was collected for three years and only one-year data is used for this model. The model is based on Recurrent Neural Network (RNN) with wavelet transform. The proposed model is verified by comparing other developed models in the literature through MATLAB deep learning toolbox and wavelet toolbox. The proposed model can more accurately forecast the load.