The paper reviews literature which addresses the application of Flexible AC Transmission System (FACTS) concepts to the improvement of Power System utilisation and performance. It summarises literature on using high speed thyristor based control of HVAC power system elements to enhance the power carrying capacity of existing transmission circuits without compromising reliability. It describes a study system representative of existing power systems that has been developed to evaluate the economic and technical issues of loading transmission lines to their thermal limits. Considered are two scenarios, a multi-line corridor and a long radial interconnection, where the issues addressed are transient and dynamic stability, power flow control, reactive support and voltage stability. A benchmark system is developed to validate performance of die more simple devices. It is concluded that FACTS devices have the potential to significantly increase system stability margins thereby increasing loading capabil...

Flexible AC transmission systems (FACTS)

The accuracy of the load model has great effects on power system stability analysis and control. Based on our practice in China on modeling load from field measurements, this paper systematically develops a measurement-based composite load model. Principles guiding the load modeling practice are discussed based on detailed analysis on stochastic characteristics of the modeling procedure. The structure of the measurement-based composite load model is presented. A multicurve identification technique is described to derive parameters. The generalization capability of this built load model is also investigated in this paper. Two cases are studied to illustrate the accuracy of the developed load model on describing the load dynamic characteristics in the actual power system.

Composite load modeling via measurement approach

The representation of load dynamic characteristics remains an area of great uncertainty and has become a limiting factor for power system analysis and control. The random nature of the load makes load modeling a very difficult problem, which becomes even more challenging when the field measurements increase and the recorded dataset becomes large. This paper proposes a novel concept of modeling load based on support vectors (SVs) of load data. A three-stage procedure to find SVs of the recorded load dataset is presented. Then the load model is built on the SVs. Although the model is derived from only a small subset of the original dataset, it has a strong generalization capability to describe dynamics of the whole dataset. However, the computational burden on the modeling process is much relieved since only a small subset of data is involved. The proposed method also answers the question on how data should be grouped and how many load models should be built as data are accumulated. This paper infers that, although the data space where the load varies seems indefinite and big, its characteristic can be captured and modeled in a much smaller subspace. The presented method is shown to be effective by the case study on Hushitai substation.

Load modeling by finding support vectors of load data from field measurements

Flexibility in certain types of loads could be exploited to provide fast and controllable power reserve if the supply voltage/frequency is controlled using existing power electronic interfaces (e.g., motor drives) or additional ones like recently proposed electric springs. Such a load together with its power electronic interface forms a so called smart load. Effectiveness of static smart loads for primary frequency response provision has been shown in the previous papers through case studies on a segment of the low voltage/medium voltage (LV/MV) distribution network. In this paper, collective contribution of both static and motor type smart loads to rapid frequency response provision is demonstrated through a case study on the Great Britain (GB) transmission system. The active power reserve available from such smart loads are quantified and aggregated at each node at the transmission level (275/400 kV). The study shows that the smart loads collectively offer a short-term power reserve which is comparable to the spinning reserve in the GB system, and thus can ensure acceptable frequency deviation and its rate of change following a large infeed loss.

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Rapid Frequency Response From Smart Loads in Great Britain Power System

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand the characteristics of loads for power system analysis and control. Challenges of load modeling come from a variety of load components and time-varying compositions. In addition, the existence of outliers in measurements further complicates the problem. This paper proposes a robust time-varying parameter identification technique for composite ZIP and induction motor load models. A batch-model regression form, including time-varying parameters, is established based on state transition models and observation models with current observations and previous predictions to guarantee data redundancy. To deal with outliers, down-weighting coefficients of measurements are calculated with a projection statistics approach. Based on the batch-model regression and the down-weighting coefficients, parameter identification at each sample time is formulated as a weighted least squares optimization, which is solved by the Newton-Raphson approach with the previous estimated parameters as the initial iteration values. In addition, parameters’ sensitivities to different outliers in measurements are analyzed. Results on the IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm can robustly identify time-varying parameters for the composite load models.

https://ieeexplore.ieee.org/ielaam/5165411/8595470/8051119-aam.pdf

Robust Time-Varying Parameter Identification for Composite Load Modeling

By transforming utility load-mix data for use in standard load flow and transient stability programs the LOADSYN software makes it easy for power system analysts to produce new, more-accurate load models for system simulations. Better models can better predict power system behavior and thus improvements in transmission system utilization and planning.

Load modeling for power flow and transient stability computer studies: Volume 1, Summary report: Final report

By transforming utility load-mix data for use in standard load flow and transient stability programs, the LOADSYN software makes it easy for power system analysts to produce new, more accurate load models for system simulations. Better models can better predict power system behavior and thus bring improvements in transmission system utilization and planning. This volume is intended to assist power system analysts in the process of developing and using load models for power flow and transient stability studies. It covers load modeling philosophy, data sources, and the models and methods developed in this project.

Load modeling for power flow and transient stability computer studies: Volume 2, Load-modeling reference manual: Final report

This report presents a summary of the development of the Load Model Synthesis (LOADSYN) computer software, which transforms data on load class mix, composition, and characteristics into the form required for commonly-used power flow and transient stability simulation programs, including the EPRI (RP1208), Philadelphia Electric, and Power Technologies, Inc. (PSS/E) programs. The load modeling software is designed for ease of use by electric utility engineers, with default data provided for load composition and characteristics. This volume describes the internal structure and variables of the Load Model Synthesis programs, including the detailed requirements specification and instructions for interfacing with additional power flow and stability programs.

F. Nozari

Papers

Load modeling for power flow and transient stability computer studies: Volume 1, Summary report: Final report

Load modeling for power flow and transient stability computer studies: Volume 2, Load-modeling reference manual: Final report

Load modeling for power flow and transient stability computer studies: Volume 4, LOADSYN code program reference manual