Pavel V. Etingov

Incorporating Uncertainty of Wind Power Generation Forecast Into Power System Operation, Dispatch, and Unit Commitment Procedures

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, capable of incorporating multiple sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and startup failures). A new method called the “flying-brick” technique is developed to evaluate the look-ahead required generation performance envelope for the worst-case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an energy management system (EMS) is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

Integration of wind generation and load forecast uncertainties into power grid operations

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulation using California Independent System Operator (CAISO) real life data has shown the effectiveness and efficiency of the proposed approach.

Integration of uncertainty information into power system operations

Contemporary power systems face uncertainties coming from multiple sources, including forecast errors of load, wind and solar generation, uninstructed deviation and forced outage of traditional generators, and unscheduled loss of transmission lines. With increasing amounts of wind and solar generation being integrated into the system, these uncertainties have been growing significantly. It is critically important to build the knowledge of major sources of uncertainties, learn how to model them, and then incorporate this information into decision-making processes and power system operations, for better reliability and efficiency. This paper gives a comprehensive overview on the sources of uncertainties in power systems, their important characteristics and models, and approaches for integrating uncertainty information into system operations. It is primarily based on previous works conducted at the Pacific Northwest National Laboratory (PNNL).

Large-Scale PV Integration Study

This research effort evaluates the impact of large-scale photovoltaic (PV) and distributed generation (DG) output on NV Energy’s electric grid system in southern Nevada. It analyzes the ability of NV Energy’s generation to accommodate increasing amounts of utility-scale PV and DG, and the resulting cost of integrating variable renewable resources. The study was jointly funded by the United States Department of Energy and NV Energy, and conducted by a project team comprised of industry experts and research scientists from Navigant Consulting Inc., Sandia National Laboratories, Pacific Northwest National Laboratory and NV Energy.

The impact of solar photovoltaic generation on balancing requirements in the southern Nevada system

The impact of integrating large-scale solar photovoltaic (PV) generation on the balancing requirements in terms of regulation and load-following requirements in the southern Nevada balancing area is evaluated. The “swinging door” algorithm and the “probability box” method developed by Pacific Northwest National Laboratory (PNNL) were used to quantify the impact of large PV generation on the balancing requirements of the system operations. The systems actual scheduling, real-time dispatch and regulation processes were simulated. Different levels of distributed generation were also considered in the study. The impact of hourly solar PV generation forecast errors on regulation and load-following requirements was assessed. The sensitivity of balancing requirements with respect to real-time forecast errors of large PV generation was analyzed.

The Characteristic Ellipsoid Methodology and its Application in Power Systems

The characteristic ellipsoid (CELL) method to monitor dynamic behaviors of a power system is proposed. Multi-dimensional minimum-volume-enclosing characteristic ellipsoids are built using synchronized phasor measurements. System dynamic behaviors are identified by tracking the change rate of the CELLs characteristic indices. Decision tree techniques are used to link the CELLs characteristic indices and the systems dynamic behaviors and to determine types, locations and related information about the dynamic behaviors. The knowledge base of representative transient events is created by offline simulations based on the full Western Electric Coordinating Council (WECC) model. Two case studies demonstrate that the CELL method combined with the decision trees can detect transient events and their features with good accuracy.

Building decision trees for characteristic ellipsoid method to monitor power system transient behaviors

This paper presents the idea and initial results of building decision trees (DTs) for detecting and identifying various transient dynamic events using the characteristic ellipsoid method. In this paper, the objective is to determine fault types, fault locations and clearance times in the system using DTs based on ellipsoids surrounding system transient responses in the system operating parameter space. The New England 10-machine 39-bus system is used to generate a sufficiently large number of transient events in different system configurations. Comprehensive transient simulations considering three fault types, two different fault clearance times and various fault locations were conducted in the study. Bus voltage magnitudes and monitored reactive and active power flows are recorded as the phasor measurements to calculate characteristic ellipsoids whose volume, eccentricity, center and projection of the longest axis on the parameter space coordinates are used as indices to build decision trees. The DTs performance is tested and compared for different sets of phasor measurement units (PMUs) locations. The results demonstrate that, depending on the number and location of PMUs in the model, the proposed approach is capable to detect the fault type, location, and clearance time in up to 99% of the cases which are not included in the training set used to build the DT.

Improving area control error diversity interchange (ADI) program by incorporating congestion constraints

The area control error (ACE) determines how much a balancing authority (BA) needs to move its regulating units to meet mandatory control performance standard requirements. Regulation is an expensive resource that could cost several hundred million dollars a year for a BA. The amount of regulation needed in a system is increasing with more intermittent generation resources added to the system. The ACE diversity interchange (ADI) program provides a tool for reducing the regulation requirement by combining ACEs from several participating BAs followed by sharing the total ACE among all participating balancing areas. The effect is achieved as a result of the low statistical correlation between the original ACEs of participating BAs. A rule-based ADI approach has already been put into practice in the US Western Interconnection. The degree of actual ACE sharing is artificially limited because of the unknown redistribution of power flows and possible system congestion (these factors are not monitored in the existing ADI). This paper proposes a two-step linear programming (LP) ADI approach that incorporates congestion constraints. In the first step of the proposed LP ADI, the line transmission limits are enforced by setting up corresponding constraints. In the second step, the business fairness is pursued. Simulation is performed to compare the properties of the proposed LP ADI and the existing rule-based ADI. Favorable features, such as avoiding line limit violations and increasing the degree of possible ACE sharing, are observed for the proposed LP ADI.

Evaluating the impact of solar generation on balancing requirements in Southern Nevada system

In this paper, the impacts of solar photovoltaic (PV) generation on balancing requirements including regulation and load following in the Southern Nevada balancing area are analyzed. The methodology is based on the “swinging door” algorithm and a probability box method developed by PNNL. The regulation and load following signals are mimicking the systems scheduling and real-time dispatch processes. Load, solar PV generation and distributed PV generation (DG) data are used in the simulation. Different levels of solar PV generation and DG penetration profiles are used in the study. Sensitivity of the regulation requirements with respect to real-time solar PV generation forecast errors is analyzed.

NV Energy Solar Integration Study: Cycling and Movements of Conventional Generators for Balancing Services

With an increasing penetration level of solar power in the southern Nevada system, the impact of solar on system operations needs to be carefully studied from various perspectives. Qualitatively, it is expected that the balancing requirements to compensate for solar power variability will be larger in magnitude; meanwhile, generators providing load following and regulation services will be moved up or down more frequently. One of the most important tasks is to quantitatively evaluate the cycling and movements of conventional generators with solar power at different penetration levels. This study is focused on developing effective methodologies for this goal and providing a basis for evaluating the wear and tear of the conventional generators