Stochastic Model for Power Grid Dynamics

We introduce a stochastic model that describes the quasi-static dynamics of an electric transmission network under perturbations introduced by random load fluctuations, random removing of system components from service, random repair times for the failed components, and random response times to implement optimal system corrections for removing line overloads in a damaged or stressed transmission network. We use a linear approximation to the network flow equations and apply linear programming techniques that optimize the dispatching of generators and loads in order to eliminate the network overloads associated with a damaged system. We also provide a simple model for the operator's response to various contingency events that is not always optimal due to either failure of the state estimation system or due to the incorrect subjective assessment of the severity associated with these events. This further allows us to use a game theoretic framework for casting the optimization of the operator's response into the choice of the optimal strategy which minimizes the operating cost. We use a simple strategy space which is the degree of tolerance to line overloads and which is an automatic control (optimization) parameter that can be adjusted to trade off automatic load shed without propagating cascades versus reduced load shed and an increased risk of propagating cascades. The tolerance parameter is chosen to describes a smooth transition from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the viewpoint of complex network

Security, protection, and control of power systems with large-scale wind power penetration

As the number of wind generation facilities in the utility system is fast increasing, many issues associated with their integration into the power system are beginning to emerge. Of the various issues, this dissertation deals with the development of new concepts and computational methods to handle the transmission issues and voltage issues caused by large-scale integration of wind turbines. This dissertation also formulates a probabilistic framework for the steady-state security assessment of wind power incorporating the forecast uncertainty and correlation. Transmission issues are mainly related to the overloading of transmission lines, when all the wind power generated cannot be delivered in full due to prior outage conditions. To deal with this problem, a method to curtail the wind turbine outputs through Energy Management System facilities in the on-line operational environment is proposed. The proposed method, which is based on linear optimization, sends the calculated control signals via the Supervisory Control and Data Acquisition system to wind farm controllers. The necessary ramping of the wind farm outputs is implemented either by the appropriate blade pitch angle control at the turbine level or by switching a certain number of turbines. The curtailment strategy is tested with an equivalent system model of MidAmerican Energy Company. The results show that the line overload in high wind areas can be alleviated by controlling the outputs of the wind farms step-by-step over an allowable period of time. A low voltage event during a system fault can cause a large number of wind turbines to trip, depending on voltages at the wind turbine terminals during the fault and the under-voltage protection setting of wind turbines. As a result, an N-1 contingency may evolve into an N-(K+1) contingency, where K is the number of wind farms tripped due to low voltage conditions. Losing a large amount of wind power following a line contingency might lead to system instabilities. It is important for the system operator to be aware of such limiting events during system operation and be prepared to take proper control actions. This can be achieved by incorporating the wind farm tripping status for each contingency as part of the static security assessment. A methodology to calculate voltages at the wind farm buses during a worst case line fault is proposed, which, along with the protection settings of wind turbines, can be used to determine the tripping of wind farms. The proposed algorithm is implemented in MATLAB and tested with MidAmerican Energy reduced network. The result shows that a large amount of wind capacity can be tripped due to a fault in the lines. A probabilistic framework to handle the uncertainty in day-ahead forecast error in order to correctly assess the steady-state security of the power system is presented. Stochastic simulations are conducted by means of Latin Hypercube sampling along with the consideration of correlations. The correlation is calculated from the historical distribution of wind power forecast errors. The results from the deterministic simulation based on point forecast and the stochastic simulation show that security assessment based solely on deterministic simulations can lead to incorrect assessment of system security. With stochastic simulations, each outcome can be assigned a probability and the decision regarding control actions can be made based on the associated probability

Enhanced AC Quasi-steady State Cascading Failure Model for Grid Vulnerability Analysis under Wind Uncertainty

This paper presents several enhancements on a mixed OPF-stochastic cascading failure model to study the impacts of renewable energy resource uncertainty on grid vulnerability. The improved quasi-steady state (QSS) cascading failure model incorporates AC power flow calculations thus allowing us to simulate voltage-related failures in the grid. The under-voltage load shedding (UVLS) relays are modeled along with a stochastic time-inverse overload relay to accurately simulate the protective system response. In addition, more realistic assumptions are considered in the modeling of wind power penetration using geographical information of grid topology and wind potential map for a given geographical area. The effectiveness of the proposed framework is evaluated on a 500-bus synthetic network developed based on the footprints of South Carolina. The enhanced model allows us to more accurately simulate cascades in the power system with high penetration of erratic renewables and identify weak points

Embedded intelligence for electrical network operation and control

Integrating multiple types of intelligent, mulitagent data analysis within a smart grid can pave the way for flexible, extensible, and robust solutions to power network management

Modeling Cascading Failures in Power Systems in the Presence of Uncertain Wind Generation

One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs. The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact of RE penetration on grid vulnerability to CF. We modeled uncertainty injected from different sources by analyzing actual high-resolution data from North American utilities. Next, we proposed two CF simulation models based on simplified DC power flow and full AC power flow to investigate system behavior under different operating conditions. Simulations show a dramatic improvement in the line flow uncertainty estimation based on the proposed model compared to the simplified DC OPF model. Furthermore, realistic assumptions on the integration of RE resources have been made to enhance our simulation technique. The proposed model is benchmarked against the historical blackout data and widely used models in the literature showing similar statistical patterns of blackout size

Portuguese transmission grid incidents risk assessment

Documento confidencial. Não pode ser disponibilizado para consultaTese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

Risk-based security assessment for operating electric power systems

The power system is a widespread and complex network whose complete behavior, at present, still remains partially characterized. Power systems have operated in most cases reliably, but conservatively with the help of many deterministic techniques that rely heavily on the modeling of system components and the associated dynamics. Now, with increasing competition and growing demand, the power system, however, has been shifting from a deterministically regulated system to a competitive and uncertain market environment. Power utilities are required to have a comprehensive knowledge of the risks as well as benefits in their transmission operations. Our interest is motivated by this need of the industry to provide a method to quantify the risk of operating a power system with consideration to the probabilistic nature of system behaviors. The objective of this dissertation is to develop a foundation of risk-based bulk power system security assessment that leads to the definition, calculation, and application of the risk in operating electric power systems. The work includes three parts of risk assessments: transmission line thermal overload, voltage insecurity, and composite risk assessments. Both the probability of insecurity problems and their cost consequences are measured such that an expected monetary impact is given as the measurement of risk. This quantitative measurement of thermal, voltage, and composite risk is helpful for the operator to trade off the benefits and costs in the competitive utility environment. For making this economic tradeoff, several decision criteria, including both deterministic and probabilistic strategies, from conservative to greedy preference, are introduced to aid the operator to make operating decisions. This research establishes a bridge between power system security and economics by the index of risk that is compatible with the economic results of market-based electricity trading. Both the method to quantify the risk and the ways to apply it in decision-making make contributions to the power industry