Non-Stationary Random Process for Large-Scale Failure and Recovery of Power Distributions

A key objective of the smart grid is to improve reliability of utility services to end users. This requires strengthening resilience of distribution networks that lie at the edge of the grid. However, distribution networks are exposed to external disturbances such as hurricanes and snow storms where electricity service to customers is disrupted repeatedly. External disturbances cause large-scale power failures that are neither well-understood, nor formulated rigorously, nor studied systematically. This work studies resilience of power distribution networks to large-scale disturbances in three aspects. First, a non-stationary random process is derived to characterize an entire life cycle of large-scale failure and recovery. Second, resilience is defined based on the non-stationary random process. Close form analytical expressions are derived under specific large-scale failure scenarios. Third, the non-stationary model and the resilience metric are applied to a real life example of large-scale disruptions due to Hurricane Ike. Real data on large-scale failures from an operational network is used to learn time-varying model parameters and resilience metrics.Comment: 11 pages, 8 figures, submitted to IEEE Sig. Pro

Key Technical Challenges for the Electric Power Industry and Climate Change

This paper, prepared by the Climate Change Technology Subcommittee, a subcommittee of the Power and Energy Society Energy Development and Power Generation Committee, identifies key technical issues facing the electric power industry, related to global climate change. The technical challenges arise from: 1) impacts on system operating strategies, configuration, and expansion plans of emission-reducing technologies; 2) power infrastructure response to extreme weather events; 3) effects of government policies including an expanded use of renewable and alternative energy technologies; and 4) impacts of market rules on power system operation. Possible lessons from other industries\u27 responses to climate change are explored

Rapid tracking of bus voltages using synchro phasor assisted state estimator

State estimation has a key role in secure operation of power systems and management of power markets. It calculates the optimal estimates of the system states using the available measurements. Increasing number of phasor measurement units (PMU) installed in power systems motivated their integration also into state estimators which so far relied solely on SCADA measurements. However, different refresh rates of PMU and SCADA measurements present a challenge in their efficient integration. This paper proposes a computationally efficient state estimator, which is based on least absolute value (LAV) estimator, to handle multiple PMU measurements received in between two consecutive SCADA measurements in the presence of a limited number of PMUs

Metrics for Success Performance Metrics for Power System State Estimators and Measurement Designs

Power system state estimators (ses) have come a long way since the introduction of the concept nearly four decades ago by Fred Schweppe. Over the years, the concept's initial formulation, implementation techniques, computational requirements, data manipulation and storage capabilities, and measurement types have changed significantly. Today, SEs are instrumental in facilitating the security and reliability of power system operation and play an important role in the management of power markets where transactions have to be carefully evaluated for feasibility and determination of real-time prices. One of the most recent developments in SEs has been the availability of synchronized phasor measurements and their introduction into the state estimation process. Synchrophasor-assisted state estimation (SPASE) is changing the way we view and operate the grid. As such, the ability to monitor and maintain SE performance within known performance standards (metrics) is a new practice. Unlike deterministic applications such as power fl ow, the state estimation solution is not deterministic and depends on the statistical characteristics of the measurements as well as the level of certainty of the assumed network model

Fluidized bed reactor for polyethylene production. The influence of polyethylene prepolymerization

This work addresses the influence of the prepolymerization of the catalyst particle on the fluidized bed reactor for polyethylene production. The influence of prepolymerization on the temperature and concentration gradients throughout the reactor was studied. The results obtained through simulations confirm industrial observations of the advantages of prepolymerization and extend these observation, showing the viable operational conditions for different superficial gas velocities and gas feeding temperatures as a function of the degree of prepolymerization