L. Goel

A reliability test system for educational purposes-basic distribution system data and results

A description is presented of an electrical distribution system for use in teaching power system reliability evaluation. It includes all the main elements found in practical systems. However, it is sufficiently small that students can analyze it using hand calculations and hence fully understand reliability models and evaluations techniques. All the data needed to perform basic reliability analyses are included in this work. It also contains the basic results for a range of case studies and alternative design/operating configurations. >

Control Strategy to Mitigate the Impact of Reduced Inertia Due to Doubly Fed Induction Generators on Large Power Systems

The present work is based on developing a control strategy to mitigate the impact of reduced inertia due to significant DFIG penetration in a large power system. The paper aims to design a supplementary control for the DFIG power converters such that the effective inertia contributed by these wind generators to the system is increased. The paper also proposes the idea of adjusting pitch compensation and maximum active power order to the converter in order to improve inertial response during the transient with response to drop in grid frequency. Results obtained on a large realistic power system indicate that the frequency nadir following a large power impact in the form of generators dropping out is effectively improved with the proposed control strategy. The proposed control is also validated against the sudden wind speed change in the form of wind gust downs and wind ramp downs occurring in conjunction with the generators dropping out. A beneficial impact in terms of damping power system oscillations is also observed, which is validated by eigenvalue analysis. The affected mode is then excited with a large disturbance in time domain. The damping improvement observed in time domain and subsequent Prony analysis support the result obtained from eigenvalue analysis.

Harmonizing AC and DC: A Hybrid AC/DC Future Grid Solution

It has been over 100 years since Thomas Edison built the first direct current (dc) electricity supply system on 4 September 1882, at Pearl Street in New York City. Many prominent events occurred in the electricity supply industry after that. The first one, ?the war of currents,? started in 1888. Thomas Edison and his dc distribution system were on one side, and George Westinghouse and Nikolai Tesla with the alternating current (ac) system were on other side. The war ?ended? in about 1891 when ac won as the dominant power supply medium. The key behind the ac win was the invention of the transformer that could easily step up medium voltage to high and extra-high voltage for long-distance power transfer from a remote ac generation station to load centers hundreds of kilometers away with lower transmission losses. Transformers can also step down high voltage back to low voltage at load stations to supply the low-voltage equipment. Since the end of the war, ac power systems have been developed and expanded at a tremendous speed from the initial small isolated networks, with each supplying only lighting and motor loads with a few hundreds of customers, to its current scale of super interconnected networks each supplying billions of customers over large geographic areas in one or several countries. The voltage levels and capacities of transmission networks have increased from the first commercialized three-phase ac system with only 2.4 kV, 250 kW in the town of Redlands, California, United States, to the first commercial long-distance, ultra-high-voltage, ac transmission line in China with 1,000 kV, 2,000 MW. Transmission distance has been increased from several miles to over thousands of kilometers (miles). With such major achievements, it is little wonder that the ac power system became the top engineering achievement of the 20th century. Does this mean that dc is gone? The answer is an unambiguous no. What has happened in the past 50 years, such as applications of advanced control technologies in conventional power system loads, the power electronics based high-voltage dc (HVdc) transmission, and the additional renewable power sources in low-voltage distribution system, calls for a rethink about dc and ac in electricity supply systems.

Long-Term Reserve Expansion of Power Systems With High Wind Power Penetration Using Universal Generating Function Methods

In a power system with high wind power penetration, reliability-based reserve expansion is a major problem of system planning and operation due to the uncertainty and fast fluctuation of wind speeds. This paper studied the impact of high wind power penetration on the system reserve and reliability from long-term planning point of view utilizing universal generating function (UGF) methods. The reliability models of wind farms and conventional generators are represented as the corresponding UGFs, and the special operators for these UGFs are defined to evaluate the customer and the system reliabilities. The effect of transmission network on customer reliabilities is also considered in the system UGF. The power output models of wind turbine generators in a wind farm considering wind speed correlation and un-correlation are developed, respectively. A reliability-based reserve expansion method is proposed to determine the conventional reserve required for power systems with high wind power penetration. The IEEE-RTS has been modified to illustrate the applications of the proposed method.

Determination of reliability worth for distribution system planning

There is an ever growing demand to justify reliability projects on a more quantifiable basis, i.e. investments related to the provision of service reliability needs to be carefully evaluated in regard to their cost and benefit implications. In addition, utilities are recognizing the significant customer and community costs that are incurred when electric supply is abruptly curtailed. Consequently, the utility industry is under pressure to assess their reliability evaluation tools and formulate methods for incorporating the economics of reliability in the decision-making process. This paper is concerned with the evaluation of a reliability worth index that can be used to make decisions in distribution system planning and design. The reliability worth index is termed the interrupted energy assessment rate (IEAR) and is obtained by relating the reliability indices to the customer cost of interruption data. Three fundamentally different approaches for evaluating distribution system reliability worth indices are presented and compared using a small but comprehensive test system. The impact on the worth indices of distribution system operating policies and configurations is also illustrated using the three methods. The worth indices developed can be used to determine the monetary implications of customer supply interruptions thereby incorporating economics in the reliability cost-benefit equation. >

Demand Side Load Management of Smart Grids using intelligent trading/Metering/ Billing System

Conventional power systems have been experiencing transition from centralized supply side management to decentralized supply&demand side management due to power system restructuring and addition of distributed generations (DGs) and Smart Grids (SGs) or Smart Distribution Systems (SDSs) with renewable power sources in the past two decades. Therefore load management under the new operating environment becomes more difficult than that under the conventional environment. This paper presents an Intelligent Metering/Trading/Billing System (ITMBS) and its implementation in Demand Side Load Management (DSLM) of SGs and SDSs. The ITMBS provides real time price information to customers through communication networks. Customers can adjust their demands through setting the operating time of some of the home appliances with energy storage feature such as heaters based on the real time prices to shift their consumptions and save cost. Customers can also participate in Direct Load Control (DLC) program in control center of a micro grid to shift their air condition demands through changing on and off circle based on the real time prices and weather conditions to save energy and to shift system peak load.

Strategic self-dispatch considering ramping costs in deregulated power markets

Ramp rates of generators are generally specified within elastic range of the strength of the shaft to safeguard the rotor from fatigue. These limits can, however, be exceeded, albeit at the risk of reducing the rotor life. Such effects on the rotor life can be compensated by incorporating appropriate ramping costs. Power demand and power price in deregulated power markets have shown a tendency of sudden wide excursions over short intervals of time. The ability to respond to such fast change in demand and price can be quite rewarding. This provides the motivation to utilize the ramping rates beyond traditional elastic limits. This paper studies the strategic use of ramping rates beyond elastic limits in a power producers self-dispatch in a power market with price and demand volatility. A set of ramping processes has been developed from ramping-cost versus ramping time relationships to derive the total operation cost including ramping costs for various levels of ramping rates exceeding elastic limits. A thorough theoretical analysis has been conducted for the selection of the optimal ramping process under different conditions. A numerical example is presented to highlight the potential benefits from the optimal use of these ramping processes. It is seen that the benefit from the strategic use of ramp rates beyond elastic limits not only depends on the high price in the power market but also on the initial loading of the generator which limits the capacity available for dispatch.

Monte Carlo simulation-based reliability studies of a distribution test system

Abstract This paper presents the results of a Monte Carlo simulation (MCS) approach to the Roy Billinton distribution test system (RBTS). The paper presents the load point reliability indices and system performance indices using the MCS method for five distribution system-buses 2, 3, 4, 5 and 6 of the RBTS. Four possible probability distributions of times to repair (TTR) and times to switching (TTS) of components are incorporated in the simulation studies. The cumulative probability distributions of system performance indices such as SAIFI and SAIDI for the four different distributions of TTR and TTS are also presented. The results obtained by the simulation method are compared with those available for the RBTS using an analytical approach. The study results show that the simulation method gives acceptable reliability indices and can also be used to provide information on the probability distributions associated with the predicted indices for different distributions of TTR and TTS.

Unreliability cost assessment of an electric power system using reliability network equivalent approaches

Unreliability cost evaluation of an entire power system provides a set of indices that can be used by a system planner to balance the investments in different segments of the system in order to provide acceptable load point reliability. This paper utilizes reliability network equivalent techniques to evaluate the customer load point unreliability cost indices caused by outages in different segments of the power system. The equivalent multistate generator (EMG), the equivalent mutistate lateral section (EMLS), and the equivalent multistate series element (EMSE) are introduced. The percentage distribution of unreliability costs for system segments is determined to find the weak segments in the system. A test system is analyzed to illustrate the application of these techniques.

A Novel Wavelet-Based Ensemble Method for Short-Term Load Forecasting with Hybrid Neural Networks and Feature Selection

In this paper, a new ensemble forecasting model for short-term load forecasting (STLF) is proposed based on extreme learning machine (ELM). Four important improvements are used to support the ELM for increased forecasting performance. First, a novel wavelet-based ensemble scheme is carried out to generate the individual ELM-based forecasters. Second, a hybrid learning algorithm blending ELM and the Levenberg-Marquardt method is proposed to improve the learning accuracy of neural networks. Third, a feature selection method based on the conditional mutual information is developed to select a compact set of input variables for the forecasting model. Fourth, to realize an accurate ensemble forecast, partial least squares regression is utilized as a combining approach to aggregate the individual forecasts. Numerical testing shows that proposed method can obtain better forecasting results in comparison with other standard and state-of-the-art methods.