Bulk system reliability evaluation in a deregulated power industry

The basic function of an electric power system is to supply its customers with electric energy as economically as possible and with a reasonable degree of continuity and quality. Power system reliability evaluation techniques are now highly developed through the work of many researchers and engineers. It is expected that the application of power system reliability evaluation in bulk power systems will continue to increase in the future especially in the newly deregulated power industry. This thesis presents research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission deficiencies in composite system adequacy assessment. The research was done using a previously developed software package designated as MECORE. Many generating companies in both the traditionally regulated and newly deregulated electrical power industry have large generating units that can operate in one or more derated states. In this research work, load point and system reliability indices are evaluated using two-state and multi-state generating unit models to examine the impact of incorporating multi-state generating unit models in composite system adequacy assessment. The intention behind deregulation in the power industry is to increase competition in order to obtain better service quality and lower production costs. This research illustrates how Canadian power systems have performed in the past using data compiled by the Canadian Electricity Association. A procedure to predict similar indices is presented and used to estimate future performance and the effects of system modifications. The incentives for market participants to invest in new generation and transmission facilities are highly influenced by the market risk in a deregulation environment. An adequate transmission system is a key element in a dynamic competitive market. This thesis presents a procedure to identify transmission deficiencies in composite generation and transmission system. The research work illustrated in this thesis is focused on the application of probabilistic techniques in composite system adequacy assessment and particularly in the newly deregulated electric power industry. The conclusions and the techniques presented should prove valuable to those responsible for power system planning

Priority Events Determination For The Risk-oriented Management Of Electric Power System

The task of risk-oriented management of the electric power system in conditions of multi-criteria choice is considered. To determine the most effective measures, the implementation of which will reduce the magnitude of the risk of an emergency situation, multi-criteria analysis methods are applied. A comparative analysis of the multi-criteria alternative (ELECTRE) ranking method based on utility theory and the Pareto method, which defines a subset of non-dominant alternatives, is carried out. The Pareto method uses in its algorithm only qualitative characteristics of the advantage and allows only to distinguish a group of competitive solutions with the same degrees of non-dominance. Given the large number of evaluation criteria, the Pareto method is ineffective because the resulting subset of activities is in the field of effective trade-offs, when no element of the set of measures can be improved without degrading at least one of the other elements. The ELECTRE method is a pairwise comparison of multi-criteria alternatives based on utility theory. This method allows to identify a subset of the most effective activities. The number of elements of the resultant subset is regulated by taking into account the coefficients of importance of optimization criteria and expert preferences

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

Quasi-Dynamic Frame Coordination For Ultra- Reliability and Low-Latency in 5G TDD Systems

The fifth generation (5G) mobile technology features the ultra-reliable and low-latency communications (URLLC) as a major service class. URLLC applications demand a tight radio latency with extreme link reliability. In 5G dynamic time division duplexing (TDD) systems, URLLC requirements become further challenging to achieve due to the severe and fast-varying cross link interference (CLI) and the switching time of the radio frame configurations (RFCs). In this work, we propose a quasi-dynamic inter-cell frame coordination algorithm using hybrid frame design and a cyclic-offset-based RFC code-book. The proposed solution adaptively updates the RFCs in time such that both the average CLI and the user-centric radio latency are minimized. Compared to state-of-the-art dynamic TDD studies, the proposed scheme shows a significant improvement in the URLLC outage latency, i.e., 92% reduction gain, while boosting the cell-edge capacity by 189% and with a greatly reduced coordination overhead space, limited to B-bit

Model-based fault detection and isolation for wind turbine

In this paper, a quantitative model based method is proposed for early fault detection and diagnosis of wind turbines. The method is based on designing an observer using a model of the system. The observer innovation signal is monitored to detect faults. For application to the wind turbines, a first principles nonlinear model with pitch angle and torque controllers is developed for simulation and then a simplified state space version of the model is derived for design. The fault detection system is designed and optimized to be most sensitive to system faults and least sensitive to system disturbances and noises. A multiobjective optimization method is then employed to solve this dual problem. Simulation results are presented to demonstrate the performance of the proposed method

Variance-constrained multiobjective control and filtering for nonlinear stochastic systems: A survey

The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H 2 / H ∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out

An empirical learning-based validation procedure for simulation workflow

Simulation workflow is a top-level model for the design and control of simulation process. It connects multiple simulation components with time and interaction restrictions to form a complete simulation system. Before the construction and evaluation of the component models, the validation of upper-layer simulation workflow is of the most importance in a simulation system. However, the methods especially for validating simulation workflow is very limit. Many of the existing validation techniques are domain-dependent with cumbersome questionnaire design and expert scoring. Therefore, this paper present an empirical learning-based validation procedure to implement a semi-automated evaluation for simulation workflow. First, representative features of general simulation workflow and their relations with validation indices are proposed. The calculation process of workflow credibility based on Analytic Hierarchy Process (AHP) is then introduced. In order to make full use of the historical data and implement more efficient validation, four learning algorithms, including back propagation neural network (BPNN), extreme learning machine (ELM), evolving new-neuron (eNFN) and fast incremental gaussian mixture model (FIGMN), are introduced for constructing the empirical relation between the workflow credibility and its features. A case study on a landing-process simulation workflow is established to test the feasibility of the proposed procedure. The experimental results also provide some useful overview of the state-of-the-art learning algorithms on the credibility evaluation of simulation models