Volume 9, Issue 4

This paper proposed a method for reliability assessment of the protection system for a switchyard by fault-tree analysis considering uncertainty of unavailability for an element. Unavailability of an element with uncertainty is expressed with the fuzzy set. The fault-tree analysis incorporated with the fuzzy set is employed to conduct the reliability assessment. The importance of elements influencing reliability can be achieved by the Fuzzy Importance Measure. Compared with traditional methods, the fault-tree analysis requires less computation. In this paper, a 345 kV switchyard in the 3rd nuclear power plant in Taiwan serves as an example for illustrating the results of the proposed method.

The need for dynamic loading of overhead lines requires reliable assessment tools that should be able to predict both the evolution of the hot-spot temperature and the associated maximum allowed duration, at any load level and on the basis of the actual conductor thermal state and environmental conditions. In order to address this problem, the paper proposes the employment of a smart sensor network distributed along the line route. Each network's node, starting from on-line measurements, assesses, by an indirect method of parameter identification, the value of the main variables which regulate the heat exchange between the conductor and its surrounding. Then, starting from these data, each node calculates the load capability curve by solving iteratively a built in dynamic thermal model and transmits the results to a central server by a cooperative based communication paradigm. To assess the performances of the proposed solution, experimental studies obtained on a laboratory overhead line are presented and discussed.

This paper addresses the issue of the application of PhotoVoltaic (PV) Distributed Generation (DG) units for supplying reactive power to the grid. In order to reach this aim, an advanced control scheme to suitably drive the injection of both active and reactive power into a MV radial distribution grid has been developed. Such algorithm allows a decoupled control of active and reactive power by properly adjusting the modulating signals of a PWM interface converter with the grid. A closed loop regulation scheme has been derived and guidelines for the choices of the reference quantities and for the design of the regulators are provided. The control algorithm has been applied to a real MV grid-connected PV power plant, which has been simulated in the PSCAD – EMTDC electromagnetic environment, in order to represent, with high detail, every system component and to thoroughly analyze the occurring electromagnetic transients. The positive effect of reactive power support to the grid from the PV unit has been highlighted, showing benefits on the grid current and voltage profiles with respect to the classical configuration, where the DG system behaves as a sole active power source.

This paper is concerned with the unit commitment of hydro generating units on an hourly basis throughout a single day. A performance criterion that takes into consideration variations in tailrace elevation, penstock head loss and turbine-generator efficiency is suggested as the objective function for the optimization model. A heuristic procedure based on Lagrangian Relaxation was implemented to solve the problem. The approach was then tested on a system composed of sixteen hydro plants, one hundred generating units, and an installed capacity of 21,933 MW, in the Brazilian power system. The scheduling of generation verified for a typical day was used for comparison with the solution proposed by this procedure. The results show a significant improvement in terms of hydro conversion efficiency.

Differential evolution (DE) has been proved to be a powerful evolutionary algorithm for global optimization in many engineering problems. The performance of this type of evolutionary algorithms is heavily dependent on the setting of control parameters. Proper selection of the control parameters is very important for the success of the algorithm. Optimal settings of control parameters of differential evolution depend on the specific problem under consideration. In this paper, a study of control parameters on differential evolution based combined economic emission dispatch with valve-point loading and transmission loss is conducted empirically. The problem is formulated considering equality constraints on power balance and inequality constraints on generation capacity limits as well as the transmission losses and effects of valve point loadings. The feasibility of the proposed method is demonstrated on a fourteen-generator system. The results of the effect of the variation of different parameters are presented systematically and it is observed that the search algorithm may fail in finding the optimal value if the parameter selection is not done with proper attention.

Transmission network expansion planning is a very critical problem due to not only the huge investment cost involved, but also the associated security issues. Any long range planning problem is confronted with the challenge of non-statistical uncertainty in the data. Although large number of papers have been published in this area, the efforts to tackle the above mentioned security and uncertainty issues have been relatively very few, due to the formidable complexity involved. This paper tries to bridge this gap by proposing a technique to tackle these problems. Boundary DC power flow is used to ascertain the worst power flows on the lines. A simple basic binary Genetic algorithm is used to solve the optimization problem as an illustration. Results for two sample test systems have been obtained to demonstrate the potential of the proposed method.

Transmission system structure has an essential effect on the reliability of the power system and electricity market performance, especially when producers bid strategically. As part of on-going research on the design of a robust algorithm for expansion planning of the transmission grid in the Australian electricity market, this paper presents a framework which addresses: (1) the security of power delivery to the load points of the transmission system in case of single line outages; (2) the minimization of transmission system lost load; (3) an efficient electricity market for market participants; (4) construction and maintenance costs of transmission augmentation options; and (5) operation efficiency of the transmission grid.The suggested algorithm benefits from the dynamic programming and sensitivity analysis approaches along with the aggregation method in its multi-criteria decision-making to locate the optimum configuration of a future transmission system. A set of indices, which account for impacts of the augmentation options of the transmission grid on five aforementioned reliability and market criteria, are proposed and used in the optimum framework for expansion planning of the transmission grid.Although the methodology is promising for expansion planning of the transmission system, considering the sensitivity analysis concept employed, the proposed methodology would be suitable to detect the sensitive areas of the transmission system to be expanded. The tool would be very useful in the case of large scale power systems for a smart reduction of the transmission expansion options.The proposed methodology has been applied to a 6-bus and a modified IEEE 30-bus test system to show the effectiveness of the sensitivity-based algorithm.