Band 16, Heft 6 -

Wide area backup protection algorithm based on fault component identification is the heart of the whole wide area backup protection system, its validity and reliability is a problem which needs to be first considered in the engineering practice applications of wide area backup protection system. Wide are backup protection algorithm mainly use two kinds of wide area information to realize protection criterion, one is electrical quantity information, such as voltage, current, etc. Another one is protection action and circuit breaker information. The wide area backup protection algorithm based on electrical quantity information is mainly utilizing the significant change of electrical quantity to search fault component, and the primary means include current differential method of wide area multi-measuring points, the comparison method of calculation and measurement, the multiple statistics method. In this paper, a novel and effective association analysis of system failure in wide area backup protection system will be discussed carefully, and the analytical results are successful and reliable.

Owing to the technological development of natural gas exploration and the increasing penetration of gas-fired power generation, gas and power systems inevitably interact with each other from both physical and economic points of view. In order to effectively assess the two systems’ interdependency, this paper proposes a systematic modeling framework and constructs simulation platforms for coupled gas and power systems in an energy market environment. By applying the proposed approach to the Australian national electricity market (NEM) and gas market, the impacts of six types of market and system factors are quantitatively analyzed, including power transmission limits, gas pipeline contingencies, gas pipeline flow constraints, carbon emission constraints, power load variations, and non-electric gas load variations. The important interdependency and infrastructure weakness for the two systems are well studied and identified. Our work provides a quantitative basis for grid operators and policy makers to support and guide operation and investment decisions for electric power and natural gas industries.

This paper considers a microgrid connected with a medium-voltage (MV) distribution network. It is assumed that the microgrid, which is managed by a prosumer, operates in a competitive environment and participates in the day-ahead market. Then, as the first step of the short-term management problem, the prosumer must determine the bids to be submitted to the market. The offer strategy is based on the application of an optimization model, which is solved for different hourly price profiles of energy exchanged with the main grid. The proposed procedure is applied to a microgrid and four different its configurations were analyzed. The configurations consider the presence of thermoelectric units that only produce electricity, a boiler or/and cogeneration power plants for the thermal loads, and an electric storage system. The numerical results confirmed the numerous theoretical considerations that have been made.

This paper proposes a simplified mathematical model to predict the impact of connection of Distributed Generators (DGs) to the ac grid. The model allows the user to examine the fluctuations in the magnitude of voltages at different nodes in the distribution system. In order to use the model, the user does not require a commercial simulation software making it a handy tool for a practicing engineer. Analysis has been presented to describe how the detailed mathematical model of the system is reduced using elementary matrix manipulation techniques to obtain the final simplified mathematical model. Simulation results are presented to verify the mathematical model with a ring distribution system with three DGs connected to it and the results validate those attained from the mathematical model.

In this paper, the effect of plug-in electric vehicles is studied on the smart distribution system with a standard IEEE 30-bus network. At first, harmonic power flow analysis is performed by Newton-Raphson method and by considering distorted substation voltage. Afterward, proper sizes of capacitors is selected by cuckoo optimization algorithm to reduce the power losses and cost and by imposing acceptable limit for total harmonic distortion and RMS voltages. It is proposed that the impact of generated current harmonics by electric vehicle battery chargers should be factored into overall load control strategies of smart appliances. This study is generalized to the different hours of a day by using daily load curve, and then optimum time for charging of electric vehicles batteries in the parking lots are determined by cuckoo optimization algorithm. The results show that injecting harmonic currents of plug-in electric vehicles causes a drop in the voltage profile and increases power loss. Moreover, charging the vehicle batteries has more impact on increasing the power losses rather than the harmonic currents effect. Also, the findings showed that the current harmonics has a great influence on increasing of THD. Finally, optimum working times of all parking lots was obtained for the utilization cost reduction.

In light of the growing number of reimbursement requests processed from consumers for electrical damage to equipment, supposedly caused through the manifestation of anomalies on the power grid, there comes the need for reliable means for providing a decision on the issues highlighted herein. Through the recognition that in the current context, the procedures used are based on reviews, information and records of occurrences in the field, there has been significant inadequacy and fragility in the issuing of conclusive advice or opinions. In particular, the search for mechanisms grounded in classical principles and accepted in electrical engineering presents itself as an important challenge on which to base the decision making process in full awareness of its incumbent science and technology. Therefore, with the aim of meeting these assumptions, the study in question excels in its presentation of the principles that guided the software analysis, which intend above all else to correlate cause and effect. The elaborated strategy involves modelling stages as well as studies aimed at: distribution supply reproduction; characterization of the distribution network to the complainant consumer; representation of the diverse electro-electronic appliances and lastly, a proposal for correlating the disturbances impacting on equipment with their dielectric and thermal supportability requirements. For the purpose of illustrating the software process, an actual case study coupled with a loss and claim scenario is presented.

From the perspective of global warming suppression and the depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), have been gaining attention in worldwide. Houses or buildings with PV and heat pumps (HPs) are recently being used in residential areas widely due to the time of use (TOU) electricity pricing scheme which is essentially inexpensive during middle-night and expensive during day-time. If fixed batteries and electric vehicles (EVs) can be introduced in the premises, the electricity cost would be even more reduced. While, if the occupants arbitrarily use these controllable loads respectively, power demand in residential buildings may fluctuate in the future. Thus, an optimal operation of controllable loads such as HPs, batteries and EV should be scheduled in the buildings in order to prevent power flow from fluctuating rapidly. This paper proposes an optimal scheduling method of controllable loads, and the purpose is not only the minimization of electricity cost for the consumers, but also suppression of fluctuation of power flow on the power supply side. Furthermore, a novel electricity pricing scheme is also suggested in this paper.

With rapid speed on electricity using and increasing in renewable energy, more and more research pay attention on distribution grid planning. For the drawbacks of existing research, this paper proposes a new risky group decision-making method for distribution grid planning. Firstly, a mixing index system with qualitative and quantitative indices is built. On the basis of considering the fuzziness of language evaluation, choose cloud model to realize “quantitative to qualitative” transformation and construct interval numbers decision matrices according to the “3En” principle. An m-dimensional interval numbers decision vector is regarded as super cuboids in m-dimensional attributes space, using two-level orthogonal experiment to arrange points uniformly and dispersedly. The numbers of points are assured by testing numbers of two-level orthogonal arrays and these points compose of distribution points set to stand for decision-making project. In order to eliminate the influence of correlation among indices, Mahalanobis distance is used to calculate the distance from each solutions to others which means that dynamic solutions are viewed as the reference. Secondly, due to the decision-maker’s attitude can affect the results, this paper defines the prospect value function based on SNR which is from Mahalanobis-Taguchi system and attains the comprehensive prospect value of each program as well as the order. At last, the validity and reliability of this method is illustrated by examples which prove the method is more valuable and superiority than the other.