Case In Practical Systems Research Articles

A Novel Approach for Monitoring of Voltage Stability Margin subsequent to Observability Analysis: a Practical System Case Study

Abstract. This paper presents a practical approach for voltage stability margin (VSM) monitoring in a pilot project, in which two related steps are considered. Through the planning stage of a practical project, it is necessary to make the grid observable to actualize the VSM monitoring during the operation. So, an observability based VSM monitoring scheme is proposed in this work. Firstly, using observability analysis and state estimation requirement, optimal location of metering devices is determined for the Hormoz distribution grid as a practical system case study. Secondly, using the information sent by metering devices, the VSM monitoring is evaluated using a transfer function (TF) model during the operation. To assess the performance of the proposed method, it is compared with a case, in which metering infrastructures are connected to the whole of buses. For further simulation, input data combinations of the TF model are varied throughout two different scenarios.

Energy aware improved least and most significant bit arbitration algorithm for WORM tags

Passive Radio Frequency Identification systems have gained enormous attention and popularity especially after its adoption in time and data critical systems. Theoretically, these systems have the potential to read over 100 tags per second in applications which are well insulated from RF noise. Nevertheless, this may not be the case in practical systems, as tag collision is one of the major deterrents affecting the recognition rate. This paper exhaustively analyses the existing probabilistic, deterministic and hybrid algorithms on collision resolutions. In probabilistic algorithms, tags send their entire ID to the RFID reader in respective slots while tags in deterministic algorithms respond bit by bit based on the RFID reader’s query. To minimize identification delay, tag communication overhead and high energy consumption, a new energy efficient collision resolution strategy named Improved Least and Most Significant Bit Algorithm (LaMSBA) is introduced to effectively singulate a tag and increase the identification efficiency in changing tag population even when the bits in tag ID’s are randomly or uniformly distributed. Extensive simulation studies show that LaMSBA can be chosen as better alternatives for dense time and data critical RFID enabled systems. In addition, M/G/1 Queuing model is suitably identified and the the analytical results concluded that LaMSBA is able to maintain the steady state condition even when Class 1 tags arrive at the rate of 15 tags/second in the reader’s interrogation zone.

Doppler Spread Estimation for Broadband Wireless OFDM Systems Over Rician Fading Channels

In this paper, we present a new Doppler spread estimation algorithm for broadband wireless orthogonal frequency division multiplexing (OFDM) systems with fast time-varying and frequency-selective Rayleigh or Rician fading channels. The new algorithm is developed by analyzing the statistical properties of the power of the received OFDM signal in the time domain, thus it is not affected by the influence of frequency-domain inter-carrier interference (ICI) introduced by channel variation within one OFDM symbol. The operation of the algorithm doesn’t require the knowledge of fading channel coefficients, transmitted data, or signal-to-noise ratio (SNR) at the receiver. It is robust against additive noise, and can provide accurate Doppler spread estimation with SNR as low as 0 dB. Moreover, unlike existing algorithms, the proposed algorithm takes into account the inter-tap correlation of the discrete-time channel representation, as is the case in practical systems. Simulation results demonstrate that this new algorithm can accurately estimate a wide range of Doppler spread with low estimation latency and high computational efficiency.

Performance of collaborative spectrum sensing for cognitive radio in the presence of gaussian channel estimation errors

The performance of collaborative spectrum sensing for cognitive radio in a lognormal shadowing and Rayleigh fading channel is investigated. Unlike previous works that assume perfect knowledge of the average channel signal-to-noise ratio, this paper considers the realistic case where estimation of the average channel signal-to-noise ratio has error. Furthermore, while previous works have designed and examined estimators based on assuming that the channel samples used in the average signal-to-noise ratio estimators are noiseless, the present work assumes that the channel samples are noisy, as is the case in practical systems. Numerical results show that the probability of missed opportunity decreases as the estimation error decreases, as expected. Perhaps unexpectedly, the results also show that in the presence of noise, there exists a threshold phenomenon for the noise level. Below a particular threshold, the probability of missed opportunity increases as the noise level increases. Yet above this threshold, the probability of missed opportunity decreases as the noise level increases.