Limited Transmission Capacity Research Articles

Improved Takagi-Sugeno fuzzy output tracking control for nonlinear networked control systems

This paper deals with the output tracking control problem for nonlinear networked control systems (NCSs) described by Takagi-Sugeno (T-S) fuzzy models. Due to the existence of inherent constraints in NCS as communication time-delays and limitation of data transmission capacity, a recent event-triggered scheme proposed in the literature is implemented to reduce the bandwidth utilization. On the other hand, the communication time-delay imposes an asynchronously operation between the proposed T-S fuzzy controller and the T-S fuzzy system handled via new LMI based conditions. Furthermore, a synchronous model operation is also proposed in this paper which allows to design a linear controller which is much simpler to implement. The main results are derived following the selection of an appropriate fuzzy Lyapunov Krasovskii Functional (LKF) together with alternative integral inequalities which lead to less conservative conditions when compared to recent results in the literature. An example illustrates the effectiveness of the proposed output tracking control for NCSs fuzzy models.

Optimal Capacity Proportion and Distribution Planning of Wind, Photovoltaic and Hydro Power in Bundled Transmission System

The wind, photovoltaic and hydro power bundled transmission system attends to become common in Northwest and Southwest of China. To make better use of the power complementary characteristic of different power sources, the installed capacity proportion of wind, photovoltaic and hydro power, and their capacity distribution for each integration node is a significant issue to be solved in power system planning stage. An optimal capacity proportion and capacity distribution model for wind, photovoltaic and hydro power bundled transmission system is proposed here, which considers the power out characteristic of power resources with different type and in different area based on real operation data. The transmission capacity limit of power grid is also considered in this paper. Simulation cases are tested referring to one real regional system in Southwest China for planning level year 2020. The results verify the effectiveness of the model in this paper.

Gerchberg–Saxton algorithm based phase correction in optical wireless communication

Optical wireless communication (OWC) enables to establish the backhaul in the fifth generation (5G) wireless communication networks. The air turbulence, however, could distort the phases of optical signals, thus limit transmission capacity. In this paper, we study the correction of phase distortions by using the Gerchberg–Saxton (GS) algorithm. The air turbulence-induced phase is generated by the Monte-Carlo phase screen method, which characterizes the realistic air turbulence effect on the optical signals. The numerical results reveal that the GS algorithm is able to retrieve the phase information with fast convergence by adopting a proper initial condition. Also, the GS algorithm based phase correction in OWC is confirmed.

Analysis on the accommodation of renewable energy in northeast China

The accommodation and curtailment of renewable energy in northeast China have attracted much attention with the rapid growth of wind and solar power generation. Large amount of wind power has been curtailed or abandoned in northeast China due to several reasons, such as, the redundancy of power supplies, inadequate power demands, imperfect power structure with less flexibility and limited cross-regional transmission capacity. In this paper, we use multi-area production simulation to analyse the accommodation of renewable energy in northeast China by 2020. Furthermore, we suggest the measures that could be adopted in generation, grid and load side to reduce curtailment of renewables.

Efficient Data Forwarding for Machine Type Communications in Internet of Things Networks

The MTC (Machine Type Communications) system is one of the most promising technologies to provide IoT (Internet of Things) applications. The MTC system suffers from congestion due to limited data transmission capacity and burst traffic. The congestion disturbs data delivery, results in an increase of energy consumption due to data retransmission, and finally poses a threat to the providers of IoT applications. In this paper, we focus on the congestion problem and present an efficient data forwarding mechanism to regulate the burst channel access from a large number of MTC devices. To regulate the communication channel access from the devices, we predict the number of devices by separating traffic load into the prediction of the number of devices that newly attempt to have access and the prediction of the number of devices that retry to access the channel. Through simulations, we show that our mechanism improves access success probability and reduces collision probability and access delay.

Singularities Analysis of the Jacobian Matrix Modified in the Continuation Power Flow: Mathematical Modeling

In recent years, the concern for voltage stability issue has gained global highlighted when referring to the energy sector industry, this is because this issue is related to the operation and planning of electrical power systems. Factors such as the increasing energy demand, the transfer of large amounts of power to meet the consumption, combined with the economic and environmental requirements has led the systems operate in stressful conditions (close to their limits), i.e., with small margins of security that is a threat to its stable operating condition. The combination of these factors can be disastrous, enabling the vulnerability of electrical power systems, i.e., exposed to risk of a situation of instability. In the literature, a study to analyze stability and voltage instability is related to the P-V curve (power versus voltage magnitude) and the maximum loading point (MLP) (point on the curve that separates the stable operation of the unstable). The maximum loading point may be consequent to a saddle node bifurcation (SNB) related to transmission capacity limit in an electrical system where the Jacobian matrix is singular, or limit induced bifurcation (LIB), related the reactive power limit of the generator, where the matrix is not singular. In this sense, it is presented in this first part of the paper, an analysis of the modified Jacobian matrices (Jm) of the methods of continuation power flow (CPF) reported in the literature (parameterization methods), the study was developed in order to analyze the changes that the matrix conventional Jacobian (J) have to eliminate the singularity problems in the MLP and in the bifurcation points of each method.

On the uplink outage throughput capacity of hybrid wireless networks with Massive MIMO

In this paper, we investigate theoretical transmission capacity limit of the uplink hybrid wireless network under infrastructure mode. Massive MIMO technology is assumed to be equipped on the base station to further increase the whole network throughput. Multi-user MIMO is preferred over Point-to-Point MIMO to achieve improved scalability and simplify UE design. Another perspective of this paper is to include the fading effect on capacity. Under favorable propagation condition, Massive MIMO greatly mitigates small scale fading effect between each user and base station antenna. Then closed-form outage capacity over large scale fading channel is derived in both low SNR and high SNR scenarios.

Application of Multi-speed Gearbox in Infinitely Variable Transmission

One way to reduce vehicles’ fuel consumption (FC) is to optimize different parts of its powertrain. Among different modern powertrains, continuously variable transmission (CVT) is one of the common types which changes speed ratio between engine and wheels, continuously. Therefore, the CVT allows the engine to operate at its fuel-optimal speed. Due to the limited power transmission capacity and speed ratio range of the CVT, researchers attempted to combine the CVT with a planetary gear train and a fixed ratio mechanism. This mechanism is called infinitely variable transmission (IVT). In this study, a multi-speed gearbox (MSG) is used in the IVT and its impact on the powertrain performance and the vehicle’s FC is investigated. After extracting the governing dynamics of the system, an optimization on the parameters which affect the IVT performance is implemented to minimize the vehicle’s FC. It is observed that the vehicle’s FC for the case of using the optimized IVT equipped with two-speed MSG is almost 5% less than the case of using the optimized six-speed AT transmission in different driving cycles.

Neural network based diagnosis of partial discharge defects patterns at XLPE cable under DC stress

The application of the XLPE cable under DC stress is now being considered as one of the promising tool for enlarging the limited transmission capacity of the traditional electric power cable due to the several technical advantages. Therefore, many research institutes are trying to improve the performance by carrying out experimental investigations related to the reliability of the cable to be used under DC stress. One of them is partial discharge (PD) detection, which is considered as the tool to indicate the insulation state of the apparatus; however, very few reports have been published based on the results obtained for the XLPE cable used under the DC stress. In this work, three different types of artificial defects are designed to produce PD under DC: void, surface and corona discharge defects. Pattern recognition of the detected PD signal is based on modified CAPD method. To improve the PD pattern recognition rate, the training data obtained through neural networks is combined with the results of the frequency domain analysis. Finally, the training data and mean square error of PD patterns obtained through neural networks is compared with the training data obtained with the use of only modified CAPD method.

Three‐wire bipolar high‐voltage direct current line using an existing single‐circuit high‐voltage alternating current line for integrating renewable energy sources in multiterminal DC networks

When compared with conventional point-to-point high-voltage direct current (HVDC) systems, multiterminal HVDC (MTDC) systems are more economical and flexible. MTDC systems can tie distributed high power renewable energy sources (such as offshore wind energy and high-power photovoltaic systems) into AC grid(s). To save in the required infrastructure for DC line installations, existing high-voltage alternating current (HVAC) lines can be converted into DC links. The bipole HVDC concept can be used easily for converting the HVAC lines into DC links, but with a limited transmission capacity. Alternatively, three-wire bipole structure (TWBS) can be used, yet it requires a power electronics-based converter connected in series with one of the wires (modulating wire), which affects the system reliability and adds more complexity. In this study, a new configuration is proposed for converting the HVAC lines into DC links with enhanced power capability compared with the two-wire bipole HVDC system. The proposed approach provides a lower power enhancement compared with that provided by TWBS. However, a higher reliability can be guaranteed as it avoids the series-connected converters. Analytical and simulation studies using Matlab/Simulink platform have been presented in this study to validate the proposed concept.

Gradient Compressive Sensing for Image Data Reduction in UAV Based Search and Rescue in the Wild

Search and rescue operations usually require significant resources, personnel, equipment, and time. In order to optimize the resources and expenses and to increase the efficiency of operations, the use of unmanned aerial vehicles (UAVs) and aerial photography is considered for fast reconnaissance of large and unreachable terrains. The images are then transmitted to control center for automatic processing and pattern recognition. Furthermore, due to the limited transmission capacities and significant battery consumption for recording high resolution images, in this paper we consider the use of smart acquisition strategy with decreased amount of image pixels following the compressive sensing paradigm. The images are completely reconstructed in the control center prior to the application of image processing for suspicious objects detection. The efficiency of this combined approach depends on the amount of acquired data and also on the complexity of the scenery observed. The proposed approach is tested on various high resolution aerial images, while the achieved results are analyzed using different quality metrics and validation tests. Additionally, a user study is performed on the original images to provide the baseline object detection performance.

Control of Microgrid with Enhancement of Wind Power Evacuation

Out of the available renewable energy sources in India, wind energy plays a dominant role accounting for nearly 68% of the total renewable power produced in the country. Out of which Tamil Nadu produces 7162 MW (38%) of the total capacity. A major problem faced by all wind farms in the state is that of evacuation of wind power due to limited power transmission capacity of existing transmission lines. Kudimangalam, one such wind farm in Coimbatore is taken up for study in this paper. By transforming this windfarm into a microgrid, wind power evacuation problems can be mitigated or minimized to a larger extent. The goal of this paper is to suggest the capacity of solar plant, gas power plant and battery storage to be used for the proposed microgrid. Energy Management Algorithm (EMA) is incorporated in MATLAB Simulink and is tested for different conditions. Finally implementation of EMA is done with the help of PIC microcontroller. From the study, it can be concluded that it is feasible to convert the considered wind farm into a microgrid with solar and gas power plants of appropriate capacity so that wind power is utilized to its maximum without power evacuation problems.

Risk constrained short-term scheduling with dynamic line ratings for increased penetration of wind power

Limited transmission capacity may lead to network congestion which results in wind curtailment during periods of high availability of wind. Conventional congestion management techniques usually involve generation management which may not always benefit large wind farms. This paper investigates the problem in detail and presents an improved methodology to quantify the latent scheduling capacity of a power system taking into account stochastic variation in line-thermal rating, intermittency of wind, and mitigating the risk of network congestion associated with high penetration of wind. The mathematical model converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation risk. The uniqueness of the approach is that it can limit the generation to be curtailed or re-dispatch by dynamically enhancing the network latent capacity as per the need. The approach is aimed at strategic planning of power systems in the context of power systems with short to medium length lines with a priori known unit commitment decisions and uses stochastic optimization with a two stage recourse action. Results suggest that a considerable level of wind penetration is possible with dynamic line ratings, without adversely affecting the risk of network congestion.

A Compressed-Domain Image Filtering and Re-Ranking Approach for Multi-Agent Image Retrieval

For the limited transmission capacity and compressed images in the network environment, a compressed-domain image filtering and re-ranking approach for multi-agent image retrieval is proposed in this paper. Firstly, the distributed image retrieval platform with multi-agent is constructed by using Aglet development system, the lifecycle and the migration mechanism of agent is designed and planned for multi-agent image retrieval by using the characteristics of mobile agent. Then, considering the redundant image brought by distributed multi-agent retrieval, the duplicate images in distributed retrieval results are filtered based on the perceptual hashing feature extracted in the compressed-domain. Finally, weight-based hamming distance is utilized to re-rank the retrieval results. The experimental results show that the proposed approach can effectively filter the duplicate images in distributed image retrieval results as well as improve the accuracy and speed of compressed-domain image retrieval.

An Event-Based Simulation Framework to Examine the Response of Power Grid to the Charging Demand of Plug-In Hybrid Electric Vehicles

This paper describes the development of a discrete-event simulation framework that emulates the interactions between the power grid and plug-in hybrid electric vehicles (PHEVs) and examines whether the capacity of the existing power system can meet the PHEV load demand. The probability distribution functions for the arrival time and energy demand of each vehicle are extracted from real-world statistical transportation data. The power grid's limited generation and transmission capacities are considered to be the major constraints. Therefore, vehicles may have to wait to receive any charge. The proposed simulation framework is justified and described in some detail in applying it to two real cases in the United States to determine certain regions' grid potential to support PHEVs. Both Level-1 and -2 charging are considered.

Disruption-Tolerant Wireless Sensor Networking for Biomedical Monitoring in Outdoor Conditions

Off-the-shelf wireless sensing devices open up interesting perspectives for biomedical monitoring. Yet because of their limited processing and transmission capacities most applications considered to date imply either indoor real-time data streaming, or ambulatory data recording. In this paper we investigate the possibility of using disruption-tolerant wireless sensors to monitor the biomedical parameters of athletes during outdoor sports events. We focus on a scenario we believe to be a most challenging one: the ECG monitoring of runners during a marathon race, using off-the shelf sensing devices and a limited number of base stations deployed along the marathon route. Field experiments conducted during intra-campus sports events show that such a scenario is indeed viable, although special attention must be paid to supporting episodic, low-rate transmissions between sensors carried by runners and roadside base stations.

Design of stabilizing strategies for dual switching stochastic-deterministic linear systems

Dual switching linear systems are systems with piecewise linear dynamics governed by two distinct external switching signals. In this paper one switching signal is stochastic and modeled as a time-homogeneous Markov chain, and the second one is assumed to be a control signal taking values in a finite set. This situation arises, for instance, in multi-loop networked control systems (NCS) with limited transmission capacity and lossy communication channels, where the control variable is the scheduling signal and the stochastic switching accounts for packet dropout. The aim of this paper is to derive suitable switching strategies for dual switching linear systems, ensuring mean-square stability and attaining guaranteed bounds on ℋ2 and ℋ∞ performance indices. The relevant sufficient conditions are expressed in terms of feasibility of sets of coupled matrix inequalities. The application to a scheduling design problem in NCS's is also discussed.

Strategies and Techniques for Data Compression in Wireless Sensor Networks

The major challenge in designing wireless sensor networks (WSNs) is to resolve the limitation of energy and transmission capacity. Data compression, as an effective solution, is attracted many attentions. In this paper, a survey is done on the strategies and techniques for data compression in WSNs. And the data compression schemes are divided into two classes: classical methods and the potential technique based on compressed sensing. The basic procedures of each method are further analyzed, and the existing problems are also highlighted. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3507 Full Text: PDF

Two-stage network constrained robust unit commitment problem

For a current deregulated power system, a large amount of operating reserve is often required to maintain the reliability of the power system using traditional approaches. In this paper, we propose a two-stage robust optimization model to address the network constrained unit commitment problem under uncertainty. In our approach, uncertain problem parameters are assumed to be within a given uncertainty set. We study cases with and without transmission capacity and ramp-rate limits (The latter case was described in Zhang and Guan (2009), for which the analysis part is included in Section 3 in this paper). We also analyze solution schemes to solve each problem that include an exact solution approach and an efficient heuristic approach that provides tight lower and upper bounds for the general network constrained robust unit commitment problem. The final computational experiments on an IEEE 118-bus system verify the effectiveness of our approaches, as compared to the nominal model without considering the uncertainty.

Multi-area economic generation and reserve dispatch considering large-scale integration of wind power

Wind power penetration in Taiwan power system faces significant barriers due to limited transmission capability. One of the most important future challenges seems to be the management of the integration of fluctuations in the electricity production from wind energy sources. The problem is further complicated by the generation dispatch imposed by the presence of transmission capacity limits. Several new important concepts about economic dispatch (ED) model are investigated in this paper for the large-scale wind capacity integration. A penalty function-hybrid direct search method (PF-HDSM) is also developed for the solution of multi-area wind-thermal coordination dispatch (MWCD) problem. Several important issues of wind capacity integration in the Taiwan power system are discussed by using the developed MWCD software. Numerical experiments are included to illustrate the impacts of transmission capacity limits on wind power penetration level in each area and to assess the impact and economic benefits of the installation of wind farms for the Taiwan power system.