Artificial neural network application to power system voltage stability improvement

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Reactive power optimization with different objectives in large power systems including HVDC systems and FACTS devices

Present day power systems are growing in size and complexity of operation with inter connections to neighboring systems, introduction of large generating units, EHV 400/765 kV AC transmission systems, HVDC systems and more sophisticated control devices such as FACTS. For planning and operational studies, it requires suitable modeling of all components in the power system, as the number of HVDC systems and FACTS devices of different type are incorporated in the system. This paper presents reactive power optimization with three objectives to minimize the sum of the squares of the voltage deviations (ve) of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (¿L2), and also the system real power loss (Ploss) minimization. The proposed methods have been tested on typical sample system. Results for Indian 96-bus equivalent system including HVDC terminal and UPFC under normal and contingency conditions are presented.

Switching and fault transient analysis of 765 kV transmission systems

The analysis of electromagnetic transients arising in EHV/UHV power networks gives necessary information about the possible stresses on the different network components, which will determine their proper design, limits of operation as well as their pertinent protection strategies. This paper describes the transient analysis of 765 kV EHV transmission system which is a typical expansion in Indian power grid system. Considering various conditions, switching transient and fault transient studies are carried out. A FORTRAN version of EMTP is developed, to study a practical example, then a comparison with the results available in the literature is made.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Changing resonator geometry to boost sound power decouples size and song frequency in a small insect

Despite their small size, some insects, such as crickets, can produce high amplitude mating songs by rubbing their wings together. By exploiting structural resonance for sound radiation, crickets broadcast species-specific songs at a sharply tuned frequency. Such songs enhance the range of signal transmission, contain information about the signaler's quality, and allow mate choice. The production of pure tones requires elaborate structural mechanisms that control and sustain resonance at the species-specific frequency. Tree crickets differ sharply from this scheme. Although they use a resonant system to produce sound, tree crickets can produce high amplitude songs at different frequencies, varying by as much as an octave. Based on an investigation of the driving mechanism and the resonant system, using laser Doppler vibrometry and finite element modeling, we show that it is the distinctive geometry of the crickets' forewings (the resonant system) that is responsible for their capacity to vary frequency. The long, enlarged wings enable the production of high amplitude songs; however, as a mechanical consequence of the high aspect ratio, the resonant structures have multiple resonant modes that are similar in frequency. The drive produced by the singing apparatus cannot, therefore, be locked to a single frequency, and different resonant modes can easily be engaged, allowing individual males to vary the carrier frequency of their songs. Such flexibility in sound production, decoupling body size and song frequency, has important implications for conventional views of mate choice, and offers inspiration for the design of miniature, multifrequency, resonant acoustic radiators.

Optimal Hop Distance and Power Control for a Single Cell, Dense, Ad Hoc Wireless Network

We consider a dense, ad hoc wireless network, confined to a small region. The wireless network is operated as a single cell, i.e., only one successful transmission is supported at a time. Data packets are sent between source-destination pairs by multihop relaying. We assume that nodes self-organize into a multihop network such that all hops are of length d meters, where d is a design parameter. There is a contention-based multiaccess scheme, and it is assumed that every node always has data to send, either originated from it or a transit packet (saturation assumption). In this scenario, we seek to maximize a measure of the transport capacity of the network (measured in bit-meters per second) over power controls (in a fading environment) and over the hop distance d, subject to an average power constraint. We first motivate that for a dense collection of nodes confined to a small region, single cell operation is efficient for single user decoding transceivers. Then, operating the dense ad hoc wireless network (described above) as a single cell, we study the hop length and power control that maximizes the transport capacity for a given network power constraint. More specifically, for a fading channel and for a fixed transmission time strategy (akin to the IEEE 802.11 TXOP), we find that there exists an intrinsic aggregate bit rate (Theta(opt) bits per second, depending on the contention mechanism and the channel fading characteristics) carried by the network, when operating at the optimal hop length and power control. The optimal transport capacity is of the form d(opt)((P) over bar (t)) x Theta(opt) with d(opt) scaling as (P) over bar (t) (1/eta), where (P) over bar (t) is the available time average transmit power and eta is the path loss exponent. Under certain conditions on the fading distribution, we then provide a simple characterization of the optimal operating point. Simulation results are provided comparing the performance of the optimal strategy derived here with some simple strategies for operating the network.

Power Controlled Reverse Channel Training Achieves an Infinite Diversity Order in a TDD-SIMO System with Perfect CSIR

In this letter, we analyze the Diversity Multiplexinggain Tradeoff (DMT) performance of a training-based reciprocal Single Input Multiple Output (SIMO) system. Assuming Channel State Information (CSI) is available at the Receiver (CSIR), we propose a channel-dependent power-controlled Reverse Channel Training (RCT) scheme that enables the transmitter to directly estimate the power control parameter to be used for the forwardlink data transmission. We show that, with an RCT power of (P) over bar (gamma), gamma > 0 and a forward data transmission power of (P) over bar, our proposed scheme achieves an infinite diversity order for 0 <= g(m) < L-c-L-B,L-tau/L-c min(gamma, 1) and r > 2, where g(m) is the multiplexing gain, L-c is the channel coherence time, L-B,L-tau is the RCT duration and r is the number of receive antennas. We also derive an upper bound on the outage probability and show that it goes to zero asymptotically as exp(-(P) over bar (E)), where E (sic) (gamma - g(m)L(c)/L-c-L-B,L-tau), at high (P) over bar. Thus, the proposed scheme achieves a significantly better DMT performance compared to the finite diversity order achieved by channel-agnostic, fixed-power RCT schemes.

Diversity-Rate Trade-off for Fading Channels with Power Control

We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

Packet scheduling for priority based transmission in energy harvesting sensors

In this paper, we determine packet scheduling policies for efficient power management in Energy Harvesting Sensors (EHS) which have to transmit packets of high and low priorities over a fading channel. We assume that incoming packets are stored in a buffer and the quality of service for a particular type of message is determined by the expected waiting time of packets of that type of message. The sensors are constrained to work with the energy that they garner from the environment. We derive transmit policies which minimize the sum of expected waiting times of the two types of messages, weighted by penalties. First, we show that for schemes with a constant rate of transmission, under a decoupling approximation, a form of truncated channel inversion is optimal. Using this result, we derive optimal solutions that minimize the weighted sum of the waiting times in the different queues.

Analysis of distance relay trip regions for EHV and UHV transmission lines

This paper presents comparative evaluation of the distance relay characteristics for UHV and EHV transmission lines. Distance protection relay characteristics for the EHV and UHV systems are developed using Electromagnetic Transients (EMT) program. The variation of ideal trip boundaries for both the systems are presented. Unlike the conventional distance protection relay which uses a lumped parameter model, this paper uses the distributed parameter model. The effect of larger shunt susceptance on the trip boundaries is highlighted. Performance of distance relay with ideal trip boundaries for EHV and UHV lines have been tested for various fault locations and fault resistances. Electromagnetic Transients (EMT) program has been developed considering distributed parameter line model for simulating the test systems. The voltage and current phasors are computed from the signals using an improved full cycle DFT algorithm taking 20 samples per cycle. Two practical transmission systems of Indian power grid, namely 765 kV UHV transmission line and SREB 24-bus 400kV EHV system are used to test the performance of the proposed approach.

Support vector machine based high speed protection relay for EHV/UHV transmission line

This paper presents a fast and accurate relaying technique for a long 765kv UHV transmission line based on support vector machine. For a long EHV/UHV transmission line with large distributed capacitance, a traditional distance relay which uses a lumped parameter model of the transmission line can cause malfunction of the relay. With a frequency of 1kHz, 1/4th cycle of instantaneous values of currents and voltages of all phases at the relying end are fed to Support Vector Machine(SVM). The SVM detects fault type accurately using 3 milliseconds of post-fault data and reduces the fault clearing time which improves the system stability and power transfer capability. The performance of relaying scheme has been checked with a typical 765kV Indian transmission System which is simulated using the Electromagnetic Transients Program(EMTP) developed by authors in which the distributed parameter line model is used. More than 15,000 different short circuit fault cases are simulated by varying fault location, fault impedance, fault incidence angle and fault type to train the SVM for high speed accurate relaying. Simulation studies have shown that the proposed relay provides fast and accurate protection irrespective of fault location, fault impedance, incidence time of fault and fault type. And also the proposed scheme can be used as augmentation for the existing relaying, particularly for Zone-2, Zone-3 protection.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Power-optimal scheduling for a green base station with delay constraints

We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

Joint Routing, Scheduling and Power Control in Multihop MIMO Networks with MAC and Broadcast Links

We consider the problem of joint routing, scheduling and power control in a multihop wireless network when the nodes have multiple antennas. We focus on exploiting the multiple degrees-of-freedom available at each transmitter and receiver due to multiple antennas. Specifically we use multiple antennas at each node to form multiple access and broadcast links in the network rather than just point to point links. We show that such a generic transmission model improves the system performance significantly. Since the complexity of the resulting optimization problem is very high, we also develop efficient suboptimal solutions for joint routing, scheduling and power control in this setup.