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Development of alternative energy sources has become a necessity as fossil energy resources are declining. At the same time, energy demand is rapidly increasing, putting the world on the verge of a global energy crisis. Moreover, the extensive use of conventional energy sources is polluting the environment and causing global warming. On the other hand, wind and other renewable energy sources are viable and clean alternatives to fossil fuels. Low operating cost and extensive availability make wind one of the most advantageous and effective renewable energy sources. This paper provides an exposure to the necessity for deployment of renewable energy sources and the worldwide installed capacity of wind power as well as a review of various wind technologies in conjunction with their applications and devices of operation. Furthermore, this paper discusses the cost of electric generation in wind power plants as well as the economic and environmental policies that advocate the installation of wind energy systems.

Transmission and distribution of electricity involve technical as well as Non-Technical Losses (NTLs). Illegal consumption of electricity constitutes a major portion of the NTL at distribution feeder level. Considering the severity and devastating effects of the problem, illegal consumption of electricity has to be detected instantly in real-time. To this end, this paper investigates the possibility and role of High Performance Computing (HPC) algorithms in detection of illegal consumers. This paper designs and implements an encoding procedure to simplify and modify customer energy consumption data for quicker analysis without compromising the quality or uniqueness of the data. This paper parallelizes overall customer classification process. The parallelized algorithms have resulted in appreciable results as displayed in the results section of the paper.

The global demand for energy is currently growing beyond the limits of installable generation capacity. To meet future energy demands efficiently, energy security and reliability must be improved and alternative energy sources must be investigated aggressively. An effective energy solution should be able to address long-term issues by utilizing alternative and renewable energy sources. Of the many available renewable sources of energy, solar energy is clearly a promising option as it is extensively available. Solar power, especially as it reaches more competitive levels with other energy sources in terms of cost, may serve to sustain the lives of millions of underprivileged people in developing countries. Furthermore, solar energy devices can benefit the environment and economy of developing countries. This paper illustrates the need for the utilization of alternative energy sources, evaluates the global scenario of installed generation systems, reviews technologies underlying various solar powered devices, and discusses several applications and challenges in this area. In addition, this paper addresses the costs of deployment, maintenance, and operation, as well as economic policies that promote installation of solar energy systems.

Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. Integration of smart meters into electricity grid involves implementation of a variety of techniques and software, depending on the features that the situation demands. Design of a smart meter depends on the requirements of the utility company as well as the customer. This paper discusses various features and technologies that can be integrated with a smart meter. In fact, deployment of smart meters needs proper selection and implementation of a communication network satisfying the security standards of smart grid communication. This paper outlines various issues and challenges involved in design, deployment, utilization, and maintenance of the smart meter infrastructure. In addition, several applications and advantages of smart meter, in the view of future electricity market are discussed in detail. This paper explains the importance of introducing smart meters in developing countries. In addition, the status of smart metering in various countries is also illustrated.

Non-technical loss (NTL) during transmission of electrical energy is a major problem in developing countries and it has been very difficult for the utility companies to detect and fight the people responsible for theft. Electricity theft forms a major chunk of NTL. These losses affect quality of supply, increase load on the generating station, and affect tariff imposed on genuine customers. This paper discusses the factors that influence the consumers to steal electricity. In view of these ill effects, various methods for detection and estimation of the theft are discussed. This paper proposes an architectural design of smart meter, external control station, harmonic generator, and filter circuit. Motivation of this work is to deject illegal consumers, and conserve and effectively utilize energy. As well, smart meters are designed to provide data of various parameters related to instantaneous power consumption. NTL in the distribution feeder is computed by external control station from the sending end information of the distribution feeder. If a considerable amount of NTL is detected, harmonic generator is operated at that feeder for introducing additional harmonic component for destroying appliances of the illegal consumers. For illustration, cost–benefit analysis for implementation of the proposed system in India is presented.

Cytoplasmic male sterility (CMS) is considered an efficient genetic tool in pearl millet hybrid breeding. Of the several CMS sources available in pearl millet, A1 is the only CMS widely exploited to produce commercial hybrids in India. To explore the possibility of using alternate CMS sources, we studied the cytoplasmic effects of different CMS sources on agronomic characters in pearl millet. Five CMS (A) lines representing A1, A2, A3, A4 and A5 cytoplasms, their respective maintainer (B) lines and eight restorer (R) lines were used to generate 40 A × R and B × R experimental crosses. The experimental material was evaluated at two different locations in India. Analysis of combining ability and heterosis revealed that A4 and A5 cytoplasms had desirable effects for earliness. The A5 CMS was found to be particularly promising, as compared to other CMS sources for improving grain yield. The study also indicated that the cytoplasmic effects on general combining ability (GCA) for various agronomic characters were largely non-significant. However, cytoplasmic effects on specific combining ability and heterosis were found to be modulated by cytoplasmic-nuclear interactions and influenced by the environmental conditions. The study also demonstrated the advantage of utilizing diverse male-sterile and restorer combinations in maximizing the productivity as well as for genetic and cytoplasmic diversification of hybrids in pearl millet.

Diversification of cytoplamic male sterile (CMS) sources is of considerable significance in pearl millet, considering that almost all the commercially cultivated hybrids, particularly in India, are based on a single CMS source, A1. We analyzed the mitochondrial DNA (mtDNA) polymorphisms among five pearl millet CMS sources (A1 to A5) and a male-fertile maintainer (B) line, all in an isonuclear background. Analysis using 21 random primers led to identification of polymorphic bands specific to the A1, A2, A3 and A5 CMS lines. Two RAPD primers, OP-G12 and OP-G19, in combination were able to distinguish all the male-sterile and male-fertile cytoplasms. Highly effective for this purpose also were four RAPD markers, OP-B7, OP-D8, OP-F10 and OP-G12. Cluster analysis, followed by bootstrap analysis, of the mtDNA dataset revealed two distinct clusters: cluster-I comprising the A1, A2, A3 CMS lines and the male-fertile line, and cluster-II comprising the A4 and A5 CMS lines.

Total losses in transmission and distribution (T&D) of electricity includes nontechnical losses (NTL). Illegal consumption of electricity constitutes a major portion of NTL. NTL affects good interests of utility companies and its customers. In this context, importance of customer load profile evaluation for detection of illegal consumers has been explained. In this paper, an encoding technique has been implemented to reduce the number of data points to be evaluated by the rule engine. In addition, rule engine algorithm has been proposed and implemented to classify customers based on their energy consumption. This paper presents synopsis of those rules, and elucidates the overall encoding and classification procedure. From the obtained results, it is evident that the rule engine yielded appreciable classification accuracy in significantly less CPU time. Results demonstrate the robustness and accuracy of this procedure in identifying illegal consumers.

Transmission and Distribution (T&D) of electricity from a power generation station involve substantial losses. T&D losses include technical as well as nontechnical losses (NTL). Most portion of the NTL constitutes of electricity theft. This paper explains the significance of the evaluation of customer energy consumption profiles for identification of illegal consumers. To reduce the complexity of the instantaneous energy consumption data for evaluation, this paper proposes and implements a data encoding technique. This encoding technique maps instantaneous energy consumption data into irregularities in consumption. In addition, exclusivity in each customer's energy consumption has been preserved. After the encoding process, the data has been inputted to a support vector machine (SVM) classification model that classifies customers into three categories: genuine customers, illegal consumers or suspicious customers. Classification accuracy of the SVM model with the encoded data is 92%. The obtained results demonstrate that this encoding procedure is significantly quick and robust in identifying (classifying) illegal consumers.

The probabilistic reliability evaluation of composite power systems is a complicated and computation intensive task. Monte Carlo Simulation (MCS) is often used as the method of choice for tackling this difficult problem, though MCS may also suffer from issues regarding high dimensionality leading to an increased need for computational resources. In order to address this issue an algorithmic method known as state space pruning has been developed in two flavors: Analytical and Metaheuristic based. The state space pruning methodology reduces the size of a given state space by removing states where there is no loss-of-load. This allows the MCS algorithm to sample a state space with a higher density of failure states which, in turn, leads to faster convergence. This study applies the CLONALG algorithm to the metaheuristic based version of state space pruning, compares and contrasts the results with genetic algorithm (GA) and particle swarm optimization (PSO) implementations, and discusses its strengths and weaknesses as applied to test systems both with and without the consideration of transmission line outages. Simulations are completed using the IEEE reliability test system (RTS) and the modified RTS (MRTS).

Climate change is a matter of pressing importance for modern society. One method that has been suggested for mitigating the role that fossil fuel based transportation plays in this issue is the introduction of Plug-in Hybrid Electric Vehicles (PHEVs) in order to electrify the transportation sector. While these vehicles would have a significant impact in reducing greenhouse gases (GHGs), they may also place a larger strain on the current power grid and the coming Smart Grid. In order to address this issue much work has been completed in order to examine the impact of PHEVs on distribution systems in modern power grids while little effort has been made to examine the effect that the inclusion of this new load will have on generation and transmission systems. As such, this work extends the probabilistic reliability evaluation of power systems by developing a model for reliability evaluation using Monte Carlo Simulation (MCS) to examine the impact that PHEVs will have on composite power systems. The model is examined using the IEEE-RTS across multiple load and penetration levels.

Total losses in transmission and distribution (T&D) of electrical energy including nontechnical losses (NTL) are huge and are affecting the good interest of utility company and its customers. In this context, importance of customer load profile evaluation for detection of illegal consumers is explained in this paper. Classification of the customers based on load profile evaluation using SVMLIB requires us to choose training function and related parameters. Selecting these parameters would consume a lot of time and is not suggestible evaluation of real time electricity consumption patterns, as, the suspicious profiles are to be predicted instantly. In light of this issue, this paper implements a neural network (NN) model and suggests a hierarchical model for enhanced estimation of the classification efficiency, if that data was classified using support vector machines (SVM). In addition, this paper proposes an encoding technique that can identify illegal consumers with better efficiency and faster classification of data.

This paper introduces dynamic distributed resource management in a Demand-Side Management (DSM) based simulation tool. The principle purpose of the simulation tool is to illustrate customer-driven DSM operation, and evaluate an estimate for home electricity consumption while minimizing the customer's cost. The tool simulates the operation of household appliances as a Hybrid Renewable Energy System (HRES). The resource management technique is implemented using an optimization algorithm, i.e. Particle Swarm Optimization, which determines the distribution of energy obtained from various sources depending on the load. The validity of the tool is illustrated through an example case study, and compared with the operating costs of the same system without the optimization algorithm.

Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. Integration of smart meters into electricity grid involves implementation of a variety of techniques and software, depending on the features that the situation demands. Design of a smart meter depends on the requirements of the utility company as well as the customer. This paper discusses various features and technologies that can be integrated with a smart meter. In fact, deployment of smart meters needs proper selection and implementation of a communication network satisfying the security standards of smart grid communication. This paper outlines various issues and challenges involved in design, deployment, utilization, and maintenance of the smart meter infrastructure. In addition, several applications and advantages of smart meter, in the view of future electricity market are discussed in detail. This paper explains the importance of introducing smart meters in developing countries. In addition, the status of smart metering in various countries is also illustrated.

This paper introduces optimized operation of household appliances in a Demand-Side Management (DSM) based simulation tool. DSM can be defined as the implementation of policies and measures to control, regulate, and reduce energy consumption. The principal purpose of the simulation tool is to illustrate customer-driven DSM operation, and evaluate an estimate for home electricity consumption while minimizing the customer's cost. An optimization algorithm i.e. Binary Particle Swarm Optimization (BPSO) is used for optimizing the DSM operation of the tool. The tool also simulates the operation of household appliances as a Hybrid Renewable Energy System (HRES). The resource management technique is implemented using an optimization algorithm, i.e. Particle Swarm Optimization (PSO), which determines the distribution of energy obtained from various sources depending on the load. The validity of the tool is illustrated through an example case study for various household situations.

Electricity theft is a major problem in developing countries and it has been very difficult for the utility companies to detect and fight against the people responsible for theft. This paper proposes an architectural design of smart meter, external control station, harmonic generator, and filter circuit, which can detect and chastise the appliances of people responsible for electricity theft. The motivation of this work is to deject the illegal consumers, and conserve and effectively utilize energy. As well, smart meters are designed to provide data of various parameters related to instantaneous power consumption. Dynamic behavior of such meters can be managed and controlled by utility companies. Total loss in the distribution feeder is computed by the external control station from the values of total load consumption and technical losses in the distribution feeder. If considerable amount of non-technical losses are detected at any given feeder, harmonic generator is operated for introducing harmonics into the feeder for destroying the appliances of the illegal consumers. In addition, harmonic analysis of the distribution feeder and consumer appliances due to the presence of harmonics is carried out to estimate the effect of induced harmonics. For illustration, cost-benefit analysis for implementation/maintenance of the proposed system in India is presented.

It is heartening to note that despite making significant improvements in all the areas relating to financial viability, profitability and competitiveness, there are concerns that formal financial institutions have not been able to include vast segment of the population, especially the underprivileged sections of the society, into the fold of basic banking services. Efforts of financial inclusion have largely remained concentrated around banking inclusion but the focus is fast shifting towards inclusion of poor people in insurance also. At this juncture the introduction of micro insurance by micro financial institutions and various public and private insurance companies comes from the recognition that this can serve the interests of marginalised sections and become the effective approach of ‗financial inclusion‘ in India. However, still micro insurance in India faces many constraints and need urgent and suitable policy attention. Keeping the above facts in view this paper has the following objectives; To understand the need and status of micro insurance in India; To discuss the constraints faced by the Indian micro insurance sector; To suggest suitable policy alternatives to the problems of micro insurance. This paper is based on the secondary information and it was gathered from various publications of government departments, reputed journals, books and newspapers.

The carpels of pearl millet (Pennisetum typhoides) are infected bySclerospora graminicola. Vegetative mycelium present in the diseased mother plant infects the carpel through the stalk of the spikelet. This process may or may not cause hypertrophy. Zoospores infect the carpel through the stimga and style, without inducing hypertrophy. Infection process leading to the establishment of downy mildew mycelium in the carpellary tissue and its implications are discussed.