R. Balasubramanian

Dynamics and stability of wind and diesel turbine generators with superconducting magnetic energy storage unit on an isolated power system

Dynamic system analysis is carried out on an isolated electric power system consisting of a diesel generator and a wind-turbine generator. The 150 kW wind turbine is operated in parallel with a diesel generator to serve an average load of 350 kW. A comprehensive digital computer model of the interconnected power system including the diesel and wind-power dynamics with a superconducting magnetic energy storage (SMES) unit is developed. Time-domain solutions are used to study the performance of the power system and control logic. Based on a linear model of the system, it is shown that changes in control-system settings could be made to improve damping and optimization of gain parameters and stability studies are done using the Lyapunov technique and eigenvalue analysis. The effect of introducing the SMES unit for improvement of stability and system dynamic response is studied. >

Adaptive automatic generation control with superconducting magnetic energy storage in power systems

An improved automatic generation control (AGC) system employing self-tuning adaptive control for the main AGC loop and the superconducting magnetic energy storage system (SMES) is presented. Computer simulations on a two-area interconnected power system showed that the proposed adaptive control scheme was very effective in damping, oscillations caused by load disturbances and its performance was quite insensitive to controller gain parameter changes of the SMES system. A performance evaluation of control schemes using adaptive and nonadaptive controllers in the main AGC and in the SMES control loops is presented. The improvement in performance resulting from the adaptive scheme was particularly pronounced for load changes of random magnitude and duration. >

Demand for commercial energy in the state of Kerala, India: an econometric analysis with medium-range projections

Abstract Rapid growth in the demand for commercial energy in Kerala, a state in India, posed serious development constraints in the recent past. The crucial issue of managing this demand will be of great importance in formulating the future development policy of the state. This study analyses the requirement of three major forms of commercial energy in the state of Kerala (viz. electricity, petroleum products and coal). Sectorwise/productwise econometric demand models are generated using regression method. The primary regression models consisting of statistically significant key energy indicators have been fitted with ordinary least-squares (OLS) estimation. Models wherever required have been subsequently refined in the second stage computations by employing Cochrane-Orcutt transformation algorithm to remove the effects of auto-correlation. The accuracy of the models have been checked using standard statistical techniques and validated against the past data by testing for ‘expost’ forecast accuracy. Employing the models, medium-range projections of demand of the state for commercial energy till the year 2020 have been made. The policy implications and related key issues have been addressed. The study identifies the urgent need for special attention in evolving effective energy policies to alleviate an ‘energy famine’ in the near future.

Analytical search of problems and prospects of power sector through Delphi study: case study of Kerala State, India

This study attempts to review and analyse the critical issues that afflict the power sector of Kerala, a developing State in India. For this purpose a Delphi study, contacting experts in the field was conducted. The paper illustrates the process followed for the conduct of Delphi survey and evaluates the responses obtained. Consensus among experts could be arrived at on various issues related to Kerala power sector in two rounds of Delphi survey. The expert-opinion concluded on various issues is discussed in the context of the present energy shortage faced by the State. The experts participated in the Delphi survey unanimously stressed on the urgent need for an integrated approach in the power sector planning process of the State. They also emphasised on the imperativeness for exploiting the demand side management potential of the State to alleviate energy crisis in future. The study fetched informative and revealing results, which may aid to formulate and review future planning strategies for the expansion of power sector of the State.

Production costing and economic analysis of power systems containing wind energy conversion systems

Abstract Electrical energy can be generated by various sources, namely conventional sources, such as nuclear, coal, diesel, etc. and non-conventional sources, such as wind, tidal, solar energy, etc. Presently, there is a great deal of growing interest in the non-conventional sources of energy, as they are limitless and cheap to operate. Of the various non-conventional sources, wind has one of the best potentials. In this paper, the effect of combining wind energy conversion systems (WECS) with the conventional power system is studied. Production costing of the combined system is performed by Fast transform techniques. An economic analysis is performed, based on the production costs, to study the benefits obtained over the lifetime of the WECS, which determines the effectiveness of the installation of a WECS at a particular wind site.

Reliability and economic analysis of a power generation system including a photovoltaic system

A method for the reliability evaluation of an electric power generation system with a photovoltaic system is presented in this paper. An economic analysis of the system in terms of conventional fuel savings due to use of the photovoltaic system is also done. The fluctuating nature of the energy produced by the photovoltaic generation system has a different effect on the overall system reliability than the energy produced by conventional units. Here, conventional and photovoltaic units are combined into separate groups. First, the generation system reliability model for each group is created. Then, the model of the photovoltaic units is modified hourly to account for the limitations of this system. Then, both models are combined hourly to find the loss of load expectation for the hour in question. This is done by a discrete state algorithm. A method for assessing the fuel savings with use of a photovoltaic system is also described.

Energy auditing kit for cement industries

Abstract Energy is now a costly and scarce commodity in any manufacturing industry, and hence, it is essential for each industry to develop an energy auditing kit to find the energy conservation opportunities and methods to reduce energy consumption. Such energy auditing would be unique, depending on the type and need of the specific industry. The auditing kit needs essential tools such as (i) subdivision of the production system of any commodity in several blocks or departments and (ii) a reliable metering or measurement system in each block. The reasons to have the subdivision or smaller pockets of a particular stage of production is to pinpoint the location of the higher energy consumption where greater attention is needed. The reasons to have a suitable metering system is to provide data for the energy audit, allow proper distribution of electrical energy costs to individual departments and to provide historical data on which performance evaluation can be done.

Stochastic load flow analysis using artificial neural networks

Stochastic load flow is a method for calculation of the effects of inaccuracies in input data on all output quantities through the load flow calculations. This gives a range of values (confidence limit) for each output quantity, which represent the operative condition of the system, to a high degree of probability or confidence. This paper presents a new method for stochastic load flow analysis using artificial neural networks. It is desirable to know the state of the power system in a range with certain confidence, with consideration of input data uncertainties and inaccuracies, on instant-to-instant basis in the fastest possible way. Present method using artificial neural networks to stochastic load flow problem is an effort in that direction and will be a very useful technique in effectively dealing with demand side uncertainties for power system planning and operation. The proposed artificial neural network model has been tested on a sample power system using two different training algorithms and simulation results are presented

Dynamics and stability of a hybrid wind-diesel power system

Abstract Dynamic system analysis is carried out on an isolated electric power system consisting of a wind turbine generator (WTG) and a diesel engine generator (DG). The 150 kW wind turbine generator is operated in parallel with the diesel generator to serve an average load of 350 kW. A comprehensive digital computer model of a hybrid wind-diesel power generation system, including the diesel and wind power dynamics for stability evaluation, is developed. The dynamic performance of the power system and its control logic are studied, using the time domain solution approach. A systematic method of choosing the gain parameter of the wind turbine generator pitch control by the second method of Lyapunov that guarantees stability is presented. The response of the power system with the optimal gain setting to the random load changes has been studied. Analysis of stability has further been explored using the eigenvalue sensitivity technique.

Modelling the Control of an Isolated Power System Based on Diesel and Pitch Controlled Wind Generation

This paper deals with the control of a stand alone power system comprised of a pitch controlled wind turbine and two diesel units. First, a single-input single-output (SISO) selftuning regulator (STR) is designed for blade-pitch control, with a conventional diesel governor control. Then, a two-input two-output (TITO) STR is used for coordinated pitch and diesel governor controls. Finally a case study is made with a superconducting magnetic energy storage unit (SMES), introduced as a damping device. In this case, a three-input three-output STR controls the wind-diesel-SMES system in a co-ordinated manner. The design of the various control schemes ensures that the system performs well under both wind and load disturbances.