Design and Testing of a Control System for Supply Side Electrical Load Management

India's energy demand is increasing rapidly with the intensive growth of economy. The electricity demand in India exceeded the availability, both in terms of base load energy and peak availability. The efficient use of energy source and its conversion and utilizations are the viable alternatives available to the utilities or industry. There are essentially two approaches to electrical energy management. First at the supply / utility end (Supply Side Management or SSM) and the other at the consumer end (Demand Side Management or DSM). This work is based on Supply Side Management (SSM) protocol and consists of design, fabrication and testing of a control device that will be able to automatically regulate the power flow to an individual consumer's premise. This control device can monitor the overuse of electricity (above the connected load or contracted demand) by the individual consumers. The present project work specially emphasizes on contract demand of every consumer and tries to reduce the use beyond the contract demand. This control unit design includes both software and hardware work and designed for 0.5 kW contract demand. The device is tested in laboratory and reveals its potential use in the field.

Suboptimal reentry guidance of a reusable launch vehicle using pitch plane maneuver

Using the recently developed model predictive static programming (MPSP) technique, a nonlinear suboptimal reentry guidance scheme is presented in this paper for a reusable launch vehicle (RLV). Unlike traditional RLV guidance, the problem considered over here is restricted only to pitch plane maneuver of the vehicle, which allows simpler mission planning and vehicle load management. The computationally efficient MPSP technique brings in the philosophy of trajectory optimization into the framework of guidance design, which in turn results in very effective guidance schemes in general. In the problem addressed in this paper, it successfully guides the RLV through the critical reentry phase both by constraining it to the allowable narrow flight corridor as well as by meeting the terminal constraints at the end of the reentry segment. The guidance design is validated by considering possible aerodynamic uncertainties as well as dispersions in the initial conditions. (C) 2010 Elsevier Masson SAS. All rights reserved.

Thermal Management of Electronics Using PCM-Based Heat Sink Subjected to Cyclic Heat Load

Designing a heat sink based on a phase change material (PCM) under cyclic loading is a critical issue. For cyclic operation, it is required that the fraction of the PCM melting during the heating cycle should completely resolidify during the cooling period, so that that thermal storage unit can be operated for an unlimited number of cycles. Accordingly, studies are carried out to find the parameters influencing the behavior of a PCM under cyclic loading. A number of parameters are identified in the process, the most important ones being the duty cycle and heat transfer coefficient (h) for cooling. The required h or the required cooling period for complete resolidification for infinite cyclic operation of a conventional PCM-based heat sink is found to be very high and unrealistic with air cooling from the surface. To overcome this problem, the conventional design is modified where h and the area exposed to heat transfer can be independently controlled. With this arrangement, the enhanced area provided for cooling keeps h within realistic limits. Analytical investigation is carried out to evaluate the thermal performance of this modified PCM-based heat sink in comparison to those with conventional designs. Experiments are also performed on both the conventional and the modified PCM-based heat sinks to validate the new findings.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Vehicle Routing Problem with Load Compatibility Constraints

The major contribution of this paper is to introduce load compatibility constraints in the mathematical model for the capacitated vehicle routing problem with pickup and deliveries. The employee transportation problem in the Indian call centers and transportation of hazardous materials provided the motivation for this variation. In this paper we develop a integer programming model for the vehicle routing problem with load compatibility constraints. Specifically two types of load compatability constraints are introduced, namely mutual exclusion and conditional exclusion. The model is demonstrated with an application from the employee transportation problem in the Indian call centers.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

A dynamic topology management in a hybrid wireless superstore network

with the development of large scale wireless networks, there has been short comings and limitations in traditional network topology management systems. In this paper, an adaptive algorithm is proposed to maintain topology of hybrid wireless superstore network by considering the transactions and individual network load. The adaptations include to choose the best network connection for the response, and to perform network Connection switching when network situation changes. At the same time, in terms of the design for topology management systems, aiming at intelligence, real-time, the study makes a step-by-step argument and research on the overall topology management scheme. Architecture for the adaptive topology management of hybrid wireless networking resources is available to user’s mobile device. Simulation results describes that the new scheme has outperformed the original topology management and it is simpler than the original rate borrowing scheme.

Fiber Bragg Grating Sensor Instrumentation for Parking Space Occupancy Management

This work aims at providing an effective parking management system by reducing the drivers' searching time for vacant car-parking space, in turn improving the traffic flow in the car park areas. This is achieved by the use of Fiber Bragg Grating Sensor (FBG) sensor instrumentation in vehicle parking management system. Present work involves embedding an array of FBG sensors underground in the parking space, then determining the strain changes on the FBG sensor due to load applied by the vehicle parked in the parking space, occupancy of the parking space is determined. To validate the FBG sensor parking management system, three most common cases have been considered. This closed loop FBG parking management system can give real-time feed-back to space-guidance display board helping the driver in maneuvering the vehicle to the appropriate parking space. The proposed technique offers optimized usage of parking space for the various segments of cars and also facilitates in a conjoined automated billing system, as compared to conventional method of parking systems.