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.

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.

Experiences With WM: A Centralised Scheduling Approach for Performance Management of IEEE 802.11 Wireless LANs

In our earlier work ([1]) we proposed WLAN Manager (or WM) a centralised controller for QoS management of infrastructure WLANs based on the IEEE 802.11 DCF standards. The WM approach is based on queueing and scheduling packets in a device that sits between all traffic flowing between the APs and the wireline LAN, requires no changes to the AP or the STAs, and can be viewed as implementing a "Split-MAC" architecture. The objectives of WM were to manage various TCP performance related issues (such as the throughput "anomaly" when STAs associate with an AP with mixed PHY rates, and upload-download unfairness induced by finite AP buffers), and also to serve as the controller for VoIP admission control and handovers, and for other QoS management measures. In this paper we report our experiences in implementing the proposals in [1]: the insights gained, new control techniques developed, and the effectiveness of the WM approach in managing TCP performance in an infrastructure WLAN. We report results from a hybrid experiment where a physical WM manages actual TCP controlled packet flows between a server and clients, with the WLAN being simulated, and also from a small physical testbed with an actual AP.

Efficient Energy Management Policies for Networks with Energy Harvesting Sensor Nodes

We study sensor networks with energy harvesting nodes. The generated energy at a node can be stored in a buffer. A sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time at the node. For such networks we develop efficient energy management policies. First, for a single node, we obtain policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable suboptimal policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay. Next using the results for a single node, we develop efficient MAC policies.

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.

Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming

Folded Dynamic Programming (FDP) is adopted for developing optimalnreservoir operation policies for flood control. It is applied to a case study of Hirakud Reservoir in Mahanadi basin, India with the objective of deriving optimal policy for flood control. The river flows down to Naraj, the head of delta where a major city is located and finally joins the Bay of Bengal. As Hirakud reservoir is on the upstream side of delta area in the basin, it plays an important role in alleviating the severity of the flood for this area. Data of 68 floods such as peaks of inflow hydrograph, peak of outflow from reservoir during each flood, peak of flow hydrograph at Naraj and d/s catchment contribution are utilized. The combinations of 51, 54, 57 thousand cumecs as peak inflow into reservoir and 25.5, 20, 14 thousand cumecs respectively as,peak d/s catchment contribution form the critical combinations for flood situation. It is observed that the combination of 57 thousand cumecs of inflow into reservoir and 14 thousand cumecs for d/s catchment contribution is the most critical among the critical combinations of flow series. The method proposed can be extended to similar situations for deriving reservoir operating policies for flood control.

Control aspects in proportionality Markov manpower systems

In this paper, the control aspects of a hierarchical organization under the influence of "proportionality" policies are analyzed. Proportionality policies are those that restrict the recruitment to every level of the hierarchy (except the bottom most level or base level) to be in strict proportion to the promotions into that level. Both long term and short term control analysis have been discussed. In long term control the specific roles of the parameters of the system with regard to control of the shape and size of the system have been analyzed and yield suitable control strategies. In short term control, the attainability of a target or goal structure within a specific time from a given initial structure has been analyzed and yields the required recruitment strategies. The theoretical analyses have been illustrated with computational examples and also with real world data.

Control aspects in proportionality Markov manpower systems

In this paper, the control aspects of a hierarchical organization under the influence of "proportionality" policies are analyzed. Proportionality policies are those that restrict the recruitment to every level of the hierarchy (except the bottom most level or base level) to be in strict proportion to the promotions into that level. Both long term and short term control analysis have been discussed. In long term control the specific roles of the parameters of the system with regard to control of the shape and size of the system have been analyzed and yield suitable control strategies. In short term control, the attainability of a target or goal structure within a specific time from a given initial structure has been analyzed and yields the required recruitment strategies. The theoretical analyses have been illustrated with computational examples and also with real world data. The control of such proportionality systems is then compared with that of the general systems (which do not follow such policies) with some significant conclusions. The control relations of such proportionality systems are found to be simpler and more practically feasible than those of general Markov systems, which do not have such restrictions. Such proportionality systems thus not only retain and match the flexibility of general Markov systems but also have the added advantage of simpler and more practically feasible controls. The proportionality policies hence act as an alternative and more practicably feasible means of control. (C) 2004 Elsevier Inc. All rights reserved.

Air Fleet and Facility Planning via Optimal Control Models

A study is presented which is aimed at developing techniques suitable for effective planning and efficient operation of fleets of aircraft typical of the air force of a developing country. An important aspect of fleet management, the problem of resource allocation for achieving prescribed operational effectiveness of the fleet, is considered. For analysis purposes, it is assumed that the planes operate in a single flying-base repair-depot environment. The perennial problem of resource allocation for fleet and facility buildup that faces planners is modeled and solved as an optimal control problem. These models contain two "policy" variables representing investments in aircraft and repair facilities. The feasibility of decentralized control is explored by assuming the two policy variables are under the control of two independent decisionmakers guided by different and not often well coordinated objectives.

Air Fleet and Facility Planning via Optimal Control Models

A study is presented which is aimed at developing techniques suitable for effective planning and efficient operation of fleets of aircraft typical of the air force of a developing country. An important aspect of fleet management, the problem of resource allocation for achieving prescribed operational effectiveness of the fleet, is considered. For analysis purposes, it is assumed that the planes operate in a single flying-base repair-depot environment. The perennial problem of resource allocation for fleet and facility buildup that faces planners is modeled and solved as an optimal control problem. These models contain two "policy" variables representing investments in aircraft and repair facilities. The feasibility of decentralized control is explored by assuming the two policy variables are under the control of two independent decisionmakers guided by different and not often well coordinated objectives.

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Incentive mechanism to control customer buy-down behaviour

Airlines have successfully practiced revenue management over the past four decades and enhanced their revenue. Most of the traditional models that are applied assume that customers buying a high-fare class ticket will not purchase a low-fare class ticket even if it is available. This is not a very realistic assumption and has led to revenue leakage due to customers exhibiting buy-down behaviour. This paper aims at devising a suitable incentive mechanism that would incite the customer to reveal his nature. This helps in reducing revenue leakage. We show that the proposed incentive mechanism is profitable to both the buyer and seller and hence ensures the buyers participation in the mechanism. Journal of the Operational Research Society (2011) 62, 1566-1573. doi:10.1057/jors.2010.57 Published online 11 August 2010

Bandwidth management in a hybrid wireless network: For superstore applications

The integration of different wireless networks, such as GSM and WiFi, as a two-tier hybrid wireless network is more popular and economical. Efficient bandwidth management, call admission control strategies and mobility management are important issues in supporting multiple types of services with different bandwidth requirements in hybrid networks. In particular, bandwidth is a critical commodity because of the type of transactions supported by these hybrid networks, which may have varying bandwidth and time requirements. In this paper, we consider such a problem in a hybrid wireless network installed in a superstore environment and design a bandwidth management algorithm based on the priority level, classification of the incoming transactions. Our scheme uses a downlink transaction scheduling algorithm, which decides how to schedule the outgoing transactions based on their priority level with efficient use of available bandwidth. The transaction scheduling algorithm is used to maximize the number of transaction-executions. The proposed scheme is simulated in a superstore environment with multi Rooms. The performance results describe that the proposed scheme can considerably improve the bandwidth utilization by reducing transaction blocking and accommodating more essential transactions at the peak time of the business.

Energy Reduction in SRAM using Dynamic Voltage and Frequency Management

This paper describes a dynamic voltage frequency control scheme for a 256 X 64 SRAM block for reducing the energy in active mode and stand-by mode. The DVFM control system monitors the external clock and changes the supply voltage and the body bias so as to achieve a significant reduction in energy. The behavioral model of the proposed DVFM control system algorithm is described and simulated in HDL using delay and energy parameters obtained through SPICE simulation. The frequency range dictated by an external controller is 100 MHz to I GHz. The supply voltage of the complete memory system is varied in steps of 50 mV over the range of 500 mV to IV. The threshold voltage range of operation is plusmn100 mV around the nominal value, achieving 83.4% energy reduction in the active mode and 86.7% in the stand-by mode. This paper also proposes a energy replica that is used in the energy monitor subsystem of the DVFM system.