Load management

Smart Grid (SG) concept is defined as an electricity network operated intelligently to integrate the behavior and actions of all energy resources connected to the network to ensure efficient, sustainable, economic and secure supply of electricity. This concept emerged in recent decades not only for economic reasons but also ecological and even political. SG have been the subject of major studies and investments and continues to represent an area of enormous challenges. Some of the problems of intelligent systems connected to the managed SG are: the real-time processing optimization algorithms and demand response programs; and more accurate predictions in the management of production and consumption. This paper presents a case study for evaluating the performance and accuracy of energy consumption forecast with use of SVM (Support Vector Machines) in different frameworks.

The growing energy needs of 21st century have made the electricity grid more intelligent that can accomplish the demand. Smart energy management system needs to be integrated for efficient usage of energy. Internet of things is a megatrend of 21st century which can be effectively used for smart energy management system. The proposed system in this paper deals with cost effective smart load management for off-grid renewable energy sources. A prototype model is developed with solar panel, battery storage system, controllable loads and the smart load management is developed using microcontroller,4-channel relay module. The whole system is supervised using mobile with cloud storage app, Cayenne.

The main objective of this paper is to introduce power system economic operations in traditionally integrated power systems and market operations in deregulated power systems and study its effects. The power system economic operation is mathematically treated as an optimization problem. Also, a function of economic operation is to minimize generation cost, transmission losses, and so on, subject to power system operation constraints. In this paper, we start from generation cost formulations and introduce traditional economic dispatch model, optimal power flow model, and unit commitment model. With the deregulation of the power industry, integrated power system is unbundled to generation, transmission, and distribution. Electricity is traded in the wholesale market. Small customers purchase energy from electricity retailers through the retail market. The electricity market is operated for energy trading while satisfying power system operation requirements. Electricity market is mathematically modelled as an optimization problem that is subject to power system operation constraints and market operation constraints.

I The growing energy needs of 21st century have made the electricity grid more intelligent that can accomplish the demand. Smart energy management system needs to be integrated for efficient usage of energy. Internet of things is a megatrend of 21st century which can be effectively used for smart energy management system. The proposed system in this paper deals with cost effective smart load management for offgrid renewable energy sources. A prototype model is developed with solar panel, battery storage system, controllable loads and the smart load management is developed using microcontroller,4-channel relay module. The whole system is supervised using mobile with cloud storage app, Cayenne.

The International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes
articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all
technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together
researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts
and establishing new collaborations in these areas.

Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual's physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise ...

This article investigates mobility load balancing (MLB) algorithm implementation through network
simulator (ns-3) in long term evolution (LTE) systems employing orthogonal frequency division multiple
access (OFDMA) for downlink (DL) data transmission. MLB is introduced by the third generation
partnership project (3GPP) as a key target of LTE self-organizing networks (SONs) [1]. Our contribution
is twofold. First, we implemented elementary procedures (EPs) related to load management (LM) function
of the X2-application protocol (X2AP) as specified in TS 136.423 [2]. We particularly focused on EPs
’Resource Status Reporting Initiation Procedure’ and 'Resource Status Reporting Procedure’. Second, we
implemented a MLB based adaptive handover (HO) algorithm enabling to configure adaptively HO
hysteresis threshold for each neighbouring cell, of an overloaded cell, according to its current load
information. Numerical results show how, through suitable simulation scenarios, MLB enables enhancing
network performance in terms of overall throughput, packet loss ratio (PLR) and fairness without incurring
HO overhead.

With the advancement of science & technology, the demand for the electricity is increasing very fast for a rapidly increasing population. The traditional electricity grid suffers from blackouts, brownouts, and other reliability issues. Many research has been carried out for the development a more reliable and resilient grid. The Smart Grid is a future electricity grid with end-to-end data communication which will facilitate more reliable and efficient power delivery with significant economic benefits. Demand Side Management (DSM) is an important component of the Smart Grid. DSM programs try to reduce the peak demand for the electricity. This paper proposes a DSM technique for a University load. It proposes a bottom-up load modeling technique to study the pattern of electricity demand in Motilal Nehru National Institute of Technology Allahabad, India. Further, it proposes a load scheduling technique to shape the demand curve by rescheduling the class timetables.

The need for a novel design framework for optimal power management in low scale organizations necessitated this paper. This paper presents an ongoing research on an optimized SMS switching model for remote load management. A simplified design and flowchart model for Digital Monitoring Systems (DMS) is developed for the prototype implementation. In the implementation phase, the DMS was realized with an embedded controller as well as two sensors which monitor the grid power source and a backup generator power supply concurrently. Using a GSM Modem, a short message alert is generated at various instances to specific end users to switch off certain loads for proper load management and energy cost savings. This research when deployed in any organization will likely save energy costs which ideally drains organizational OPEX. A simulation schematic and the prototype construction with a validation model will form the basis for future work.