Various demand side management techniques and its role in smart grid–the state of art

The current lifestyle of humanity relies heavily on energy consumption, thus rendering it an inevitable need. An ever-increasing demand for energy has resulted from the increasing population. Most of this demand is met by the traditional sources that continuously deplete and raise significant environmental issues. The existing power structure of developing nations is aging, unstable, and unfeasible, further prolonging the problem. The existing electricity grid is unstable, vulnerable to blackouts and disruption, has high transmission losses, low quality of power, insufficient electricity supply, and discourages distributed energy sources from being incorporated. Mitigating these problems requires a complete redesign of the system of power distribution. The modernization of the electric grid, i.e., the smart grid, is an emerging combination of different technologies designed to bring about the electrical power grid that is changing dramatically. Demand side management (DSM) allow customers to be more involved in contributors to the power systems to achieve system goals by scheduling their shiftable load. Effective DSM systems require the participation of customers in the system that can be done in a fair system. This paper focuses primarily on techniques of DSM and demand responses (DR), including scheduling approaches and strategies for optimal savings

A transition from manual to Intelligent Automated power system operation -A Indicative Review

This paper reviews the transition of the power system operation from the traditional manual mode of power system operations to the level where automation using Internet of Things (IOT) and intelligence using Artificial Intelligence (AI) is implemented. To make the review paper brief only indicative papers are chosen to cover multiple power system operation based implementation. Care is taken there is lesser repeatation of similar technology or application be reviewed. The indicative review is to take only a representative literature to bypass scrutinizing multiple literatures with similar objectives and methods. A brief review of the slow transition from the traditional to the intelligent automated way of carrying out power system operations like the energy audit, load forecasting, fault detection, power quality control, smart grid technology, islanding detection, energy management etc is discussed .The Mechanical Engineering Perspective on the basis of applications would be noticed in the paper although the energy management and power delivery concepts are electrical

ASSESSMENT OF CONSUMERS POWER CONSUMPTION OPTIMIZATION BASED ON DEMAND SIDE MANAGEMENT

To ensure the functioning of the energy system, coordination and increase the efficiency of its parts need new control mechanisms. Generation, transmission and consumption of electricity needed control mechanisms that include integration of self-organizing power and heat supply systems, built on multi-agent principle. Also they must correspond intellectual basis, monitoring and accumulation. This includes effectiveness assessment of the state and analysis of technical, technological and organizational management mechanisms. One of the main parts is interaction principles of energy systems in accordance with European Community policy at various levels at liberalized electricity market. In most developed countries, demand management programs are widely used as a means of harmonizing the modes of generation and consumption in the power supply system. The main direct methods are set in the form of electricity tariffs. Indirect methods are set in the form of programs to manage electricity demand and the possibility of their application to manage electricity demand. Methods for estimating the unevenness of the daily schedule of electricity consumption and the factors influencing the technological environment are presented. The work aims at scientific and applied problem – finding methods of estimation and features of managing the demand for electricity. The use of the proposed estimation methods of electricity consumption influence non-uniformity on the level of power supplies system losses based on Frize QF power and optimization of consumers’ operation modes in the power supply system is considered. Approaches and optimization mechanisms of the daily electricity consumption on the example of a residential complex with the possibility of energy accumulation are offere

Load-shedding techniques for microgrids: A comprehensive review

Abstract: The increasing interest in integrating renewable energies source has raised concerns about control operations. The presence of new energy sources, distributed storage, power electronic devices and communication links make a power system’s control and monitoring more complex and adaptive than ever before. Recently, the use of agent-based distributed control has seen to have a significant impact on the grid and microgrid controls. The load-shedding technique is among the features used to balance the power consumption in the power system upon less power production. Towards achieving these, different mechanisms, algorithms, challenges, and approaches have been developed and hence need to be reviewed and integrated from the system solution perspective. This research focuses on the review of the state-of-the-art load-shedding techniques, whereby the focus is on control algorithms, simulation platforms and integrations, and control devices for DC microgrid. The research also investigates open issues and challenges that need further investigations. The analyses reported in the paper upholds the importance of the distributed multi-agent system, MAS, in implementing distinct control operations including load-shedding. The effectiveness of the control operations using MAS rely on low-latency and secure communication links in which IoT has been branded as a promising technology for implementing distributed MAS.</p

Internet of Things Applications as Energy Internet in Smart Grids and Smart Environments

Energy Internet (EI) has been recently introduced as a new concept, which aims to evolve smart grids by integrating several energy forms into an extremely flexible and effective grid. In this paper, we have comprehensively analyzed Internet of Things (IoT) applications enabled for smart grids and smart environments, such as smart cities, smart homes, smart metering, and energy management infrastructures to investigate the development of the EI based IoT applications. These applications are promising key areas of the EI concept, since the IoT is considered one of the most important driving factors of the EI. Moreover, we discussed the challenges, open issues, and future research opportunities for the EI concept based on IoT applications and addressed some important research areas

Distributed Load Scheduling in Residential Neighborhoods for Coordinated Operation of Multiple Home Energy Management Systems

Recently, home energy management systems (HEMS) are gaining more popularity enabling customers to minimize their electricity bill under time-varying electricity prices. Although they offer a promising solution for better energy management in smart grids, the uncoordinated and autonomous operation of HEMS may lead to some operational problems at the grid level. This paper aims to develop a coordinated framework for the operation of multiple HEMS in a residential neighborhood based on the optimal and secure operation of the grid. In the proposed framework customers cooperate to optimize energy consumption at the neighborhood level and prevent any grid operational constraints violation. A new price-based global and individualized incentives are proposed for customers to respond and adjust loads. The individual customers are rewarded for their cooperation and the network operator benefits by eliminating rebounding network peaks. The alternating direction method of multipliers (ADMM) technique is used to implement coordinated load scheduling in a distributed manner reducing the computational burden and ensure customer privacy. Simulation results demonstrate the efficacy of the proposed method in maintaining nominal network conditions while ensuring benefits for individual customers as well as grid operators

A hybrid prediction-based microgrid energy management strategy considering demand-side response and data interruption

© 2019 Data interruption may cause the centralized energy management system of a microgrid (MG)to collapse. To solve this problem, a hybrid prediction-based energy management strategy is proposed in this paper to predict interrupted data for the centralized dispatching process of an MG. This hybrid prediction method is designed following a combination of model predictive control and extreme learning machine techniques. Based on the predicted data of distributed energy resources and three types of loads from demand-side response, an optimization model is formulated to minimize the operational cost. If some predicted data are interrupted during transmission, then a prospect vulnerability assessment method is applied to select a neighboring device to predict the interrupted data. In the end, an improved particle swarm optimization algorithm is proposed with the help of genetic algorithms to accelerate convergence to global optimal solutions for the proposed MG energy management problem. The effectiveness of the proposed models and solution methods is also verified by a case study

Review of technologies for DC grids - power conversion, flow control and protection

Abstract: This article reviews dc transmission technologies for future power grids. The article emphasizes the attributes that each technology offers in terms of enhance controllability and stability, resiliency to ac and dc faults, and encourage increased exploitations of renewable energy resources (RERs) for electricity generation. Discussions of ac/dc and dc/dc converters reveal that the self-commutated dc transmission technologies are critical for better utilization of large RERs which tend to be dispersed over wide geographical areas, and offer needed controllability for operation of centralized and decentralized power grids. It is concluded that the series power flow controllers have potential to restrict the expensive isolated dc/dc converters to few applications, in which the prevention of dc fault propagation is paramount. Cheaper non-isolated dc/dc converters offer dc voltage tapping and matching and power regulation but they are unable to prevent pole-shifting during pole-to-ground dc fault. To date hybrid dc circuit breakers target dc fault isolation times ranging from 3ms to 5ms; while the resonance-based dc circuit breakers with forced current zeros target dc fault clearance times from 8ms to 12.5ms

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

[EN] Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. 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