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.

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Home Load-Side Management in Smart Grids Using Global Optimization

Handbook of Research on Smart Power System Operation and Control - Advances in Computer and Electrical Engineering ◽

10.4018/978-1-5225-8030-0.ch005 ◽

2019 ◽

pp. 127-161

Author(s):

Abdelmadjid Recioui

Keyword(s):

Smart Grids ◽

Energy Use ◽

Peak Load ◽

Computational Cost ◽

Demand Side Management ◽

Demand Side ◽

Demand And Supply ◽

Management Techniques ◽

Increasing Demand

Demand-side management (DSM) is a strategy enabling the power supplying companies to effectively manage the increasing demand for electricity and the quality of the supplied power. The main objectives of DSM programs are to improve the financial performance and customer relations. The idea is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times. The DSM controls the match between the demand and supply of electricity. Another objective of DSM is to maintain the power quality in order to level the load curves. In this chapter, a genetic algorithm is used in conjunction with demand-side management techniques to find the optimal scheduling of energy consumption inside N buildings in a neighborhood. The issue is formulated as multi-objective optimization problem aiming at reducing the peak load as well as minimizing the energy cost. The simulations reveal that the adopted strategy is able to plan the daily energy consumptions of a great number of electrical devices with good performance in terms of computational cost.

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Home Load-Side Management in Smart Grids Using Global Optimization

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms ◽

10.4018/978-1-7998-8048-6.ch051 ◽

2021 ◽

pp. 1017-1052

Author(s):

Abdelmadjid Recioui

Keyword(s):

Smart Grids ◽

Energy Use ◽

Peak Load ◽

Computational Cost ◽

Demand Side Management ◽

Demand Side ◽

Demand And Supply ◽

Management Techniques ◽

Increasing Demand

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Impacts of Demand-Side Management on Electrical Power Systems: A Review

Energies ◽

10.3390/en11051050 ◽

2018 ◽

Vol 11 (5) ◽

pp. 1050 ◽

Cited By ~ 27

Author(s):

Hussein Jabir ◽

Jiashen Teh ◽

Dahaman Ishak ◽

Hamza Abunima

Keyword(s):

Power Systems ◽

Electrical Power ◽

Demand Side Management ◽

Demand Side ◽

Electrical Power Systems

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A Survey on Demand Side Management In Electrical Power Systems

i-manager s Journal on Power Systems Engineering ◽

10.26634/jps.5.1.13536 ◽

2017 ◽

Vol 5 (1) ◽

pp. 40

Author(s):

IBRAHIM AHMED M. ◽

ATTIA MAHMOUD A. ◽

OTHMAN MAHMOUD M. ◽

ABDELAZIZ ALMOATAZ Y. ◽

◽

...

Keyword(s):

Power Systems ◽

Electrical Power ◽

Demand Side Management ◽

Demand Side ◽

Electrical Power Systems ◽

On Demand

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Additional applications of demand side management techniques in power systems integrated with distributed generation

18th International Conference and Exhibition on Electricity Distribution (CIRED 2005) ◽

10.1049/cp:20051239 ◽

2005 ◽

Author(s):

Y.S. Lim ◽

S. White ◽

G. Nicholson ◽

P. Taylor

Keyword(s):

Power Systems ◽

Distributed Generation ◽

Demand Side Management ◽

Demand Side ◽

Management Techniques

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Improving Efficiency of Power Systems by Demand Side Management Method

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v7i1.pp100-106 ◽

2017 ◽

Vol 7 (1) ◽

pp. 100

Author(s):

Tibbie Pon Symon V.A. ◽

I. Jacob Ragland

Keyword(s):

Smart Grid ◽

Power Systems ◽

Stochastic Scheduling ◽

Demand Side Management ◽

Pso Algorithm ◽

Normal System ◽

System Control ◽

Demand Side ◽

Efficient Manner ◽

Management Method

In the smart grid infrastructure based power systems, it is necessary to consider the demand side management to enhance the energy reduction and system control. In many countries the resources are very less so the available resources have to be used in an efficient manner without any loss. The total loss cannot be avoided but it can be reduced. In the proposed system, the Particle Swarm Optimization (PSO) technique is used to distribute the power in the smart grid. Here, the grids are arranged in such a way that the losses in it are reduced. The load connected to the grid is rearranged according to their use. It uses a new and stochastic scheduling technique to handle the uncertainties in the power system. Solar and wind power are taken in account for twenty four hours and the values are given to the PSO algorithm. The experiment was conducted by MATLAB and the results show that the efficiency level of wind and solar power systems was increased by an appreciable level. The proposed technique is compared with the normal system without using Demand Side Management (DSM) and it shows that the proposed system gives better results than the existing systems.

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Adaptive demand-side management in smart grid with plug-in electric vehicle

10.1063/5.0032640 ◽

2020 ◽

Author(s):

Shashank Singh ◽

Shiva Pujan Jaiswal

Keyword(s):

Smart Grid ◽

Electric Vehicle ◽

Demand Side Management ◽

Demand Side

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Architectural and functional classification of smart grid solutions

Energy Informatics ◽

10.1186/s42162-019-0083-1 ◽

2019 ◽

Vol 2 (S1) ◽

Author(s):

Friederike Wenderoth ◽

Elisabeth Drayer ◽

Robert Schmoll ◽

Michael Niedermeier ◽

Martin Braun

Keyword(s):

Smart Grid ◽

Power Systems ◽

Power System ◽

Power Distribution ◽

Hierarchical Architecture ◽

Distribution Grid ◽

Active System ◽

System Operation ◽

Power System Operation

Abstract Historically, the power distribution grid was a passive system with limited control capabilities. Due to its increasing digitalization, this paradigm has shifted: the passive architecture of the power system itself, which includes cables, lines, and transformers, is extended by a communication infrastructure to become an active distribution grid. This transformation to an active system results from control capabilities that combine the communication and the physical components of the grid. It aims at optimizing, securing, enhancing, or facilitating the power system operation. The combination of power system, communication, and control capabilities is also referred to as a “smart grid”. A multitude of different architectures exist to realize such integrated systems. They are often labeled with descriptive terms such as “distributed,” “decentralized,” “local,” or “central." However, the actual meaning of these terms varies considerably within the research community.This paper illustrates the conflicting uses of prominent classification terms for the description of smart grid architectures. One source of this inconsistency is that the development of such interconnected systems is not only in the hands of classic power engineering but requires input from neighboring research disciplines such as control theory and automation, information and telecommunication technology, and electronics. This impedes a clear classification of smart grid solutions. Furthermore, this paper proposes a set of well-defined operation architectures specialized for use in power systems. Based on these architectures, this paper defines clear classifiers for the assessment of smart grid solutions. This allows the structural classification and comparison between different smart grid solutions and promotes a mutual understanding between the research disciplines. This paper presents revised parts of Chapters 4.2 and 5.2 of the dissertation of Drayer (Resilient Operation of Distribution Grids with Distributed-Hierarchical Architecture. Energy Management and Power System Operation, vol. 6, 2018).

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