Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization

This paper proposes Object-Oriented Usability Indices (OOUI) for multi-objective Demand Side Management (DSM). These indices quantify the achievements of multi-objective DSM in a power network. DSM can be considered as a method adopted by utilities to shed some load during peak load hours. Usually, there are service contracts, and the curtailments or dimming of load are automatically done by service providers based on contract provisions. This paper formulates three indices, namely peak power shaving, renewable energy integration, and an overall usability index. The first two indices indicate the amount of peak load shaving and integration of renewable energy, while the third one combines the impact of both indices and quantifies the overall benefit achieved through DSM. The application of the proposed indices is presented through simulation performed in a grid-tied microgrid environment for a multi-objective DSM formulation. The adopted microgrid structure consists of three units of diesel generators and two renewable energy sources. Simulation has been done using MATLAB software. Teaching-Learning-Based Optimization (TLBO) is adopted as the optimization tool due to its simplicity and independency of algorithm-specific control parameters. Five different cases of renewable energy availability with results validate the efficiency of the proposed approach. The results indicate the usefulness in determining the suitable condition regarding DSM application.

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Demand Side Management for Reducing Rolling Blackouts Due to Power Supply Deficit in Sumatra

Jurnal Teknologi ◽

10.11113/jt.v69.3202 ◽

2014 ◽

Vol 69 (5) ◽

Author(s):

Husna Syadli ◽

Md Pauzi Abdullah ◽

Muhammad Yusri Hassan ◽

Faridah Hussin

Keyword(s):

Power Systems ◽

Customer Service ◽

Power Supply ◽

Management Strategies ◽

Peak Load ◽

Demand Side Management ◽

Demand Side ◽

Demand Growth ◽

Save Energy ◽

The Impact

When the high electricity demand growth is not matched by growth in generating sufficient capacity, deficit cannot be avoided. In Sumatera, power outages of up to 6 hours per day are part of the power crisis experienced. To date, deficits experienced by Sumatera require better management strategy and operation of electric power systems, taking into account the security system, reliability and customer service. This paper briefly discusses the impact of rolling blackouts on the community's economy and proposed demand-side management strategies as short term measure to overcome the power supply deficit in Sumatera. From the analysis, electricity savings in household equipment can save energy consumption by 98.79 MW at peak load and 97.55 MW for off peak load time.

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Demand Side Management for Commercial Area Using Teaching Learning Based Optimization

10.3233/apc210304 ◽

2021 ◽

Author(s):

Dhanshri Narayane ◽

Amarjeet S Pandey ◽

D B Pardeshi ◽

Renuka Rasal

Keyword(s):

Smart Grid ◽

Management Strategy ◽

Optimization Problems ◽

Demand Side Management ◽

Demand Side ◽

Load Shifting ◽

Load Demand ◽

Commercial Area ◽

Teaching Learning Based Optimization ◽

Teaching Learning

In Smart Grid Demand side management (DSM) plays a crucial role which permits customers to form educated selections concerning their energy consumption. It allows the strength to companies lessen the height load call for and reshape the burden profile. Most of the present demand aspect management ways utilized in ancient energy management system is with specific techniques and algorithms. In addition, the present ways handle solely a restricted range of governable a lot of restricted varieties of loads. This paper covers a requirement aspect management strategy supported load shifting technique for demand aspect management of future sensible grids with an outsized range of devices of many sorts. The day-in advance load shifting technique is proposed and mathematically formulated as a minimization problem. Teaching Learning Based Optimization (TLBO) is an efficient optimization is proposed. Considering Smart Grid with commercial customer, Simulations has been carried out. The respective results emphasis that the considered demand side management strategy attains substantial savings, whereas suppresses the mark of load demand of the smart grid. The outcome is by improve in sustainability of the smart grid, in addition to reduced standard operational value and carbon emission levels. The proposed algorithms can be easily applied to various optimization problems.

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DEMAND SIDE MANAGEMENT OF RENEWABLE ENERGY INTEGRATED SMART GRID USING LOAD SHIFTING TECHNIQUES

Journal of Critical Reviews ◽

10.31838/jcr.07.10.546 ◽

2020 ◽

pp. 3193-3199

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Smart Grid ◽

Energy Management ◽

Demand Side Management ◽

Energy Resources ◽

Management Approach ◽

Demand Side ◽

Load Shifting ◽

The Impact

The Paris Agreement on Climate Change has led to introduction of new reforms for clean power plan such as decarbonization of power sector, planned decommissioning of thermal power plants and inclusion of renewable energies for power production. But this desired integration of renewable energy resources to power system faces two technical challenges: variability and uncertainty. An effective energy management with help of smart grid engineering can be the key for its beneficial use. Demand Side Management (DSM) is a valuable strategy for energy management in smart grid. It supports numerous smart grid functionalities for instance electricity market control, Load scheduling, managing decentralized distributed energy resources. Identifying energy consumption patterns and to sketch electricity load profiles can be achieved through numerous DSM based programs. Load shifting based DSM can be linked to consumer’s behavior in understanding their pattern of energy consumption. Here, the practiced load shifting based demand side management approach can help in maximizing power efficiency, sustaining power reliability and resiliency of renewable sources. This paper reviews the various energy management strategies developed to minimize the impact of renewable energy intermittency using Load Shifting Demand Side Management (DSM) approach.

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A Techno-Economic Comparison of Demand Side Management with Other Flexibility Options

The Future European Energy System ◽

10.1007/978-3-030-60914-6_9 ◽

2021 ◽

pp. 155-173

Author(s):

Theresa Ladwig

Keyword(s):

System Integration ◽

Power Plants ◽

Renewable Energy Sources ◽

Peak Load ◽

Demand Side Management ◽

Demand Side ◽

Load Increase ◽

Flexibility Options ◽

The Impact ◽

Economic Comparison

AbstractThis chapter assesses the techno-economic characteristics of demand side management (DSM) in comparison with other flexibility options (e.g., energy storages) in order to estimate its flexibility and benefit for the system integration of renewable energy sources (RES). The results show that load shedding and load shifting are less flexible than other flexibility options and can therefore only balance short-term fluctuations. In contrast, load increase is more flexible and can integrate excess feed-in from RES also over longer periods. Analysis about the impact of DSM on other flexibility options show, that DSM lowers utilization and contribution margin of peak load plants and energy storages, while it increases both for baseload power plants. More electricity is consumed nationally due to DSM as it decreases imports and exports.

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Demand Side Management based techno-economic performance analysis for a stand-alone hybrid renewable energy system of India

Energy Sources Part A Recovery Utilization and Environmental Effects ◽

10.1080/15567036.2020.1851820 ◽

2021 ◽

pp. 1-29

Author(s):

Mala Ramesh ◽

Rajeshwer Prasad Saini

Keyword(s):

Renewable Energy ◽

Performance Analysis ◽

Economic Performance ◽

Demand Side Management ◽

Energy System ◽

Demand Side ◽

Hybrid Renewable Energy System ◽

Renewable Energy System ◽

Hybrid Renewable Energy

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An Adaptive Multi-objective Salp Swarm Algorithm for Efficient Demand Side Management

2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) ◽

10.1109/mass50613.2020.00044 ◽

2020 ◽

Author(s):

Zezheng Zhao ◽

Chunqiu Xia ◽

Lian Chi ◽

Xiaomin Chang ◽

Wei Li ◽

...

Keyword(s):

Demand Side Management ◽

Demand Side ◽

Salp Swarm Algorithm ◽

Multi Objective ◽

Swarm Algorithm

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Autonomous Fuzzy Controller Design for the Utilization of Hybrid PV-Wind Energy Resources in Demand Side Management Environment

Electronics ◽

10.3390/electronics10141618 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1618

Author(s):

Mohanasundaram Anthony ◽

Valsalal Prasad ◽

Raju Kannadasan ◽

Saad Mekhilef ◽

Mohammed H. Alsharif ◽

...

Keyword(s):

Wind Energy ◽

Energy Cost ◽

Fuzzy Controller ◽

Residential Buildings ◽

Peak Load ◽

Demand Side Management ◽

Consumption Pattern ◽

Demand Side ◽

Pv System ◽

Inference System

This work describes an optimum utilization of hybrid photovoltaic (PV)—wind energy for residential buildings on its occurrence with a newly proposed autonomous fuzzy controller (AuFuCo). In this regard, a virtual model of a vertical axis wind turbine (VAWT) and PV system (each rated at 2 kW) are constructed in a MATLAB Simulink environment. An autonomous fuzzy inference system is applied to model primary units of the controller such as load forecasting (LF), grid power selection (GPS) switch, renewable energy management system (REMS), and fuzzy load switch (FLS). The residential load consumption pattern (4 kW of connected load) is allowed to consume energy from the grid and hybrid resources located at the demand side and classified as base, priority, short-term, and schedulable loads. The simulation results identify that the proposed controller manages the demand side management (DSM) techniques for peak load shifting and valley filling effectively with renewable sources. Also, energy costs and savings for the home environment are evaluated using the proposed controller. Further, the energy conservation technique is studied by increasing renewable conversion efficiency (18% to 23% for PV and 35% to 45% for the VAWT model), which reduces the spending of 0.5% in energy cost and a 1.25% reduction in grid demand for 24-time units/day of the simulation study. Additionally, the proposed controller is adapted for computing energy cost (considering the same load pattern) for future demand, and it is exposed that the PV-wind energy cost reduced to 6.9% but 30.6% increase of coal energy cost due to its rise in the Indian energy market by 2030.

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