scholarly journals Demand Side Management Technique to Optimally Schedule Electric Vehicle Loads in Smart Grid

2019 ◽  
Vol 8 (4) ◽  
pp. 10043-10046
Keyword(s):  
Electric Vehicles ◽  
Smart Grids ◽  
Peak Load ◽  
Demand Side Management ◽  
Management Technique ◽  
Demand Side ◽  
Load Curve ◽  
Load Variations ◽  
Vehicle Loads ◽  
Aggregated Load

Demand-side management (DSM) in smart grids helps the problem of reducing peak load of utilities during certain hourly periods. Based on DSM techniques, peak load hours can be equalized to non-peak load hours therefore users will have less bill payments. In this paper optimal scheduling of Electric Vehicles (EVs) is done based on an objective function formulated to minimize the load variations. Firstly, hourly consumption of load during a day at Koneru Lakshmaiah Education Foundation is considered, EVs load is assumed and flattened the aggregated load curve by optimally scheduling the EVs during off peak hours.

scholarly journals Demand side management based charging strategy for fleet of plug-in hybrid electric vehicles

2020 ◽  
Vol 32 ◽  
pp. 01003
Author(s):  
Sachpreet Kaur ◽  
Ravtej Singh Sandhu ◽  
Tarlochan Kaur ◽  
Rintu Khanna
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Peak Load ◽  
Demand Side Management ◽  
Total Power ◽  
Demand Side ◽  
Electric Grid ◽  
Smart Charging ◽  
Hybrid Electric ◽  
Charging Strategy

In coming years, the widespread use of Plug-in Hybrid Electric Vehicles (PHEVs) will impose a significant burden on the existing electric grid. The situation may worsen due to uncontrolled charging strategies adopted for PHEVs. On the other hand, these PHEVs, if charged through proper control mechanisms may reduce additional dynamic load demands. Also, if utilized properly, they may provide significant support to electric grid from time to time. The entire process of regulating the power exchanged with PHEVs w.r.t the existing grid conditions is well known as Demand Side Management (DSM). To indulge PHEVs in DSM, an accurate estimate of characteristics of PHEVs, both on-road and off-road, is necessary. Thus, this study aims to mathematically model the behaviour of four imperative parameters of PHEVs. These are dynamic travel behaviour, battery state-of-charge (SOC) requirements, the energy demands of PHEVs and, total power exchanged by PHEVs with the electric grid. In addition to this, a smart charging strategy is proposed and tested to verify the ability of PHEVs for participating in DSM for peak load management. The impacts of uncontrolled charging and smart charging of PHEVs on grid power demands are also discussed.

scholarly journals Demand side management by PHEV charging scheduling in residential areas

2021 ◽  
Author(s):  
Babak Dayyani
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Peak Load ◽  
Demand Side Management ◽  
Distribution Networks ◽  
Utilization Rate ◽  
Demand Side ◽  
Transit System ◽  
Water Filling ◽  
Hybrid Electric

During the last decade, Plug-in Hybrid Electric Vehicles (PHEVs) have become a part of modern transportation fleet, offering green alternatives to fossil fuel based transit system. Taking PHEVs great potentials into consideration, this transition can revolutionize transportation systems and push technological advancements further. However, in spite of plentiful economical and environmental advantages, new concerns are being brought up as PHEVs’ utilization rate increases. PHEV’s driving force is supplied by electricity. Hence, the built-in battery requires charging. Such newly introduced power demand, has raised alarming realizations for utility providers. Impacts of PHEVs on distribution networks, although have been proven to be noticeable, have not been thoroughly investigated for future years. In smart grid, the charging of PHEVs can be controlled to reduce the peak load, known as Demand-Side Management (DSM). In this work, we explore various DSM approaches accompanied by their effects on power consumption patterns. Moreover, Geometric Water-filling (GWF) method has been utilized to increase the accuracy of our proposed scheduling schemes. The main contribution of this work emerges by fusing consumer and utility provider concerns, resulting in our dual-target objective function. Such method allows us to alter the focal point between consumer and utility company satisfaction. Index Terms: Plug-in Hybrid Electric Vehicles, Demand-Side Management, Water-Filling

scholarly journals Real-Time Demand Side Management Algorithm Using Stochastic Optimization

2018 ◽  
Author(s):  
Moses Amoasi Acquah ◽  
Daisuke Kodaira ◽  
Sekyung Han
Keyword(s):  
Stochastic Optimization ◽  
Real Time ◽  
Peak Load ◽  
Demand Side Management ◽  
Management Technique ◽  
Demand Side ◽  
Demand Forecast ◽  
Electricity Cost ◽  
Management Algorithm ◽  
Battery Energy

A Demand-side management technique are deployed along with battery energy-storage systems (BESSs) to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand

Home Load-Side Management in Smart Grids Using Global Optimization

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.

Home Load-Side Management in Smart Grids Using Global Optimization

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

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.

scholarly journals Optimizing the effect of charging electric vehicles on distribution transformer using demand side management

2022 ◽  
Vol 25 (1) ◽  
pp. 25
Author(s):  
Swapna Ganapaneni ◽  
Srinivasa Varma Pinni
Keyword(s):  
Electric Vehicles ◽  
Peak Load ◽  
Demand Side Management ◽  
Residential Area ◽  
Demand Side ◽  
Objective Functions ◽  
Distribution Transformer ◽  
Price Prediction ◽  
Modeling Software ◽  
Actual Price

This paper mainly aims to present the demand side management (DSM) of electric vehicles (EVs) by considering distribution transformer capacity at a residential area. The objective functions are formulated to obtain charging schedule for individual owner by i) minimizing the load variance and ii) price indicated charging mechanism. Both the objective functions profit the owner in the following ways: i) fulfilling their needs, ii) minimizing overall charging cost, iii) lessening the peak load, and iv) avoiding the overloading of distribution transformer. The proposed objective functions were worked on a residential area with 8 houses each house with an EV connected to a 20 kVA distribution transformer. The formulations were tested in LINGO platform optimization modeling software for linear, nonlinear, and integer programming. The results obtained were compared which gives good insight of EV load scheduling without actual price prediction.

scholarly journals Demand side management by PHEV charging scheduling in residential areas

2021 ◽  
Author(s):  
Babak Dayyani
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Peak Load ◽  
Demand Side Management ◽  
Distribution Networks ◽  
Utilization Rate ◽  
Demand Side ◽  
Transit System ◽  
Water Filling ◽  
Hybrid Electric

During the last decade, Plug-in Hybrid Electric Vehicles (PHEVs) have become a part of modern transportation fleet, offering green alternatives to fossil fuel based transit system. Taking PHEVs great potentials into consideration, this transition can revolutionize transportation systems and push technological advancements further. However, in spite of plentiful economical and environmental advantages, new concerns are being brought up as PHEVs’ utilization rate increases. PHEV’s driving force is supplied by electricity. Hence, the built-in battery requires charging. Such newly introduced power demand, has raised alarming realizations for utility providers. Impacts of PHEVs on distribution networks, although have been proven to be noticeable, have not been thoroughly investigated for future years. In smart grid, the charging of PHEVs can be controlled to reduce the peak load, known as Demand-Side Management (DSM). In this work, we explore various DSM approaches accompanied by their effects on power consumption patterns. Moreover, Geometric Water-filling (GWF) method has been utilized to increase the accuracy of our proposed scheduling schemes. The main contribution of this work emerges by fusing consumer and utility provider concerns, resulting in our dual-target objective function. Such method allows us to alter the focal point between consumer and utility company satisfaction. Index Terms: Plug-in Hybrid Electric Vehicles, Demand-Side Management, Water-Filling

scholarly journals Demand Side Management for Charging Plug-In Hybrid Electric Vehicles

2020 ◽  
pp. 152-157
Author(s):  
Praveena P ◽  
Chandrika V S ◽  
Baranilingesan I ◽  
Ravindran S ◽  
Pazhanimuthu C
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Hybrid Electric Vehicles ◽  
Low Voltage ◽  
Peak Load ◽  
Demand Side Management ◽  
Demand Side ◽  
Wide Range ◽  
Hybrid Electric ◽  
Power Curves

In future the usage of Plug-in hybrid electric vehicles (PHEV) will be in wide range, which will impose huge burden to the distributive system. The peak load at the distribution system can be controlled by Demand Side Management (DSM) strategy. In the proposed study, the load curve of Low-voltage Transformers (LVTs) is made to be flatten, on satisfying the requirement of charging PHEV at given time to the required level. The proposed problem statement is formulated as convex optimization problem, and then the random arrival of PHEV is handled by introducing the moving horizon strategy. Based on this, the PHEV are being disconnected from the LVTs beyond their respective exit times. Such that the demand curve of the LVTs is flattened. This problem is solved using MATLAB and the power demand curves of the LVTs, power curves of the PHEVs and non- PHEV load are compared over a time of 24 hours to show that the power curve is flattened with the penetration of PHEV.

Sign in / Sign up

Export Citation Format

Share Document