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

Author(s):  
Swapna Ganapaneni ◽  
Srinivasa Varma Pinni

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.

2020 ◽  
Vol 32 ◽  
pp. 01003
Author(s):  
Sachpreet Kaur ◽  
Ravtej Singh Sandhu ◽  
Tarlochan Kaur ◽  
Rintu Khanna

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.


2021 ◽  
Author(s):  
Babak Dayyani

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


2021 ◽  
Author(s):  
Babak Dayyani

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


2019 ◽  
Vol 8 (4) ◽  
pp. 10043-10046

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.


2020 ◽  
pp. 152-157
Author(s):  
Praveena P ◽  
Chandrika V S ◽  
Baranilingesan I ◽  
Ravindran S ◽  
Pazhanimuthu C

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.


Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1618
Author(s):  
Mohanasundaram Anthony ◽  
Valsalal Prasad ◽  
Raju Kannadasan ◽  
Saad Mekhilef ◽  
Mohammed H. Alsharif ◽  
...  

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.


2021 ◽  
Author(s):  
Sophie Adams ◽  
Lisa Diamond ◽  
Tara Esterl ◽  
Peter Fröhlich ◽  
Rishabh Ghotge ◽  
...  

Executive Summary of the final report of the Users TCP Social License to Automate Task findings from a 2 year project with 16 researchers in 6 countries, 26 Case studies spanning electric vehicles, home and precinct batteries, air conditioners and other heat pumps.


2014 ◽  
Vol 69 (5) ◽  
Author(s):  
Husna Syadli ◽  
Md Pauzi Abdullah ◽  
Muhammad Yusri Hassan ◽  
Faridah Hussin

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. 


2021 ◽  
Vol 20 (1) ◽  
pp. 21-33
Author(s):  
Hossam Eldin Hamed Shalaby

Electrical peak load demand all over the world is always anticipated to grow, which is challenging electrical utility to supply such increasing load demand in a cost effective, reliable and sustainable manner. Thus, there is a need to study some of load management (LM) techniques employed to minimize energy consumption, reduce consumers' electricity bills and decrease the greenhouse gas emissions responsible for global warming. This paper presents a review of several recent LM strategies and optimization algorithms in different domains. The review is complemented by tabulating several demand side management (DSM) techniques with a specific view on the used demand response (DR) programs, key finding and benefits gained. A special focus is directed to the communication protocols and wireless technology, incorporation of renewable energy resources (RERs), battery energy storage (BES), home appliances scheduling and power quality applications. The outcome of this review reveals that the real time pricing (RTP) is the most efficient price-based mechanism program (PBP), whilst time of use (TOU) is the basic PBP and easiest to implement. Energy efficiency programs have proved the highest influential impact on the annual energy saving over the other dynamic pricing mechanism programs. Through a forecasted proposal of future study, DSM proved tremendous potential annual energy savings, peak demand savings, and investment cost rates within different consumption sectors progressively up to year 2030.


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