scholarly journals Peak-Load Reduction by Coordinated Response of Photovoltaics, Battery Storage, and Electric Vehicles

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 29353-29365 ◽  
Author(s):  
Khizir Mahmud ◽  
M. Jahangir Hossain ◽  
Graham E. Town
2018 ◽  
Vol 8 (1) ◽  
pp. 2621-2626 ◽  
Author(s):  
D. Behrens ◽  
T. Schoormann ◽  
R. Knackstedt

Due to technological improvement and changing environment, energy grids face various challenges, which, for example, deal with integrating new appliances such as electric vehicles and photovoltaic. Managing such grids has become increasingly important for research and practice, since, for example, grid reliability and cost benefits are endangered. Demand response (DR) is one possibility to contribute to this crucial task by shifting and managing energy loads in particular. Realizing DR thereby can address multiple objectives (such as cost savings, peak load reduction and flattening the load profile) to obtain various goals. However, current research lacks algorithms that address multiple DR objectives sufficiently. This paper aims to design a multi-objective DR optimization algorithm and to purpose a solution strategy. We therefore first investigate the research field and existing solutions, and then design an algorithm suitable for taking multiple objectives into account. The algorithm has a predictable runtime and guarantees termination.


Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2304 ◽  
Author(s):  
Mingfu Li ◽  
Guan-Yi Li ◽  
Hou-Ren Chen ◽  
Cheng-Wei Jiang

To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE.


2019 ◽  
Vol 13 (3) ◽  
pp. 3274-3282 ◽  
Author(s):  
Hanane Dagdougui ◽  
Ahmed Ouammi ◽  
Louis A. Dessaint

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Qingshan Xu ◽  
Yujun Liu ◽  
Maosheng Ding ◽  
Pingliang Zeng ◽  
Wei Pan

Electric vehicles (EVs) are developing remarkably fast these years which makes the technology of vehicle-to-grid (V2G) easier to implement. Peak load shifting (PLS) is an important part of V2G service. A model of EVs’ capacity in V2G service is proposed for the research on PLS in this paper. The capacity is valued in accordance with three types of situations. Based on the model, three different scenarios are suggested in order to evaluate the capacity with MATLAB. The evaluation results indicate that EVs can provide potential energy to participate in PLS. Then, the principle of PLS with EVs is researched through the analysis of the relationship between their power and capacity. The performance of EVs in PLS is also simulated. The comparison of two simulation results shows that EVs can fulfill the request of PLS without intensely lowering their capacity level.


2019 ◽  
Vol 13 (2) ◽  
pp. 1872-1882 ◽  
Author(s):  
Khizir Mahmud ◽  
M. J. Hossain ◽  
Jayashri Ravishankar

2019 ◽  
Vol 10 (3) ◽  
pp. 1034-1043 ◽  
Author(s):  
Ibrahim Sengor ◽  
Ozan Erdinc ◽  
Baris Yener ◽  
Akin Tascikaraoglu ◽  
Joao P. S. Catalao

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