scholarly journals Energy Saving and Interference Coordination in HetNets Using Dynamic Programming and CEC

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 71110-71121 ◽  
Author(s):  
Jose A. Ayala-Romero ◽  
Juan J. Alcaraz ◽  
Javier Vales-Alonso
Keyword(s):  
Dynamic Programming ◽  
Energy Saving ◽  
Interference Coordination

scholarly journals Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 588 ◽  
Author(s):  
Chaofeng Pan ◽  
Yanyan Liang ◽  
Long Chen ◽  
Liao Chen
Keyword(s):  
Dynamic Programming ◽  
Energy Consumption ◽  
Power System ◽  
Energy Saving ◽  
Electric Vehicle ◽  
System Efficiency ◽  
Rule Based ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Simulation Results

In this paper, the efficiency characteristics of battery, super capacitor (SC), direct current (DC)-DC converter and electric motor in a hybrid power system of an electric vehicle (EV) are analyzed. In addition, the optimal efficiency model of the hybrid power system is proposed based on the hybrid power system component’s models. A rule-based strategy is then proposed based on the projection partition of composite power system efficiency, so it has strong adaptive adjustment ability. Additionally. the simulation results under the New European Driving Cycle (NEDC) condition show that the efficiency of rule-based strategy is higher than that of single power system. Furthermore, in order to explore the maximum energy-saving potential of hybrid power electric vehicles, a dynamic programming (DP) optimization method is proposed on the basis of the establishment of the whole hybrid power system, which takes into account various energy consumption factors of the whole system. Compared to the battery-only EV based on simulation results, the hybrid power system controlled by rule-based strategy can decrease energy consumption by 13.4% in line with the NEDC condition, while the power-split strategy derived from the DP approach can reduce energy consumption by 17.6%. The results show that compared with rule-based strategy, the optimized DP strategy has higher system efficiency and lower energy consumption.

scholarly journals Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Zeyu Chen ◽  
Weiguo Liu ◽  
Ying Yang ◽  
Weiqiang Chen
Keyword(s):  
Dynamic Programming ◽  
Energy Saving ◽  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Energy Management Strategy ◽  
Driving Range ◽  
Hybrid Electric

The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs). An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence ona prioridriving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.

Online Learning for Energy Saving and Interference Coordination in HetNets

2019 ◽  
Vol 37 (6) ◽  
pp. 1374-1388 ◽  
Author(s):  
Jose A. Ayala-Romero ◽  
Juan J. Alcaraz ◽  
Andrea Zanella ◽  
Michele Zorzi
Keyword(s):  
Online Learning ◽  
Energy Saving ◽  
Interference Coordination

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

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