A Novel Optimization of Plug-In Electric Vehicles Charging and Discharging Behaviors in Electrical Distribution Grid

In most countries, the problems of energy and environment are becoming worse. To deal with the environmental impacts and the dependence on fossil energy, many solutions were proposed. Plug-in electric vehicles (PEVs) is one of the best technique among these solutions. However, the large number of PEVs connected to the power grid simultaneously might increase power fluctuation or even cause the electricity shortage and thus affecting the typical use of the basic load. To cope with this issue and inspire PEV users coordinating with scheduling results, an algorithm was proposed to ensure the power transmission safety of branches and maximize the economic benefits. Considering the cost of both PEV owners and the power grid, a two-phase model of optimizing PEVs charging and discharging behaviors was built. According to the traveling purpose of PEV owners and the current electricity price, in the first phase, a novel model which defines each PEV’s charging or discharging status was established. The number of PEVs’ charging and discharging in each charging station can be obtained. Considering the constraints on the power transportation of branch, in the second phase, we built a mathematical model to maximize the benefit of both power grid and PEV owners. The genetic algorithm was used to optimize the charging and discharging power of PEVs. Simulation results show that the optimization method proposed in this paper has a better performance on the daily power curve compared with the uncoordinated PEVs charging.

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Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Journal of Advanced Transportation ◽

10.1155/2020/8890233 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Xiaomin Xu ◽

Dongxiao Niu ◽

Yan Li ◽

Lijie Sun

Keyword(s):

Electric Vehicles ◽

Optimization Problems ◽

Power Grid ◽

Economic Benefits ◽

Pricing Strategy ◽

Optimal Pricing ◽

Electricity Pricing ◽

Optimal Pricing Strategy ◽

Charging Stations ◽

The Impact

Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

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The Study on Robust Controller Synthesis Using Genetic Optimization Algorithm Integrating Taguchi Methods

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.284-287.2341 ◽

2013 ◽

Vol 284-287 ◽

pp. 2341-2345

Author(s):

Ho Nien Shou

Keyword(s):

Taguchi Method ◽

Parameter Optimization ◽

Optimization Method ◽

Controller Synthesis ◽

Taguchi Methods ◽

Superior Performance ◽

Second Phase ◽

Quality Factors ◽

Two Phase ◽

Noise Factors

A controller synthesis algorithm is developed in this paper. The algorithm employs the genetic algorithm for parameter optimization and Taguchi method for the planning of trails in applying the genetic algorithms. The resulting two-phase algorithm explores the orthogonal array in Taguchi method to conduct a series of experiments so that key parameters pertaining to the control factors, noise factors, and quality factors can be determined. In the first phase, a matrix-type experiment is conducted to determine the configuration for parameter optimization. The second phase then applies parameter optimization method to determine the controller parameter that leads to robust performance. The combined two-phase approach is effective and efficient in controller synthesis. The proposed algorithm is applied to a control-design benchmark problem. The resulting design is shown to have a superior performance to other existing controllers.

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Safety and Reliability of Wireless Charging System for Electric Vehicles Based on the Yunnan Power Grid

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.518.324 ◽

2014 ◽

Vol 518 ◽

pp. 324-328 ◽

Cited By ~ 1

Author(s):

Hong Liang Wang ◽

Juan Liu ◽

Min Cao ◽

Xian Fu Chen ◽

Da Da Wang ◽

...

Keyword(s):

Electric Vehicles ◽

Large Scale ◽

Power Transmission ◽

Power Grid ◽

Wireless Charging ◽

Wireless Power ◽

Gradual Improvement ◽

Electric Cars ◽

Huge Impact ◽

Battery Technology

Electric cars are emerged as the energy crisis and environmental problems have become more severe. Electric vehicles charging include contact and non-contact. The battery technology has not been solved absolutely for Contactless charging, in addition, charging pile construction will take up a lot of urban land, normal charge is slow, fast charge will have a huge impact to grid, the high cost of change the batteries, these drawbacks of electric vehicles has been hampered the large-scale development of EV. With the development and gradual improvement of wireless power transmission technology .wireless charging technology applied to electric vehicles has great prospects. In the wireless power charging process safe, reliable transmission is very important. In this paper, security and reliability problems have been discussed for the various aspects of wireless charging systems and combined analysis of the characteristics of Yunnan Power Grid for wireless charging systems of electric vehicles.

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Study on Global Parameters Optimization of Dual-Drive Powertrain System of Pure Electric Vehicle Based on Multiple Condition Computer Simulation

Complexity ◽

10.1155/2020/6057870 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yong Wang ◽

Hongguo Cai ◽

Yinghua Liao ◽

Jun Gao

Keyword(s):

Computer Simulation ◽

Electric Vehicles ◽

Power Transmission ◽

Dynamic Performance ◽

Optimization Method ◽

Transmission System ◽

Vehicle Dynamic ◽

Transmission Scheme ◽

Electric Transmission ◽

Powertrain System

Equipped with two power sources, the dual-driving powertrain system for pure electric vehicles has a driving mode different from traditional electric vehicles. Under the premise that the structural form of the transmission system remains unchanged, the following transmission schemes can be adopted for double drive electric vehicles according to the demand power: the main and auxiliary electric transmission scheme (two motors are driven separately with dual-motor coupling drive), the transmission scheme in which the two motors always maintain coupling drive, and the speed-regulating type electric transmission scheme (the main motor is always responsible for driving, and the auxiliary motor is responsible for speed regulation). Therefore, a significant difference exists in the design methods of the power transmission system of double drive electric vehicles and existing vehicles. As for such differences, this paper adopts intelligent algorithm to design the parameters of the transmission system and introduces the genetic algorithm into the optimization design of parameters to obtain the optimal vital parameters of the power transmission system based on computer simulation. The prototype car used in this paper is a self-owned brand car; MATLAB/Simulink platform is used to build the vehicle simulation model, which is used for the computer simulation analysis of the vehicle dynamic performance and economy. It can be seen from the analysis result that the system parameters obtained by using the global optimization method proposed in this study can improve the vehicle dynamic performance and economic performance to varying degrees, which proves the efficiency and feasibility of the optimization method.

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Optimal Day-Time Charging Strategies for Electric Vehicles considering Photovoltaic Power System and Distribution Grid Constraints

Mathematical Problems in Engineering ◽

10.1155/2015/765362 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Weige Zhang ◽

Wenjie Ge ◽

Mei Huang ◽

Jiuchun Jiang

Keyword(s):

Electric Vehicles ◽

Optimization Method ◽

Programming Algorithm ◽

Distribution Grid ◽

Pv System ◽

Load Curve ◽

Electricity Cost ◽

Photovoltaic Power ◽

Coordinated Charging ◽

Charging Stations

Electric vehicles (EVs) charging stations with a photovoltaic (PV) system for day-time charging have been studied. This paper investigates the issues such as how to coordinate the EVs customers for coordinated charging, maximize photovoltaic utilization, and reduce customers cost of EVs charging and operator electricity. Firstly, an ideal charging load curve was built through using the linear programming algorithm. This optimal curve, which realized maximum photovoltaic power and minimum electricity cost, was used as the objective curve. Secondly, a customer response model was utilized, to propose an optimization method and strategy for charging service tariffs. Particle swarm optimization algorithm was used for time-of-use tariffs and peak-flat-valley time division so that the charging load after price regulation was adjusted to best fit the objective curve, and both the EVs customers and the operator benefit from this. Finally, the proposed model and method have been verified by two cases.

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Collaborative Optimization Method of Power and Efficiency for LCC-S Wireless Power Transmission System

Electronics ◽

10.3390/electronics10243088 ◽

2021 ◽

Vol 10 (24) ◽

pp. 3088

Author(s):

Ming Xue ◽

Qingxin Yang ◽

Chunzhi Li ◽

Pengcheng Zhang ◽

Shuting Ma ◽

...

Keyword(s):

Electric Vehicles ◽

Power Transmission ◽

Optimization Method ◽

Collaborative Optimization ◽

Wireless Power ◽

Environmental Disturbances ◽

Power Adjustment ◽

Optimal Load ◽

Optimal Efficiency ◽

Equivalent Load

Dynamic wireless charging enables moving equipment such as electric vehicles, robots to be charged in motion, and thus is a research hotspot. The applications in practice, however, suffer from mutual inductance fluctuation due to unavoidable environmental disturbances. In addition, the load also changes during operation, which makes the problem more complicated. This paper analyzes the impacts of equivalent load and mutual inductances variation over the system by LCC-S topology modeling utilizing two-port theory. The optimal load expression is derived. Moreover, a double-sided control strategy enabling optimal efficiency and power adjustment is proposed. Voltage conducting angles on the inverter and rectifier are introduced. The simulation and experimental results verify the proposed method.

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Customer-Oriented Vehicle Routing Problem with Environment Consideration: Two-Phase Optimization Approach and Heuristic Solution

Mathematical Problems in Engineering ◽

10.1155/2019/1073609 ◽

2019 ◽

Vol 2019 ◽

pp. 1-19

Author(s):

Fanting Meng ◽

Yong Ding ◽

Wenjie Li ◽

Rongge Guo

Keyword(s):

Vehicle Routing ◽

Fuel Consumption ◽

Vehicle Routing Problem ◽

Optimization Method ◽

Second Phase ◽

Optimization Approach ◽

Two Phase ◽

Routing Problem ◽

Problem Model ◽

Phase Optimization

With the fastest consumer demand growth, the increasing customer’s demands trend to multivarieties and small-batch and the customer requires an efficient distribution planning. How to plan the vehicle route to meet customer satisfaction of mass distribution as well as reduce the fuel consumption and emission has become a hot topic. This paper proposes a two-phase optimization method to handle the vehicle routing problem, considering the customer demands and time windows coupled with multivehicles. The first phase of the optimization method provides a fuzzy hierarchical clustering method for customer grouping. The second phase formulates the optimization en-group vehicle routing problem model and a genetic algorithm to account for vehicle routing optimization within each group so that fuel consumption and emissions are minimized. Finally, we provide some numerical examples. Results show that the two-phase optimization method and the designed algorithm are efficient.

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Security Margin Assessment Method of Centralized Spot Market Based on Information Entropy

E3S Web of Conferences ◽

10.1051/e3sconf/202127501059 ◽

2021 ◽

Vol 275 ◽

pp. 01059

Author(s):

Yue Leng ◽

Lili Li ◽

Feng Zhang ◽

Ziqing Zhou ◽

Zhiqi Wang ◽

...

Keyword(s):

Information Entropy ◽

Power Flow ◽

Power Transmission ◽

Power Grid ◽

Spot Market ◽

Assessment Method ◽

Economic Benefits ◽

Margin Assessment ◽

Operation Condition ◽

Flow Transfer

In the centralized spot market, each participant pursues the maximization of economic benefits, which leads to the operation condition of the power grid closer to the security boundary. Thus, in this paper, a novel approach to security margin assessment of the centralized spot market is proposed. By proceeding from the mechanism of influence of load variation on power flow, the relationship between power flow transfer characteristics and the security margin of the power grid is explored. Then, on the basis of information entropy theory, the power flow transfer balancing evaluation index of the power grid is established. And this index is applied for security margin assessment of the power grid in the environment of the centralized spot market. Results of an IEEE 14-bus system case study have validated the effectiveness and quickness of the proposed method. Meanwhile, in accordance with the analysis results, it is proved that the proposed method is capable of accurately identifying the critical power transmission and transformation equipment affecting the security margin of the power grid, which is helpful to identify the potential risks of the operation of the power grid in advance.

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Prioritized optimization by Nash games : towards an adaptive multi-objective strategy

ESAIM Proceedings and Surveys ◽

10.1051/proc/202171106 ◽

2021 ◽

Vol 71 ◽

pp. 54-63

Author(s):

Jean-Antoine Désidéri ◽

Régis Duvigneau

Keyword(s):

Optimal Solution ◽

Optimization Method ◽

Cost Functions ◽

Second Phase ◽

Two Phase ◽

Nash Games ◽

Multi Objective ◽

Business Jet ◽

Decreasing Functions

This work is part of the development of a two-phase multi-objective differentiable optimization method. The first phase is classical: it corresponds to the optimization of a set of primary cost functions, subject to nonlinear equality constraints, and it yields at least one known Pareto-optimal solution xA*. This study focuses on the second phase, which is introduced to permit to reduce another set of cost functions, considered as secondary, by the determination of a continuum of Nash equilibria, {x̅ε} (ε≥ 0), in a way such that: firstly, x̅0=xA* (compatibility), and secondly, for ε sufficiently small, the Pareto-optimality condition of the primary cost functions remains O(ε2), whereas the secondary cost functions are linearly decreasing functions of ε. The theoretical results are recalled and the method is applied numerically to a Super-Sonic Business Jet (SSBJ) sizing problem to optimize the flight performance.

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Multiobjective Optimization regarding Vehicles and Power Grids

Wireless Communications and Mobile Computing ◽

10.1155/2021/5552626 ◽

2021 ◽

Vol 2021 ◽

pp. 1-6

Author(s):

Kaiyang Zhong ◽

Ping Wang ◽

Jiaming Pei ◽

Jiyuan Xu ◽

Zonglin Han ◽

...

Keyword(s):

Multiobjective Optimization ◽

Electric Vehicles ◽

Power Grid ◽

Real Life ◽

Optimization Method ◽

Power Grids ◽

Load Curve ◽

Before And After ◽

Grid Operators ◽

The Impact

Vehicle to Grid (V2G) refers to the optimal management of the charging and discharging behavior of electric vehicles through reasonable strategies and advanced communication. In the process of interaction, there are three stakeholders: the power grid, operators (charging stations), and EV users. In real life, the impact of peak-valley difference caused a lot of power loss when charging. At the same time, the loss of current is also a loss for power grid companies and EV users. In this paper, we propose a multiobjective optimization method to reduce the current loss and determine the relationship between the parameters and the objective function and constraints. This optimization method uses a genetic algorithm for multiobjective optimization. Through the analysis of the number of vehicles and load curve of AC class I and AC class II electric vehicles before and after optimization in each period, we found that the charging load of electric vehicles played a role of valley filling in the low valley price stage and played a peak-cutting role in a peak price period.

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