The parametric analysis of the electric vehicles and vehicle to grid system's role in flattening the power demand

Although the deployment of electric vehicles (EVs) increases the power demand, implementing the vehicle to grid technology (V2G) can decrease the power issues and improve the efficiency of the network. A transition to the V2G system enables EVs to flatten the load profile by shaving the peak demand and filling the valley demand by utilizing the unused/extra stored power in batteries to support the grid. Many authors have focused on shaving the peak demand with different methods like energy storage system (ESS) and demand-side management (DSM) and utilized various algorithms to assess the impacts of EVs and V2G system on shaving the peak demand. In most of these papers, only limited aspects of the implementation of V2G and its impacts on peak demand have been analyzed. In this paper, we propose a novel methodology to comprehensively evaluate the role of the EVs and V2G on shaving the peak demand and filling the valley demand under different parameters such as penetration level of EVs and V2G, charging mode, charging location, and schedule of charging. Monte Carlo simulation is utilized to analyze the influences of parameters on the power demand profile. The results indicate that un-controlled charging intensifies the peak demand up to 5% more than off-peak scenarios that negatively affect the grid's reliability. Among analyzed cases, integrating the EVs and V2G system under off-peak charging has better consequences in shaving the peak and filling the valley demand. The off-peak mode can level the load curve where the peak demand is decreased around 2%, and the valley demand is increased around 3%. Based on the outputs of the simulation, encouraging the EVs’ owners to charge their electric batteries at late night or early morning would be the best policy to improve the power grid's performance. Charging at home would be a better option for leveling the load profile among all charging stations. Moreover, analysis indicates that there is a need for policies to regulate the schedule of charging at public stations. © 2022 Elsevier Lt

Using malmquist TFP index for evaluating agricultural productivity: Agriculture of Türkiye NUTS2 regions

Agriculture is one of the main economic sectors in Türkiye. Therefore, a performance evaluation is essential for an improvement in agricultural sector. In this study, the productivity of Turkish agricultural sector was analyzed for the years between 2006-2015. A non-parametric technique, Data Envelopment Analysis (DEA) based Malmquist index method, was applied to calculate the Total Factor Productivity (TFP) indices for agriculture in 26 NUTS2 (The Nomenclature of Territorial Units for Statistics) regions of Türkiye for the selected 10-year period. Total agricultural production value is used as the output variable and six input variables are selected as: land, labor, machine, livestock and government investment. The analysis was conducted via the computer program DEAP2.1. The result reveals that agricultural TFP of regions has decreased by 2% annually on average. The maximum TFP growth in agriculture occurred between 2007 and 2008 with a mean increase of 12% in overall TFP of regions. On the other hand, the greatest regression in the overall TFP was observed in 2010-2011 period by a decrease of 13%

A Methodology for Explicit Representation of the Stochastic Demand due to Electric_x000D_ Vehicles in Generation Expansion Planning Problems

Generation expansion planning (GEP) problems are solved to find the optimum investment decisions to satisfy the increasing_x000D_ electricity demand. Integration of electric vehicles (EVs) with the capability of charging from the grid will also increase the_x000D_ electricity demand of the grid. Depending on the charging/driving characteristics of users, demand curves for EVs will be shaped_x000D_ and it will be different on each day. Therefore, it is very crucial to represent this stochastic nature of EVs demand in the associated_x000D_ GEP problems. This paper is proposing a methodology to represent EVs demand realistically on GEP models. The proposed_x000D_ methodology starts with generating random demand patterns to demonstrate possibilities for the EVs demand patterns via Monte_x000D_ Carlo Simulation, then using an optimization-based model to select a representative set. Two stage stochastic programming_x000D_ model is proposed for GEP problems and solved to minimize the expected cost over the entire set, the representative set and the_x000D_ average EVs demand. The results show that GEP models with selected demand curves produce more realistic decisions (closer_x000D_ to the solutions obtained by using the entire demand patterns) than the decisions obtained by the models with average EVs_x000D_ demand. In most cases, the models using average EVs demand fail to capture the new peaks generated by EVs, therefore, they_x000D_ suggest less capacity expansion then the required amount. This results in more unmet demand in the system

Influences of vehicle to grid (V2G) on power grid: An analysis by considering associated stochastic parameters explicitly

Integration of the electric vehicles (EVs) and vehicle-to-grid (V2G) technology with renewable energy sources (RESs) is the hottest topics among researchers. Many studies have been done in this field, but in most of them, discussion of aspects of electrified transportation have been limited. The V2G system due to its structure and supporting role for the grid influences the power demand and supply curve simultaneously depending on the patterns of driving, preferences for charging/discharging times, location, and the infrastructure of the system. Due to complexity of this system, it is necessary to cover all the influential elements in one package and analyze the impact of the system on them in a unique process. In this paper, we apply a precise and efficient methodology to analyze the impacts of the EVs and V2G on reliability, cost, and emissions with respect to the power grid. The strength of this paper is the applicability of the suggested methodology to the power grids with different patterns and features with respect to shares of RESs generated power by explicitly considering the stochastic parameters shaping the daily demand/supply curves. We introduce two novel indexes for measuring the reliability of the power grid based on availability of the RESs under power supply systems: stochastic and constant power supply. To cover all the possibilities, based on different penetration levels of EVs and V2G, charging modes, locations and schedules several cases are defined and for each case, the Monte Carlo simulation is used to evaluate the impacts of the considered cases regarding the reliability, emission, and cost of the power grid. In the numerical analysis under assumed cases, results show integration of the EVs and V2G system in stochastic power supply (high RESs) improves the power grid's efficiency in terms of decreasing the total cost and emission rate. The intermittent nature of RESs can increase fluctuation in the power grid and consequently negatively affect the reliability of the system but our analysis indicates that integration of these sources with V2G system can improve the reliability of the power grid. (c) 2020 Elsevier Ltd. All rights reserved

A comprehensive analysis of Vehicle to Grid (V2G) systems and scholarly literature on the application of such

Without any doubt, the environmental issues are the top worries between all the nations in the current century. According to the recent studies, the researchers have shown that the transportation fleet is one of the biggest sources of emission. The penetrating the renewable energy sources (RESs) and electric vehicles (EVs) are the green solutions to decrease the current environmental issues. Due to intermittent nature of RESs and high investment costs of developing EVs' infrastructure, tendency for using them is under the predicted estimations. In this paper, by analyzing a precise and comprehensive literature review, we consider all aspects of implementing the EVs especially their supporting roles for the grid in vehicle to grid system (V2G). Moreover, we study the integration of the electrified fleet with RESs in smart grid and evaluate their possible impacts on the power network. In addition, we count the advantages and disadvantages of implementing the V2G system on the power network. The main purpose of this paper is analyzing the influences of the V2G system on the power grid in four main subjects and classifying them based on their proposed methodology for the future studies. However there are some review papers related to this topic, this field of study suffers a lack of clear direction for future studies and researchers and also a comprehensive analysis about the V2G-related articles is still missing. Finally, an analysis and survey of the last two decades of scholarly literature and projects in this field of study from 2004 to March 2019 is presented. The results show that a limited number of articles have conducted to investigate the social aspects of implementation of V2G system. In addition, however, there are many researches about integration of the V2G system with RESs and smart grid; a few of them use the real data for estimating the availability of RESs in each hour of day

Profiling energy efficiency tendency:a case for Turkish households

There is no need to discuss the importance of energy and energy policies in the global agenda. Countries whose electricity demand rises steadily, and depends heavily on fossil fuels and imports, should consider energy efficiency in any aspects. As one of examples such a country, this study investigates the behaviors and attitudes of Turkish households regarding energy efficiency. An online survey of 526 Turkish households in 2014 gathered data on current habits including peak hour use, energy labeling, standby use, willingness for behavioral change, and policy options they would like to see implemented to improve energy efficiency. The results indicate the awareness level of energy efficiency among Turkish households is quite low, and should be promoted by demand side programs. Two-step cluster analysis is used to construct clusters to group households with respect to their policy preferences. Four different clusters are identified and characteristics of these clusters suggest the importance of having unique intervention strategies for successful behavioral change and for the attainment of energy efficiency

Profiling energy efficiency tendency:a case for Turkish households

There is no need to discuss the importance of energy and energy policies in the global agenda. Countries whose electricity demand rises steadily, and depends heavily on fossil fuels and imports, should consider energy efficiency in any aspects. As one of examples such a country, this study investigates the behaviors and attitudes of Turkish households regarding energy efficiency. An online survey of 526 Turkish households in 2014 gathered data on current habits including peak hour use, energy labeling, standby use, willingness for behavioral change, and policy options they would like to see implemented to improve energy efficiency. The results indicate the awareness level of energy efficiency among Turkish households is quite low, and should be promoted by demand side programs. Two-step cluster analysis is used to construct clusters to group households with respect to their policy preferences. Four different clusters are identified and characteristics of these clusters suggest the importance of having unique intervention strategies for successful behavioral change and for the attainment of energy efficiency

Optimization of lte radio resource block allocation for maritime channels

In this study, we describe the behavior of LTE over the sea and investigate the problem of radio resource block allocation in such SINR limited maritime channels. For simulations of such sea environment, we considered a network scenario of Bosphorus Strait in Istanbul, Turkey with different number of ships ferrying between two ports at a given time. After exploiting the network characteristics, we formulated and solved the radio resource allocation problem by max-min integer linear programming method. The radio resource allocation fairness in terms of Jain's fairness index was computed and it was compared with round robin and opportunistic methods. Results show that the max-min optimization method performs better than the opportunistic and round robin methods. This result in turn reflects that the max-min optimization method gives us the high minimum best throughput as compared to other two methods considering different ship density scenarios in the sea. Also, it was observed that as the number of ships begin to increase in the sea, the max-min method performs significantly better with good fairness as compared to the other two methods

Mean-risk stochastic electricity generation expansion planning problems with demand uncertainties considering conditional-value-at-risk and maximum regret as risk measures

This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people’s living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered