The Effect of Ratio-Based Incentive on Wind Capacity Development and Investment Risk of Wind Units: A System Dynamics Approach

Esmaeili, Mohammad; Anvari‐Moghaddam, Amjad

doi:10.1109/access.2021.3103283

Cited by 5 publications

(14 citation statements)

References 40 publications

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“…1. The details of two inner negative loops (loops 1 and 2) in the market can be found in [10] and [22]. Loops 1 and 2 show the price elasticity of demand and the price elasticity of conventional units' generation, respectively.…”

Section: General Aspects Of the Modelmentioning

confidence: 99%

“…Green arrows form the third negative loop and pink arrows construct the fourth one. The investments in new wind farms and fossil fuel power plants are balanced through the third and the fourth loops, respectively [22]. In order to show the causal loop diagram of the transportation system and complete the proposed models of [10] and [22], a positive loop is added.…”

Section: General Aspects Of the Modelmentioning

confidence: 99%

“…In this paper, it is a random variable so the normal distribution function with the standard deviation equal to 0.01 and expected value equal to 0.011 shows its random behavior [30]. Therefore, the weekly demand is determined from (7) [22].…”

Section: B Electricity Demandmentioning

confidence: 99%

“…It is assumed that consumers can modify their demand proportional to the long-term price signals that they receive. Such assumption can be modeled by ( 8) [22].…”

Section: B Electricity Demandmentioning

confidence: 99%

“…• A dynamic model is designed to model the purchasing behavior of PEV drivers as well as the behavior of companies in the investment in DC charging infrastructures. Then, this model is combined with the proposed dynamic model of the electricity market in [22] to achieve a comprehensive model to study the behavior of the coupled electricity market and electrified transportation system. Such models draw a better picture of the whole system for policymakers and help them provide planning strategies and policies effectively.…”

Section: Introductionmentioning

confidence: 99%

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On the Role of Renewable Energy Policies and Electric Vehicle Deployment Incentives for a Greener Sector Coupling

et al. 2022

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Various incentives are introduced for the expansion of electric vehicle fleets and electricity generation from renewable energy resources. Although many researchers studied the effect of these policies on the related sector, there is no study investigating the indirect effect of renewable energy incentives on the deployment of electric vehicles or the indirect effect of electric vehicle adoption policies on the long-term integration of renewable energy resources. The main contribution of this paper is to analyze the impact of the specific incentives on both deployment of electric vehicles in the transportation system and investment in capacity generation in the electricity market. For this purpose, a new framework was designed to analyze the effect of policies on the electric vehicle deployment and development of DC charging stations based on the system dynamics approach. Then, this framework was combined with the existing dynamic models of the electricity market to study the interaction and behavior of both coupled systems from the policymakers' perspective. The effect of policies implementation was interpreted in a mathematical framework and the Net Present Value method was used for assessing the investment in charging infrastructures. Simulation results of a case study in the United States and sensitivity analysis illustrate that increasing the wind capacity incentives accelerated the electrification of the transportation system and increasing the incentives for electrification of transportation system influences wind capacity positively. Moreover, the sensitivity of the electric vehicle adoption to gas price is more than the sensitivity of the wind capac ity penetration to gas price. INDEX TERMSDC charging stations, Electricity market, Electric vehicles deployment policies, Plug-in electric vehicles, Renewable capacity incentive, System dynamics, Wind capacity investment. NOMENCLATURE Abbreviations ESS Energy storage system RES Renewable energy source PEV Plug-in electric vehicle EVSE Electric vehicle supply equipment HC Hard coal units CCGT Combined cycle gas turbines GT Gas turbines NPV Net Present Value Variables DUCH Number of PEVs that are supplied in DC charging station d Time step (day) TNPEV Total number of plug-in electric vehicles

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Section: General Aspects Of the Modelmentioning

confidence: 99%

Section: General Aspects Of the Modelmentioning

confidence: 99%

Section: B Electricity Demandmentioning

confidence: 99%

“…It is assumed that consumers can modify their demand proportional to the long-term price signals that they receive. Such assumption can be modeled by ( 8) [22].…”

Section: B Electricity Demandmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations