Impact Of Market Penetration Research Articles

Modeling and Analysis of Driving Behaviour for Heterogeneous Traffic Flow Considering Market Penetration under Capacity Constraints

Based on analytical and simulation methods, this paper discusses the path choice behavior of mixed traffic flow with autonomous vehicles, advanced traveler information systems (ATIS) vehicles and ordinary vehicles, aiming to promote the development of autonomous vehicles. Firstly, a bi-level programming model of mixed traffic flow assignments constrained by link capacity is established to minimize travel time. Subsequently, the algorithm based on the incremental allocation method and method of successive averages is proposed to solve the model. Through a numerical example, the road network capacity under different modes is obtained, the impact of market penetration on travel time is analyzed, and the state and characteristics of single equilibrium flow and mixed equilibrium flow are explored. Analysis results show that the road network can be maximized based on saving travel time when all vehicles are autonomous, especially when the autonomous lane is adopted. The travel time can be shortened by increasing the market penetration of autonomous vehicles and ATIS vehicles, while the former is more effective. However, the popularization of autonomous vehicles cannot be realized in the short term; the market penetration of autonomous vehicles and ATIS vehicles can be set to 0.2 and 0.6, respectively, during the introduction period.

Electric Vehicle Cost in 2035: The impact of market penetration and charging strategies

This paper analyzes charging cost of battery electric vehicles (BEVs) for different penetration levels of BEVs and for different charging strategies by taking into account their impact on the electricity sector. We analyze a multi-level equilibrium model, which incorporates endogenous generation capacity investment, network expansion, and congestion management. We calibrate our model for the German electricity sector in 2035 and consider different degrees of BEV penetration and various charging strategies: (i) non-smart charging based on a standard charging profile, (ii) smart charging, where the charging load can be shifted throughout the entire day to provide flexibility to the system, and (iii) a mixed charging strategy, where smart charging is only possible during night hours. Our final results reveal that larger BEV penetration yields lower CO2 emissions even in those scenarios with smaller availability of green electricity production. Furthermore, both charging cost and resulting CO2 emissions are substantially reduced for smarter charging strategies for all scenarios considered. Finally, even for scale deployment of BEVs, charging cost remains comparatively low. The Total Cost of Ownership (TCO) of BEV adoption thus continues to crucially depend on the evolution of vehicle purchase prices.

Routing of autonomous vehicles for system optimal flows and average travel time equilibrium over time

We envisage a transportation management center (TMC) for future autonomous vehicles that distributes the traffic over a cycle comprising many days in such a manner that the average travel time (AVT) of vehicles of the same origin–destination (OD) over the cycle is identical at equilibrium while the entire network achieves system optimal (SO) flows every day. Vehicles are assigned to a set of paths, with different proportions of time within the cycle on different paths, but with the same AVT over the cycle at equilibrium. Since AVT is the same for each user, it is inherently fair to every-one. Thus, not only do users gain by subscribing to this system but the overall system also, as SO flows are followed each day. We then model the case of mixed equilibrium (ME), wherein drivers are given the option to subscribe to the TMC path combinations and hence assist in achieving SO, while non-subscribers only minimize their own private costs and follow their user equilibrium (UE) paths, which typically have shorter times than the corresponding AVT. To counter this, a tolling scheme is imposed on non-subscribers, i.e., UE users, based on their value-of-time (VOT) distribution and the travel time difference between subscribers' AVT and non-subscribers' UE time at ME. In the end, the total cost of travel of non-subscribers, toll plus UE time, is equal to the corresponding AVT of subscribers. The efficiency of this system is shown through numerical studies. Finally, the impact of market penetration and different VOT distributions on AVT and toll are investigated through sensitivity analysis.

Electric vehicle adoption in a market environment in 2035: The impact of market penetration and charging strategies

This paper analyzes the profitability for adopting battery electric vehicles (BEVs) in the year 2035 accounting for different charging options and their feedback on the electricity sector. We propose a multi-level equilibrium model for the electricity market to determine charging costs, which incorporates endogenous determination of generation capacity investment, network expansion and redispatch, including demand for large-scale deployment of BEV mobility. The model allows to investigate the impact of BEV mobility and different charging options on the electricity system and its endogenous feedback on charging prices. For different degrees of BEV penetration, we calibrate our model for the German electricity market in 2035 and consider various charging options: (i) non-smart charging based on a standard charging profile, (ii) smart charging, where the charging load can be shifted throughout the entire day to provide flexibility to the system and (iii) a mixed charging strategy, where smart charging is only possible during night hours. We then analyze the impact of those charging strategies on charging and electricity prices, generation and transmission investment, RES curtailment, CO2 emissions and total system cost. In a next step, those endogenously determined charging prices are incorporated in a total cost of ownership analysis to investigate BEV profitability. Our results reveal that larger BEV penetration yields lower CO2 emissions even in those scenarios with smaller availability of green electricity production. Charging prices and resulting CO2 emission substantially depend on the chosen charging strategy. Even for large-scale deployment of BEV, however, electricity prices will remain comparatively low and thus charging prices in all considered scenarios account only for a small fraction of total vehicle cost. Thus, the profitability of adopting an electric vehicle crucially depends on the initial investment cost and potentially granted public support schemes.

Active demand response with electric heating systems: Impact of market penetration

Active demand response (ADR) is a powerful instrument among electric demand side management strategies to influence the customers’ load shape. Assessing the real potential of ADR programmes in improving the performance of the electric power system is a complex task, due to the strict interaction between supply and demand for electricity, which requires integrated modelling tools. In this paper an analysis is performed aimed at evaluating the benefits of ADR programmes in terms of electricity consumption and operational costs, both from the final user’s and the overall system’s perspective. The demand side technologies considered are electric heating systems (i.e. heat pumps and electric resistance heaters) coupled with thermal energy storage (i.e. the thermal mass of the building envelope and the domestic hot water tank). In particular, the effect of the penetration rate of ADR programmes among consumers with electric heating systems is studied. Results clearly show that increasing the number of participating consumers increases the flexibility of the system and, therefore, reduces the overall operational costs. On the other hand, the benefit per individual participant decreases in the presence of more ADR-adherent consumers since a reduced effort from each consumer is needed. Total cost saving ranges at most between about 400€ and 200€ per participant per year for a 5% and 100% ADR penetration rate respectively.