Contribution of Real-Time Pricing to Impacts of Electric Cars on Distribution Network

Skolthanarat, Siriya; Somsiri, P.; Tungpimolrut, Kanokvate

doi:10.1109/ias.2019.8912317

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…However, the utility parameter for each consumer may be private, potentially rendering the method challenging to apply in practical situations. Reference [21] investigated the contribution of real-time pricing to the effects of charging electric cars but failed to investigate the impacts of load demand with high price elasticity.…”

Section: S Dmaxmentioning

confidence: 99%

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Wang,

Yu,

2024

ENERGY

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Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users, the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies. For this purpose, a power grid-flexible load bilevel model is constructed based on dynamic pricing, where the leader is the dispatching center and the lower-level flexible load acts as the follower. Initially, an upper-level day-ahead dispatching model for the power grid is established, considering the lowest power grid dispatching cost as the objective function and incorporating the power gridside constraints. Then, the lower level comprehensively considers the load characteristics of industrial load, energy storage, and data centers, and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function. Finally, the proposed method is validated using the IEEE-118 system, and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively, thereby reducing the peak-valley difference and decreasing users' purchasing costs. KEYWORDSDemand response; fixed time-of-use electricity price mechanism; dynamic price incentives mechanism; bi-level model; flexible loadThe active generation of generator v at time t P ij.tThe transmission capacity of the line between node i and j θ i.t , θ j.tVoltage angle of node i and j at time t dP N d,t The variation of load d responds to demand response at time t C N d,t The unit electricity consumption cost of load d at time t λ in d,tThe interactive data allocated to data center d at time t λ de d,tThe batch processing data allocated to data center d at time t S d,tThe data storage capacity of the data center d at time t S de,opl d,t The total batch processing data processed by data center d at time t P Q d,t Refrigerating active power of data center d at time t P IT d.t IT power consumption of data centers d at time t P N d.tThe consumption of electricity demand d at time t

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Section: S Dmaxmentioning

confidence: 99%

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Wang,

Yu,

2024

ENERGY

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“…Another study presented in [12] compares three approaches (heuristic, optimization, and stochastic programming) used to schedule under uncertainty the charging process of three different electric vehicles' fleets at a common charging infrastructure. Dynamic price signals are developed in [13] to implement demandside management, and alleviate the stress of concurrent charging on the distribution network. A statistical demand-price model with its application in optimal real-time price is presented in [14], and a similar work is proposed in [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Behavioural Change in Green Transportation: Micro-Economics Perspectives and Optimization Strategies

Bordin

Tomasgård

2021

Energies

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The increasing demand for Electric Vehicle (EV) charging is putting pressure on the power grids and capacities of charging stations. This work focuses on how to use indirect control through price signals to level out the load curve in order to avoid the power consumption from exceeding these capacities. We propose mathematical programming models for the indirect control of EV charging that aim at finding an optimal set of price signals to be sent to the drivers based on price elasticities. The objective is to satisfy the demand for a given price structure, or minimize the curtailment of loads, when there is a shortage of capacity. The key contribution is the use of elasticity matrices through which it is possible to estimate the EV drivers’ reactions to the price signals. As real-world data on relating the elasticity values to the EV driver’s behaviour are currently non-existent, we concentrate on sensitivity analysis to test how different assumptions on elasticities affect the optimal price structure. In particular, we study how market segments of drivers with different elasticities may affect the ability of the operator to both handle a capacity problem and properly satisfy the charging needs.

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“…In this sense, the DSR program can utilize a real-time pricing scheme, leading to a suitable option to alleviate network congestion when customers are encouraged to shift their charging process to off-peak periods. Compared with other price-based DSR programs, i.e., time of use, critical peak pricing, and peak time rebate, the real-time pricing scheme represents a more appropriate alternative for bill savings and dampening energy price volatility [108].…”

Section: Subperiod 2019mentioning

confidence: 99%

A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems

2020

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In the last decade, the deployment of electric vehicles (EVs) has been largely promoted. This development has increased challenges in the power systems in the context of planning and operation due to the massive amount of recharge needed for EVs. Furthermore, EVs may also offer new opportunities and can be used to support the grid to provide auxiliary services. In this regard, and considering the research around EVs and power grids, this paper presents a chronological background review of EVs and their interactions with power systems, particularly electric distribution networks, considering publications from the IEEE Xplore database. The review is extended from 1973 to 2019 and is developed via systematic classification using key categories that describe the types of interactions between EVs and power grids. These interactions are in the framework of the power quality, study of scenarios, electricity markets, demand response, demand management, power system stability, Vehicle-to-Grid (V2G) concept, and optimal location of battery swap and charging stations.

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Contribution of Real-Time Pricing to Impacts of Electric Cars on Distribution Network

Cited by 6 publications

References 4 publications

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Behavioural Change in Green Transportation: Micro-Economics Perspectives and Optimization Strategies

A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems

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