Bilevel Model for Retail Electricity Pricing

2017 ◽  
pp. 675-681
Author(s):  
Georgia E. Asimakopoulou ◽  
Andreas G. Vlachos ◽  
Nikos D. Hatziargyriou
Keyword(s):  
Electricity Pricing

Predicting Baseline for Analysis of Electricity Pricing

2016 ◽  
Author(s):  
T. Kim ◽  
D. Lee ◽  
J. Choi ◽  
A. Spurlock ◽  
A. Sim ◽  
...  
Keyword(s):  
Electricity Pricing

Energy consumption characteristics and adaptive electricity pricing strategies for college dormitories based on historical monitored data

2021 ◽  
pp. 111041
Author(s):  
Yunchun Yang ◽  
Jiaqi Yuan ◽  
Ziwei Xiao ◽  
Hao Yi ◽  
Chong Zhang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Pricing Strategies ◽  
Electricity Pricing

Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components

2021 ◽  
Vol 95 ◽  
pp. 105110
Author(s):  
Filippos Ioannidis ◽  
Kyriaki Kosmidou ◽  
Christos Savva ◽  
Panayiotis Theodossiou
Keyword(s):  
Garch Model ◽  
Electricity Pricing ◽  
Skewness And Kurtosis

scholarly journals Financial Impacts of Net-Metered Distributed PV on a Prototypical Western Utility’s Shareholders and Ratepayers

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4794 ◽  
Author(s):  
Peter Cappers ◽  
Andrew Satchwell ◽  
Will Gorman ◽  
Javier Reneses
Keyword(s):  
Capital Investment ◽  
Operating Conditions ◽  
Net Energy ◽  
Electricity Pricing ◽  
Operating Characteristics ◽  
Financial Model ◽  
Energy Metering ◽  
Percentage Basis ◽  
Financial Impacts ◽  
Net Energy Metering

Distributed solar photovoltaic (DPV) under net-energy metering with volumetric retail electricity pricing has raised concerns among utilities and regulators about adverse financial impacts for shareholders and ratepayers. Using a pro forma financial model, we estimate the financial impacts of different DPV deployment levels on a prototypical Western U.S. investor-owned utility under a varied set of operating conditions that would be expected to affect the value of DPV. Our results show that the financial impacts on shareholders and ratepayers increase as the level of DPV deployment increases, though the magnitude is small even at high DPV penetration levels. Even rather dramatic changes in DPV value result in modest changes to shareholder and ratepayer impacts, but the impacts on the former are greater than the latter (in percentage terms). The range of financial impacts are driven by differences in the amount of incremental capital investment that is deferred, as well as the amount of incremental distribution operating expenses that are incurred. While many of the impacts appear relatively small (on a percentage basis), they demonstrate how the magnitude of impacts depend critically on utility physical, financial, and operating characteristics.

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

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.

A game-theoretic approach for optimal time-of-use electricity pricing

2013 ◽  
Vol 28 (2) ◽  
pp. 884-892 ◽  
Author(s):  
Peng Yang ◽  
Gongguo Tang ◽  
Arye Nehorai
Keyword(s):  
Optimal Time ◽  
Theoretic Approach ◽  
Electricity Pricing ◽  
Game Theoretic ◽  
Game Theoretic Approach

scholarly journals A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles

2008 ◽  
Author(s):  
Scott J. Moura ◽  
Hosam K. Fathy ◽  
Duncan S. Callaway ◽  
Jeffrey L. Stein
Keyword(s):  
Power Management ◽  
Hybrid Electric Vehicle ◽  
Single Mode ◽  
Stochastic Dynamic ◽  
Electricity Pricing ◽  
Control Approach ◽  
Potential Benefits ◽  
Hybrid Electric ◽  
The Impact ◽  
Charge Depletion

This paper examines the problem of optimally splitting driver power demand among the different actuators (i.e., the engine and electric machines) in a plug-in hybrid electric vehicle (PHEV). Existing studies focus mostly on optimizing PHEV power management for fuel economy, subject to charge sustenance constraints, over individual drive cycles. This paper adds three original contributions to this literature. First, it uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle. Second, it explicitly trades off fuel and electricity usage in a PHEV, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance. Finally, it examines the impact of variations in relative fuel-to-electricity pricing on optimal PHEV power management. The paper focuses on a single-mode powersplit PHEV configuration for mid-size sedans, but its approach is extendible to other configurations and sizes as well.

Electricity Pricing in Sweden in Theory and Practice

1994 ◽  
Vol 16 (4) ◽  
pp. 519-530
Author(s):  
FERDINAND E. BANKS
Keyword(s):  
Theory And Practice ◽  
Electricity Pricing

Optimal Scheduling Method of Controllable Loads in DC Smart Apartment Building

2015 ◽  
Vol 16 (6) ◽  
pp. 579-589 ◽  
Author(s):  
Tsubasa Shimoji ◽  
Hayato Tahara ◽  
Hidehito Matayoshi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu
Keyword(s):  
Power Flow ◽  
Residential Buildings ◽  
Heat Pumps ◽  
Optimal Operation ◽  
Optimal Scheduling ◽  
Electricity Pricing ◽  
Residential Areas ◽  
Electricity Cost ◽  
Pricing Scheme ◽  
Scheduling Method

Abstract From the perspective of global warming suppression and the depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), have been gaining attention in worldwide. Houses or buildings with PV and heat pumps (HPs) are recently being used in residential areas widely due to the time of use (TOU) electricity pricing scheme which is essentially inexpensive during middle-night and expensive during day-time. If fixed batteries and electric vehicles (EVs) can be introduced in the premises, the electricity cost would be even more reduced. While, if the occupants arbitrarily use these controllable loads respectively, power demand in residential buildings may fluctuate in the future. Thus, an optimal operation of controllable loads such as HPs, batteries and EV should be scheduled in the buildings in order to prevent power flow from fluctuating rapidly. This paper proposes an optimal scheduling method of controllable loads, and the purpose is not only the minimization of electricity cost for the consumers, but also suppression of fluctuation of power flow on the power supply side. Furthermore, a novel electricity pricing scheme is also suggested in this paper.

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