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Artykuły w czasopismach na temat "Time of Use (ToU) tariff"

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Sundt, Swantje, Katrin Rehdanz, and Jürgen Meyerhoff. "Consumers’ Willingness to Accept Time-of-Use Tariffs for Shifting Electricity Demand." Energies 13, no. 8 (2020): 1895. http://dx.doi.org/10.3390/en13081895.

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Time-of-use (TOU) electricity tariffs represent an instrument for demand side management. By reducing energy demand during peak times, less investments in otherwise necessary, costly, and CO2 intensive redispatch would be required. We use a choice experiment (CE) to analyze private consumers’ acceptance of TOU tariffs in Germany. In our CE, respondents choose between a fixed rate tariff and two TOU tariffs that differ by peak time scheme and by a control of appliances’ electricity consumption during that time. We use a mixed logit model to account for taste heterogeneity. Moreover, investigating decision strategies, we identify three different strategies that shed light on drivers of unobserved taste heterogeneity: (1) Always choosing the status quo, (2) always choosing the maximum discount, and (3) choosing a TOU tariff but not always going for the maximum discount. Overall, about 70% of our 1398 respondents would choose a TOU tariff and shift their electricity demand, leading to a decline in energy demand during peak times. Rough estimates indicate that this would lead to significant savings in electricity generation, avoiding up to a mid to large-sized fossil-fuel power plant.
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Sundt, Swantje. "Influence of Attitudes on Willingness to Choose Time-of-Use Electricity Tariffs in Germany. Evidence from Factor Analysis." Energies 14, no. 17 (2021): 5406. http://dx.doi.org/10.3390/en14175406.

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Time-of-use (TOU) electricity tariffs are a demand side measure to ease balancing of demand and supply to cope with a rising share of renewables in a country’s electricity mix. In general, consumers require compensation for accepting these tariffs. This study analyzes how attitudes drive consumers’ willingness to choose a TOU tariff in Germany. To identify attitudinal profiles, I use an exploratory factor analysis on items capturing positive and negative attitudes towards TOU tariffs, climate change awareness, and belief in energy saving measures. I use these factors as predictors in an ordered logit specification to estimate consumers’ stated willingness to choose a TOU tariff. Three factors are significant: positive and negative attitudes towards TOU tariffs, and climate change awareness. These findings highlight that decision makers who aim at balancing demand and supply through the use of TOU tariffs should focus on informing consumers about the positive impacts of these tariffs on climate change mitigation, grid stability, and possible energy savings.
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Azrina Mohd Azman, Nur, Md Pauzi Abdullah, Mohammad Yusri hasan, Dalila Mat Said, and Faridah Hussin. "Enhanced Time of Use Electricity Pricing for Industrial Customers in Malaysia." Indonesian Journal of Electrical Engineering and Computer Science 6, no. 1 (2017): 155. http://dx.doi.org/10.11591/ijeecs.v6.i1.pp155-159.

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<p>New Time of Use (ToU) tariff scheme known as Enhanced ToU (EToU) has been introduced on 1st January 2016 for industrial customers in Malaysia. EToU scheme is the advanced version of current ToU where the daily time frame is divided into six period blocks, as compared to only two in the existing ToU. Mid-peak tariff is introduced on top of peak-hour and off-peak tariff. The new scheme is designed to reduce Malaysia’s peak hour electricity demand. On customer side, they could be benefited from the low off-peak tariff by simply shifting their consumption. However, it depends on their consumption profile and their flexibility in shifting their consumption. Since EToU scheme is voluntary, each customer needs to perform cost-benefit analysis before deciding to switch into the scheme. This paper analyzes this problem by considering EToU tariff scheme for industry and customer’s electricity consumption profile. Case studies using different practical data from different industries are presented and discussed in this paper.</p>
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Phan, Binh Thi Thanh, Qui Minh Le, and Cuong Viet Vo. "Optimizing the time of use tariff with different scenarios of load management." Science and Technology Development Journal 20, K7 (2018): 15–20. http://dx.doi.org/10.32508/stdj.v20ik7.1206.

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Demand Response program is applied in many countries as an effective instrument to regulate the electricity consumption. In this program, time of use (TOU) tariff is used widely. Optimal TOU pricing according to different objectives was mentioned in this paper such as peak load reduction, improving load curve, energy conservation, avoiding a new peak load. This is a problem with multiobjective functions in different unit of measurement and is solved by PSO algorithm. An example to find optimal TOU tariff for one utility is also presented in this paper.
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Xue, Wanlei, Xin Zhao, Yan Li, et al. "Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand." Energies 16, no. 4 (2023): 1625. http://dx.doi.org/10.3390/en16041625.

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Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model.
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Chen, Lu, Yong Biao Yang, and Li Huang. "Design of Time-of-Use Model for Promoting Wind Power’s Penetration." Advanced Materials Research 953-954 (June 2014): 575–81. http://dx.doi.org/10.4028/www.scientific.net/amr.953-954.575.

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Considering wind power output characteristics, TOU model with frequency is proposed, in the form of “normal tariff plus frequency tariff”. Response mode and capacity is analyzed on the basis of consumer psychology. The numerical examples shows its effectiveness, that wind power output can be complemented by demand through tariff incentives, avoid abandoning the wind and reducing peak power difference.
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Jang, Minseok, Hyun-Cheol Jeong, Taegon Kim, and Sung-Kwan Joo. "Load Profile-Based Residential Customer Segmentation for Analyzing Customer Preferred Time-of-Use (TOU) Tariffs." Energies 14, no. 19 (2021): 6130. http://dx.doi.org/10.3390/en14196130.

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Smart meters and dynamic pricing are key factors in implementing a smart grid. Dynamic pricing is one of the demand-side management methods that can shift demand from on-peak to off-peak. Furthermore, dynamic pricing can help utilities reduce the investment cost of a power system by charging different prices at different times according to system load profile. On the other hand, a dynamic pricing strategy that can satisfy residential customers is required from the customer’s perspective. Residential load profiles can be used to comprehend residential customers’ preferences for electricity tariffs. In this study, in order to analyze the preference for time-of-use (TOU) rates of Korean residential customers through residential electricity consumption data, a representative load profile for each customer can be found by utilizing the hourly consumption of median. In the feature extraction stage, six features that can explain the customer’s daily usage patterns are extracted from the representative load profile. Korean residential load profiles are clustered into four groups using a Gaussian mixture model (GMM) with Bayesian information criterion (BIC), which helps find the optimal number of groups, in the clustering stage. Furthermore, a choice experiment (CE) is performed to identify Korean residential customers’ preferences for TOU with selected attributes. A mixed logit model with a Bayesian approach is used to estimate each group’s customer preference for attributes of a time-of-use (TOU) tariff. Finally, a TOU tariff for each group’s load profile is recommended using the estimated part-worth.
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Sulaima, Mohamad Fani, Nurliyana Binti Baharin, Aida Fazliana Abdul Kadir, Norhafiz Bin Salim Obtained, and Elia Erwani Hassan. "Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 1 (2022): 1. http://dx.doi.org/10.11591/ijeecs.v28.i1.pp1-11.

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<span>A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed where the maximum load shifting weightage was set up to 30% to reflect the consumers’ effort towards energy efficiency (EE) program. The previously proposed TOU design was identified to be a suitable structure that can promote balancing of EE and demand response (DR) program effort in most consumers' houses category in Malaysia.</span>
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Nazar, J., J. J. Jamian, M. A. Baharudin, and S. N. Syed Nasir. "New Dynamic Time-of-Use Tariff For Islanded Microgrid System With High Penetration of Renewable Energy." Journal of Physics: Conference Series 2523, no. 1 (2023): 012027. http://dx.doi.org/10.1088/1742-6596/2523/1/012027.

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Abstract This paper proposes a dynamic time-of-use (d-TOU) tariff scheme for microgrid (MG) systems in islanded mode. The main problem for the islanded MG is the high cost of electricity, and the output from renewable energy is uncontrollable compared to the traditional grid. Therefore, this paper focuses on developing a suitable tariff scheme that provides reliability and financial benefits for both utility and customer. The time zone energy prices based on the Levelized Cost of Energy (LCOE) are introduced for islanded MG. The results show a contradiction between islanded MG with the standard traditional power generation TOU. Even though the LCOE obtained for MG is higher than conventional electricity rates, the greenhouse gas (GHG) emissions rate is reduced by 85%. In conclusion, the proposed d-TOU tariff scheme is suitable for the islanded MG system and it is beneficial for both the utility and the customer by not causing a financial burden to the utility and encouraging the customer to make a demand response in the future.
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Lee, Jinyeong, Jaehee Lee, and Young-Min Wi. "Impact of Revised Time of Use Tariff on Variable Renewable Energy Curtailment on Jeju Island." Electronics 10, no. 2 (2021): 135. http://dx.doi.org/10.3390/electronics10020135.

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Jeju Island announced the “Carbon Free Island (CFI) Plan by 2030” in 2012. This plan aims to replace conventional generators with distributed energy resources (DERs) up to a level of 70% by 2030. Akin to Jeju Island, as DERs have been expanded in islanded power systems, variable renewable energy (VRE) has become a significant component of DERs. However, VRE curtailment can occur to meet power balance, and VRE curtailment generally causes energy waste and low efficiency, so it should be minimized. This paper first presents a systematic procedure for estimating the annual VRE curtailment for the stable operation of the islanded power systems. In this procedure, the VRE curtailment is estimated based on the power demand, the grid interconnection, the capacity factor of VRE, and conventional generators in the base year. Next, through the analysis of the hourly net load profile for the year in which the VRE curtailment is expected to occur, a procedure was proposed to find the season and hour when VRE curtailment occurs the most. It could be applied to revised Time-of-Use (ToU) tariff rates as the most cost-effective mitigation method of VRE curtailment on the retail market-side. Finally, price elasticity of electricity demand was presented for applying the revised ToU tariff rate scenarios in a specific season and hour, which found that VRE curtailment occurred the most. Considering self- and cross-price elasticity of electricity, revised ToU tariff rate scenarios were used in a case study on Jeju Island. Eventually, it was confirmed that VRE curtailment could be mitigated when the revised ToU tariff rates were applied, considering the price elasticity of demand.
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