scholarly journals Development of Consumer Preference based Demand Response Model for Home Energy Management

2019 ◽  
Vol 8 (4S2) ◽  
pp. 387-390
Keyword(s):  
Demand Response ◽  
Consumer Preferences ◽  
Supply And Demand ◽  
Consumer Preference ◽  
Response Model ◽  
Home Energy Management ◽  
Scheduling Method ◽  
Load Pattern ◽  
Android App ◽  
The Internet Of Things

Demand response has become an effective method for energy saving and to reduce the energy cost. By adjusting the residential loads, it reacts quickly for the mismatches of supply and demand. In this paper, the Internet of Things (IoT) based Demand Response (Load scheduling method) methodology is proposed to mitigate the energy waste and tariff. Two different alarm provisions are made at the consumer side to indicate the normal and demand modes operated by the supplier. The consumer is provided with a controller that read the market signal and answers with consumer preferences. Whenever demand mode arises, the consumer is completely free to change the load setting; also the developed system will propose the load pattern. The demand mode will be given during peak hour and the tariff will be high at that time and normal mode will consist of the minimum tariff. The consumer may control their load through cloud-MQTT by giving a specific command or from the MQTT dashboard android app. Based on the tariff, the consumption profile could be reduced

scholarly journals Thermal demand response model considering user's satisfaction with heat consumption under electrothermal coupling

2021 ◽  
Vol 236 ◽  
pp. 01034
Author(s):  
Wang Zhenyu ◽  
Zhang Jianhua ◽  
Hu Chunlan ◽  
Xu Lanlan ◽  
Han Yongjun
Keyword(s):  
Demand Response ◽  
Supply And Demand ◽  
Thermal Power ◽  
Response Model ◽  
Power Demand ◽  
Time Sharing ◽  
Economic Operation ◽  
New Energy ◽  
Heating Mode ◽  
Demand Side Response

.In recent years, the development of new energy has become a bottleneck. As a high-quality demand side response resource that can be flexibly dispatched, thermal load can be used to promote the consumption and utilization of new energy. Based on the theory of peak valley electricity price and power demand response mechanism, this paper designs a demand response model of thermal price type, which uses time-sharing heat price to guide users to use heat orderly on the heating side. The simulation results show that the reasonable setting of heat price and satisfaction constraints of different heating modes can effectively change the heating mode of the user side and alleviate the contradiction between the supply and demand of thermal power, reduce the heating cost and realize the economic operation of the system.

The Impact of Consumer Preference Distributions on Dynamic Electricity Pricing for Residential Demand Response

2019 ◽  
Author(s):  
Samuel Dunbar ◽  
Scott Ferguson
Keyword(s):  
Demand Response ◽  
Dynamic Pricing ◽  
Consumer Preferences ◽  
Consumer Preference ◽  
Population Level ◽  
Economic Incentives ◽  
System Level ◽  
Renewable Energy Resources ◽  
Product Use ◽  
The Impact

Abstract Demand Response (DR) is the adjustment of consumer electricity demand through the deployment of one or more strategies, e.g. direct load control, policy implementation, dynamic pricing, or other economic incentives. Widespread implementation of DR is a promising solution for addressing energy challenges such as the integration of intermittent renewable energy resources, reducing capacity cost, and improving grid reliability. Understanding residential consumer preferences for shifting product usage and how these preferences are distributed amongst a population are key to predicting the effectiveness of different DR strategies. In addition, there is a need for a better understanding of how different DR programs, system level objectives, and preference distributions will impact different segments of consumers within a population. Specifically, the impacts on their product use behavior and electricity bill. To address this challenge, a product based approach to modeling consumer decisions about altering their electricity consumption is proposed, which links consumer value to their products, instead of directly to the amount of electricity they consume. This model is then used to demonstrate how population level preference distributions for altering product use impact system level objectives.

scholarly journals Pricing Mechanism of Charging Pile Power Supply Market——Based on RTP Theory and Price Discrimination Model

2021 ◽  
Vol 275 ◽  
pp. 01073
Author(s):  
Shiyao Ding ◽  
Siqi Zhang
Keyword(s):  
Price Discrimination ◽  
Demand Response ◽  
Cost Model ◽  
Supply And Demand ◽  
Retail Market ◽  
Response Model ◽  
Supply Pressure ◽  
Discrimination Model ◽  
New Energy ◽  
Differential Pricing

Based on the data of monopoly enterprises in China’s new energy charging pile power retail market, this paper explores the application of RTP differential pricing in new areas. First of all, from the perspective of business, this paper constructs the incentive cost model of low period which can minimize the supply pressure of power sales enterprises. Then, from the perspective of charging consumers, based on the assumption of user’s conversion cost, an improved demand response model is established according to the price elasticity. The paper is to consider the premise of maximizing social welfare, in the supply and demand of both sides to improve the pressure of electricity measurement, to minimize the operation and maintenance costs in peak and trough period.

scholarly journals Diversity in Nutrient Content and Consumer Preferences of Sensory Attributes of Peanut (Arachis hypogaea L.) Varieties in Ugandan Agroecosystems

2021 ◽  
Vol 13 (5) ◽  
pp. 2658
Author(s):  
Rose Nankya ◽  
John W. Mulumba ◽  
Hannington Lwandasa ◽  
Moses Matovu ◽  
Brian Isabirye ◽  
...  
Keyword(s):  
Arachis Hypogaea ◽  
Consumer Preferences ◽  
Consumer Preference ◽  
Nutrient Content ◽  
Intraspecific Diversity ◽  
Laboratory Evaluation ◽  
Organoleptic Characteristics ◽  
Arachis Hypogaea L ◽  
Cultivated Peanut ◽  
Nutrient Amounts

The cultivated peanut (Arachis hypogaea L.) is one of the most widely consumed legumes globally due to its nutrient content, taste, and affordability. Nutrient composition and consumer preference were determined for twenty local farmer (landrace) and commercial peanut varieties grown in the Nakaseke and Nakasongola districts of the central wooded savanna of Uganda through sensory and laboratory evaluation. Significant differences in nutrient content (p < 0.05) among peanut varieties were found within and across sites. A significant relationship between nutrient content and consumer preference for varieties within and across sites was also realized (Wilk’s lambda = 0.05, p = 0.00). The differences in nutrient content influenced key organoleptic characteristics, including taste, crunchiness, appearance, and soup aroma, which contributed to why consumers may prefer certain varieties to others. Gender differences in variety selection were significantly related to consumer preference for the crunchiness of roasted peanut varieties (F = 5.7, p = 0.016). The results imply that selecting different varieties of peanuts enables consumers to receive different nutrient amounts, while experiencing variety uniqueness. The promotion of peanut intraspecific diversity is crucial for improved nutrition, organoleptic appreciation and the livelihood of those engaged in peanut value chains, especially for the actors who specialize in different peanut products. The conservation of peanut diversity will ensure that the present and future generations benefit from the nutritional content and organoleptic enjoyment that is linked to unique peanut varieties.

Exploring the Role of Interaction Effects in Visual Conjoint Analysis

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Brian Sylcott ◽  
Jeremy J. Michalek ◽  
Jonathan Cagan
Keyword(s):  
Conjoint Analysis ◽  
Consumer Preferences ◽  
Consumer Preference ◽  
Interaction Effects ◽  
Fractional Factorial ◽  
Main Effects ◽  
Full Factorial ◽  
Biased Estimates ◽  
Data Requirements

In conjoint analysis, interaction effects characterize how preference for the level of one product attribute is dependent on the level of another attribute. When interaction effects are negligible, a main effects fractional factorial experimental design can be used to reduce data requirements and survey cost. This is particularly important when the presence of many parameters or levels makes full factorial designs intractable. However, if interaction effects are relevant, main effects design can create biased estimates and lead to erroneous conclusions. This work investigates consumer preference interactions in the nontraditional context of visual choice-based conjoint analysis, where the conjoint attributes are parameters that define a product's shape. Although many conjoint studies assume interaction effects to be negligible, they may play a larger role for shape parameters. The role of interaction effects is explored in two visual conjoint case studies. The results suggest that interactions can be either negligible or dominant in visual conjoint, depending on consumer preferences. Generally, we suggest using randomized designs to avoid any bias resulting from the presence of interaction effects.

Real-time price-based demand response model for combined heat and power systems

Energy ◽  
2019 ◽  
Vol 168 ◽  
pp. 1119-1127 ◽  
Author(s):  
Manijeh Alipour ◽  
Kazem Zare ◽  
Heresh Seyedi ◽  
Mehdi Jalali
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Demand Response ◽  
Combined Heat And Power ◽  
Response Model ◽  
Time Price

scholarly journals Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7484
Author(s):  
Yuki Matsuda ◽  
Yuto Yamazaki ◽  
Hiromu Oki ◽  
Yasuhiro Takeda ◽  
Daishi Sagawa ◽  
...  
Keyword(s):  
Supply And Demand ◽  
Real Life ◽  
Energy System ◽  
Energy Markets ◽  
Peer To Peer ◽  
Renewable Energy Resources ◽  
Trading System ◽  
Energy Trading ◽  
Demonstration Experiment ◽  
Home Energy Management

To further implement decentralized renewable energy resources, blockchain based peer-to-peer (P2P) energy trading is gaining attention and its architecture has been proposed with virtual demonstrations. In this paper, to further socially implement this concept, a blockchain based peer to peer energy trading system which could coordinate with energy control hardware was constructed, and a demonstration experiment was conducted. Previous work focused on virtually matching energy supply and demand via blockchain P2P energy markets, and our work pushes this forward by demonstrating the possibility of actual energy flow control. In this demonstration, Plug-in Hybrid Electrical Vehicles(PHEVs) and Home Energy Management Systems(HEMS) actually used in daily life were controlled in coordination with the blockchain system. In construction, the need of a multi-tagged continuous market was found and proposed. In the demonstration experiment, the proposed blockchain market and hardware control interface was proven capable of securing and stably transmitting energy within the P2P energy system. Also, by the implementation of multi-tagged energy markets, the number of transactions required to secure the required amount of electricity was reduced.

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