Real-time Pricing Information Research Articles

ShopWisely - The Ultimate Price Comparer

Abstract: Customers are faced with an abundance of options in the quickly changing world of online shopping and food delivery, which makes it difficult and time-consuming to find the best offers and affordable solutions. ShopWisely has come to light as a trailblazing answer to this problem, providing consumers with a thorough platform for comparing costs from top e-commerce sites like Amazon and Flipkart as well as popular meal delivery services like Zomato and Swiggy. ShopWisely is an online project that makes it easy for people to make educated purchases. It accomplishes this by compiling real-time pricing information from several sources, giving consumers a comprehensive picture of their choices. With an attractive and userfriendly design, the platform's main objective is to expedite the online shopping and meal ordering process, eventually

Performance Analysis of Hybridization of Heuristic Techniques for Residential Load Scheduling

With the emergence of the smart grid, both consumers and electricity providing companies can benefit from real-time interaction and pricing methods. In this work, a smart power system is considered, where consumers share a common energy source. Each consumer is equipped with a home energy management controller (HEMC) as scheduler and a smart meter. The HEMC keeps updating the utility with the load profile of the home. The smart meter is connected to a power grid having an advanced metering infrastructure which is responsible for two-way communication. Genetic teaching-learning based optimization, flower pollination teaching learning based optimization, flower pollination BAT and flower pollination genetic algorithm based energy consumption scheduling algorithms are proposed. These algorithms schedule the loads in order to shave the peak formation without compromising user comfort. The proposed algorithms achieve optimal energy consumption profile for the home appliances equipped with sensors to maximize the consumer benefits in a fair and efficient manner by exchanging control messages. Control messages contain energy consumption of consumer and real-time pricing information. Simulation results show that proposed algorithms reduce the peak-to-average ratio by 34.56% and help the users to reduce their energy expenses by 42.41% without compromising the comfort. The daily discomfort is reduced by 28.18%.

The new power supply!

Thanks to many qualified authors, Energy Science and Engineering has contained papers of good quality and on relevant topics during the past year. When 2017 started, we had seen the falling costs of solar and offshore wind power during the preceding year. Many of the technologies and systems issues then identified have been addressed in the in the journal. During 2017, industrial development has progressed further. We have seen procurement of offshore wind by Germany resulting in winning bids, offering to produce electricity without any subsidies. But the most remarkable news came from Saudi Arabia, where solar power was offered at 1.79 US¢ per kWh. While it was possible a year ago, to say that new renewable sources of electricity could outcompete any other kind of new power plant, we are about to reach the point where new solar and wind plants provide cheaper electricity than existing thermal plants. This will speed up the transition. But when doing so, opportunities to utilize the characteristics of the new power supply will come fast as well. Electricity-intensive industries may maximize their competitiveness by power price-optimizing strategies, departing from traditional continuous operation process technologies. There is increased use of power control techniques automatically managing any electricity consumption in relation to real-time price information. New developments of microgrid, storage, and direct current technologies are finding customers as disconnecting from large electricity grids becomes economically feasible and often in demand before that solution is really economically superior. As the supply of solar and wind electricity has become cheaper, many have started to disregard energy efficiency options. This is a mistake for at least three reasons: First, energy-efficient technologies have developed fast, too. The obvious example is that while solar photovoltaic technologies making light into electricity have developed, light-emitting diodes, making electricity into light, have demonstrated improved efficiency and falling costs. Sometimes, the development is faster than the implementation so that the economic efficiency potential is actually increasing. Second, when looking for ways to adapt to fluctuating availability of solar and wind power, traditional energy efficiency measures often appear as cost-efficient options to minimize system costs. Finally, lower cost electricity has made electrification competitive with fuel-based systems, almost always providing higher energy efficiency and better controllability at the same time. No doubt, Energy Science and Engineering has a wide range of topics to cover during this period of rapid progress. The ambition is to contribute to the rapid transfer of science into industrial engineering and utilization. To this end, being an open-access journal is a vital feature. Global, immediate access for anybody with Internet is avoiding many barriers previously delaying implementation. With its first impact factor of 2.172, this should be more attractive than ever!

Consumer Acceptance Analysis of the Home Energy Management System

The purpose of this paper is to study consumer acceptance of the Home Energy Management System, which is the next generation electronic management system that the Korean government plans to implement in households. The Home Energy Management System is a critical device in maximizing the efficiency of electric energy consumption for each household by using a smart grid. Because it can visualize real-time price information on the electricity, households can easily monitor and control the amount of electricity consumption. With this feature, the Home Energy Management System can contribute to consumers’ total energy savings. This is a major reason why the Korean government wishes to implement it nationwide. Since the Home Energy Management System is a product that applies new technology that has not yet been directly encountered by consumers, there may be a difference in the level of public perception of the Home Energy Management System. Therefore, the impact of consumers’ awareness of the Home Energy Management System on their intention to use is important. To do this, the Technology Acceptance Model is utilized in this study. Traditional research on the Technology Acceptance Model includes awareness of usefulness and ease of use as well as intention to use. In contrast, in this research, an extended Technology Acceptance Model with four additional factors—economic benefit, social contribution, environmental responsibility, and innovativeness—that may affect the consumer’s awareness of usefulness and ease of use, is proposed. To collect the data, the survey was conducted with 287 respondents. As a result, the proposed model proved to be suitable in explaining the intention to use with a 70.3% explanation power. It is found that economic benefit (0.231) and innovativeness (0.259) impact on usefulness of the Home Energy Management System. Moreover, usefulness (0.551) has a bigger effect on intention to use than ease of use (0.338) does. Based on this, it is desirable for the Korean government to pursue a public relations strategy that emphasizes the economic benefits, social contributions, and environmental responsibility that will be gained when introducing the Home Energy Management System. It is effective to focus on consumers who are inclined to accept innovation. In addition, more effective results can be obtained by referring to the usefulness of the Home Energy Management System rather than referring to ease of use.

Modelling of coal trade process for the logistics enterprise and its optimisation with stochastic predictive control

In the paper, a typical coal trade process is described and modelled, where one logistics enterprise with blending equipments lies in the core and two types of common contracts are elucidated to define constraints. A mixed-integer model is built and featured by addressing contract violation, blending operation, real-time price information and arbitrarily distributed stochastic demands. To deal with the stochastic demands, probabilistic constraints are formed. Accordingly, stochastic model predictive control strategy with both receding horizon and decreasing horizon formulations is developed to handle the probabilistic constraints and exploit the value of newest price information. By solving a series of mixed-integer linear programmes, optimal coal trade decisions for the logistics enterprise can be obtained, including procurement decision, selling decision and operational decision of the blending equipments. Thorough simulation experiments are carried out and compared with three different strategies, which interpret the effectiveness of the proposed strategy.

Creating a Smarter U.S. Electricity Grid

This paper focuses on efforts to build what policymakers call the “smart grid,” involving 1) improved remote monitoring and automatic and remote control of facilities in high-voltage electricity transmission networks; 2) improved remote monitoring, two-way communications, and automatic and remote control of local distribution networks; and 3) installation of “smart” metering and associated communications capabilities on customer premises so that customers can receive real-time price information and/or take advantage of opportunities to contract with their retail supplier to manage the consumer's electricity demands remotely in response to wholesale prices and network congestion. I examine the opportunities, challenges, and uncertainties associated with investments in “smart grid” technologies. I discuss some basic electricity supply and demand, pricing, and physical network attributes that are critical for understanding the opportunities and challenges associated with expanding deployment of smart grid technologies. Then I cover issues associated with the deployment of these technologies at the high voltage transmission, local distribution, and end-use metering levels.

Knowing when to act: an optimal stopping method for smart grid demand response

A major benefit of the smart grid is that it can provide real-time pricing, which enables residential electricity customers to reduce their electricity expenses by scheduling their appliance use. A commonly utilized technique is to operate electrical appliances when the price of electricity is low. Although this technique is simple in principle and easy to apply, there are several issues that need to be addressed: Studies have shown that residents do not know how, or have the time to take advantage of real-time price information; residents seek to save money by delaying device usage but do not want the inconvenience of long wait times; and a lack of automated energy management systems - industry trials of real-time pricing programs requiring manual user intervention have performed poorly. In this work, we address these issues by the means of an optimal stopping approach, which can balance electricity expense and waiting time. We formulate the problem of deciding when to start home appliances as an optimal stopping problem, and combine optimal stopping rules with appliance energy usage profiles. Our result is an automated residential energy management and scheduling platform, which can reduce energy bills and minimize peak loads. Reduced peak loads result in lower usage rates of dirty coal-based peaker plants, reducing carbon emissions. Additional benefits include lower domestic energy use by controlling vampire loads. Simulation results show that our approach can reduce energy costs by about 10-50 percent depending on the appliance type, and demonstrate the usefulness of our approach in managing residential energy costs.

Transitory real‐time property rights and exchange intellectual property

AbstractAmerican exchanges own the price quotations they generate. Access to real‐time price information is highly valued by most market participants. This enables exchanges to exact royalties from the sale of such market information. In this sense, an exchange's ownership of its price quotations is akin to owning a property right in a perishable commodity (i.e., fresh market price quotations) that is most valuable for only a transitory or limited period of time. The implications of exchange ownership of price data extend beyond financial markets. Recently, Woodard (2000) has noted that some internet auction operators have asserted ownership over the prices they generate. This study reviews the legal origin and nature of the property right to price quotations generated on U.S. futures exchanges and assesses whether exchange ownership should be transitory. The legal basis for transitory real‐time (real and personal) property rights is discussed and the economic implications are considered. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:891–913, 2003

Making Every Electricity Consumer a Market Participant (Putting Demand Back in the Equation)

Contrary to a widely held belief, customers without fancy meters, load control equipment, and real-time price information can still signal their willingness to adjust their usage to both rising and declining prices, and thereby moderate those fluctuations and limit market power on the supply side.