Grid Load Shifting and Performance Assessments of Residential Efficient Energy Technologies, a Case Study in Japan

Li, Yanxue; Gao, Weijun; Ruan, Yingjun; Ushifusa, Yoshiaki

doi:10.3390/su10072117

Cited by 11 publications

(6 citation statements)

References 26 publications

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“…PV generation, EES, Load Shifting, Electric Vehicles and, especially, Efficient Technologies are managed to participate in grid load management for residential scenarios in Japan [21]. The efficient technology that is considered is Heat Pump Water Heaters (six million units in Japan in 2017 with rated power in the range of 4.5/6.0 kW).…”

Section: Literature Surveymentioning

confidence: 99%

Integration of Demand Response and Photovoltaic Resources in Residential Segments

et al. 2018

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The development of renewable sources in residential segments is basic to achieve a sustainable energy scenario in the horizon 2030–2050 because these segments explain around 25% of the final energy consumption. Demand Response and its effective coordination with renewable are additional concerns for residential segments. This paper deals with two problems: the demonstration of cost-effectiveness of renewables in three different scenarios, and the application of the flexibility of demand, performing as energy storage systems, to efficiently manage the generation of renewable sources while improving benefits and avoiding penalties for the customer. A residential customer in Spain has been used as example. The work combines the use of a commercial simulator to obtain photovoltaic generation, the monitoring of customer to obtain demand patterns, and the development of a Physically-Based Model to evaluate the capability of demand to follow self-generation. As a main result, the integration of models (load/generation), neglected in practice in other approaches in the literature, allows customers to improve revenue up to 20% and reach a basic but important knowledge on how they can modify the demand, development of new skills and, in this way, learn how to deal with the characteristics and limitations of both Demand and Generation when a customer becomes a prosumer. This synergy amongst demand and generation physically-based models boosts the possibilities of customers in electricity markets.

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Section: Literature Surveymentioning

confidence: 99%

Integration of Demand Response and Photovoltaic Resources in Residential Segments

et al. 2018

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“…Previous research has focused on estimating national and international DR potentials [5,7,10,11] or simulating or monitoring DR potentials in individual power-consuming units [12][13][14]. There is also literature on how markets have responded to new, more variable tariff structures [1,2,15].…”

Section: Contextualising the Problem: Previous Literature On Demand Rmentioning

confidence: 99%

Piloting Demand Response in Retailing: Lessons Learned in Real-Life Context

2018

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This article presents a case study on a demand response (DR) pilot project dealing with the application of DR in a grocery store with the utilization of refrigeration equipment as energy storage and photovoltaics (PV) as an energy source. DR has recently gained increased interest due to the growing penetration of intermittent renewable energy requiring flexibility in power consumption. The smart power grid enables the introduction of novel solutions to increase flexibility and the entrance of new actors into the markets. Developing new solutions for the mainstream markets requires experimentation in real-life settings serving the development of technological capabilities, necessary policies and regulation, and user and market needs, as well as adaptation of and to infrastructure and maintenance systems. Our case study on a DR pilot in a grocery store in Northern Finland focuses on how the project contributes to knowledge on the potential for DR and scaling up. It was found that energy efficiency, DR, and self-generated PV power can be aligned and even enhance the potential for DR. While mature technologies exist, applications and installations have not yet been standardized to enable rapid scaling up, and current DR market rules and practices fail to accommodate for small electricity consumers.

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“…Marketing strategies today are at odds with the strategies of marketers such as by Jon Spoelstra, for example. Modern marketing is aimed at creating a permanent customer base, with consumers coming again and again (Maloletko, 2017;Li et al, 2018). However, the question of the effectiveness of these strategies is very philosophical.…”

Section: Literature Reviewmentioning

confidence: 99%

Unconditional Demand based on Information Networks

Kuljamina¹,

Leonova²,

Vishnyakova³

2018

ERSJ

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The relevance of the study is namely determined by the need of modern methods of product promotion form special semantic fields in the areas of information systems that anticipate the possible "remorse" of the consumer. In this regard, the article is aimed at modern marketing technologies that affect more and more areas of our lives. The general method of the study is a economic analysis in conjunction with the synthesis on the basis of empirical knowledge obtained from the studies on the related topics. The article reveals the economic situation when economic entities consuming goods and services at the free market are not always satisfied with the results of transactions. The results of the article examine the levels of consumer influence in diverse social and information networks, the formation of the semantic field of network users and the factors affecting the organization of cognitive distortion of consumers. The materials of the article are of practical value for specialists in economic sciences and marketing research.

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Grid Load Shifting and Performance Assessments of Residential Efficient Energy Technologies, a Case Study in Japan

Cited by 11 publications

References 26 publications

Integration of Demand Response and Photovoltaic Resources in Residential Segments

Integration of Demand Response and Photovoltaic Resources in Residential Segments

Piloting Demand Response in Retailing: Lessons Learned in Real-Life Context

Unconditional Demand based on Information Networks

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