Table 2 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
![TOU tariff according to the literature [37-40].](publication/325164031/figure/tbl2/AS:667821503684610@1536232462387/TOU-tariff-according-to-the-literature-37-40.png)
Source publication
![Table 2 . TOU tariff according to the literature [37-40].](publication/325164031/figure/tbl2/AS:667821503684610@1536232462387/TOU-tariff-according-to-the-literature-37-40_Q320.jpg)
The increase of domestic electrical and thermal controllable devices and the emergence of dynamic electrical pricing leads to the opportunity to integrate and optimize electrical and thermal energy at a house level using a home energy management system (HEMS) in order to minimize the energy costs. In the literature, optimization-based algorithms yi...
Context in source publication
Context 1
... multiple TOU tariffs in the literature does not enable to extract a typical TOU. Therefore, the considered TOU tariff in this work (Table 2) is based on actual TOU tariffs which implement a three period tariff [37]. Based on the price ratio in the literature [37][38][39][40], the peak demand and the off peak prices are adapted according to the current tariff in Germany (30 ce/kWh), whereas feed-in tariff is still considered. ...
Citations
... Customers must necessarily be equipped with specific automation technologies [49] and they have to be informed of the hourly prices trend, one hour before or the day before at least. However, many key variables intrinsic to residential customers are significantly more complicated if compared to those of commercial and industrial ones [50,51]. The main advantage of the RTP tariffs lies in the temporal granularity of price signals transmission to customers enabling them to respond rapidly to the market conditions changes [52,53]. ...
This study is focused on the definition of an energy aggregator model for domestic users, offering the Demand Response (DR) optimization and additional services. The research project is based on the Italian electricity system analysis pointing out the renewables high contribution, the poor domestic users’ electrification and the need to figure out those issues by a demand flexibility system implementation. Moreover, the characterization of Italian domestic users’ energy loads allowed to identify the suitable strategies to get higher flexibility degree. Thus, three case studies have been considered to assess the achievable economic savings due to the DR implementation, accounting for the revenue for dispatching services as well as the intraday energy price variations on the Italian market. It emerged that the demand side flexibility implementation offers benefits to the Italian electricity system but entails small economic benefits for the end-users. Additionally, the adoption of such a system is quite complicated due to the lack of suitable and reliable automation devices. For that reason, a potential energy aggregator for domestic users will have to search funds for its own operation providing customers with additional services, such as energy saving and assisted-living, by using of ICT along with automation within each dwelling.
With the development of society and the progress of science and technology, people’s demand for electric energy is becoming stronger and stronger. In order to adapt to the increasing demand for electric energy, smart grids are gradually popularized. It not only changed the development mode of our country’s power grid, but also brought new opportunities and challenges for our country’s power companies. Among them, the electricity bill information management system based on network micro-service technology ensures the accuracy and stability of users’ electricity consumption data. The purpose of this paper is to study the construction of electricity bill information management system based on network microservice technology. This article takes the electricity bill information management system as the research object, combined with the network micro-service technology, analyzes the functional characteristics of the system, and details the functional modules of the system’s user management, meter reading management, electricity bill collection management, and electricity monitoring management. This article briefly introduces the system test environment, and conducts main functional module tests and stress tests on the system. The test results show that the shortest response time of each function of the system is 2.016 s, and the longest is 2.341 s. And the success rate of system function operation is above 98%. It can be seen that this system has good performance and meets the performance requirements of the system.KeywordsElectricity bill managementElectricity consumption information collectionManagement analysisNetwork microservices
