A Research on Operational Stability of Demand Response Resource for Different Manufacturing Sub-sectors through Power Consumption Pattern Analysis

Author(s):  
Hye-Young Kim ◽  
Hyunsoo Kim ◽  
Bok-Deok Shin
Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3129
Author(s):  
Jewon Oh ◽  
Daisuke Sumiyoshi ◽  
Masatoshi Nishioka ◽  
Hyunbae Kim

The mass introduction of renewable energy is essential to reduce carbon dioxide emissions. We examined an operation method that combines the surplus energy of photovoltaic power generation using demand response (DR), which recognizes the balance between power supply and demand, with an aquifer heat storage system. In the case that predicts the occurrence of DR and performs DR storage and heat dissipation operation, the result was an operation that can suppress daytime power consumption without increasing total power consumption. Case 1-2, which performs nighttime heat storage operation for about 6 h, has become an operation that suppresses daytime power consumption by more than 60%. Furthermore, the increase in total power consumption was suppressed by combining DR heat storage operation. The long night heat storage operation did not use up the heat storage amount. Therefore, it is recommended to the heat storage operation at night as much as possible before DR occurs. In the target area of this study, the underground temperature was 19.1 °C, the room temperature during cooling was about 25 °C and groundwater could be used as the heat source. The aquifer thermal energy storage (ATES) system in this study uses three wells, and consists of a well that pumps groundwater, a heat storage well that stores heat and a well that used heat and then returns it. Care must be taken using such an operation method depending on the layer configuration.


Author(s):  
Mohammad H. Naraghi

The clear sky and monthly clearness index models are used to evaluate the hourly and monthly insolation on unit area of a tilted surface for the entire year. The hourly power consumption of a typical municipality (for this case New York City) for typical summer and winter days are used to determine the tilt and azimuth angles of a solar panel such that the solar energy reached the panel best match the energy consumption pattern. For the example case considered, in this work New York City, the electric power consumption peaks during summers at afternoon hours, due to increase in building cooling loads. It is found that orienting the solar panel at a westward azimuth angle with a tilt angle that results in maximum annual insolation is the best orientation of the solar panel for responding to both the peak energy demand and having reasonably high overall annual power generation. Although the model is used to optimize the solar panel orientation for New York City, it can however, be used for any building at any location as long as the needed solar data and power consumption pattern are known.


Author(s):  
Yunzhi Wang ◽  
Xiangdong Wang ◽  
Yueliang Qian ◽  
Haiyong Luo ◽  
Fujiang Ge ◽  
...  

The smart grid is an important application field of the Internet of things. This paper presents a method of user electricity consumption pattern analysis for smart grid applications based on the audio feature EEUPC. A novel similarity function based on EEUPC is adapted to support clustering analysis of residential load patterns. The EEUPC similarity exploits features of peaks and valleys on curves instead of directly comparing values and obtains better performance for clustering analysis. Moreover, the proposed approach performs load pattern clustering, extracts a typical pattern for each cluster, and gives suggestions toward better power consumption for each typical pattern. Experimental results demonstrate that the EEUPC similarity is more consistent with human judgment than the Euclidean distance and higher clustering performance can be achieved for residential electric load data.


2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Ibrahim S.H. ◽  
Baharun A. ◽  
Nawi M.N.M ◽  
Chai C.J.

This study presents a method to determine power consumption pattern for several types of consumers in Sarawak, Malaysia. The power consumption data for consumers has been recorded using EDMI Mk.6 Genius polyphase electronic (E3) meters installed at their premises. The multistage cluster sampling is used to design the sample size to determine the sufficient amount of meters required. The data obtained from the meters has been analysed to obtain the pattern of power consumption for different types of consumers. This power consumption pattern has been applied to determine load factor, diversity factor for the calculation of After Diversity Maximum Demand (ADMD). ADMD is also used to determine the optimal amount of load, distribution transformer size and 11kV cable size. Temperature sensitivity analysis related to the demand has been investigated as well. It is found that power consumption pattern model is beneficial in finding the total electrical load, distribution transformer size and 11kV cable size needed by the consumers. Thus through this study the load characteristics had been determined to support utility operation and planning efficiently.


2020 ◽  
Vol 10 (5) ◽  
pp. 1627 ◽  
Author(s):  
Himanshu Nagpal ◽  
Andrea Staino ◽  
Biswajit Basu

In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.


2013 ◽  
Vol 4 (2) ◽  
pp. 1048-1057 ◽  
Author(s):  
Hideitsu Hino ◽  
Haoyang Shen ◽  
Noboru Murata ◽  
Shinji Wakao ◽  
Yasuhiro Hayashi

Sign in / Sign up

Export Citation Format

Share Document