scholarly journals Scheduling Optimization of Smart Homes Based on Demand Response

2015 ◽  
pp. 223-236 ◽  
Author(s):  
Jiawei Zhu ◽  
Fabrice Lauri ◽  
Abderrafiaa Koukam ◽  
Vincent Hilaire
Keyword(s):  
Demand Response ◽  
Smart Homes ◽  
Scheduling Optimization ◽  
On Demand

A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response

2021 ◽  
Vol 170 ◽  
pp. 884-896
Author(s):  
Marcos Tostado-Véliz ◽  
Daniel Icaza-Alvarez ◽  
Francisco Jurado
Keyword(s):  
Demand Response ◽  
Smart Homes ◽  
Optimal Sizing ◽  
Battery Systems

scholarly journals Research on Demand Response Aggregators Participating in Power Market Based on Bi-level Optimization

2021 ◽  
Vol 781 (4) ◽  
pp. 042009
Author(s):  
Weijie Shen ◽  
Cheng Fang ◽  
Jiaxin Ma ◽  
Jialin Lin ◽  
Ming Zeng
Keyword(s):  
Demand Response ◽  
Power Market ◽  
On Demand

scholarly journals A Multiobjective Scheduling Optimization Model for Multienergy Complementary System Integrated by Wind-Photovoltaic-Convention Gas Turbines considering Demand Response

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Zhang Lihui ◽  
Xin He ◽  
Ju Liwei
Keyword(s):  
Demand Response ◽  
Optimization Model ◽  
Gas Turbines ◽  
Risk Level ◽  
Objective Functions ◽  
Entropy Weight ◽  
Scheduling Optimization ◽  
Power Sources ◽  
Complementary System ◽  
Scheduling Model

To utilize the complementary feature of different power sources, wind power plant (WPP), and solar photovoltaic power (PV), convention gas turbines (CGT) and incentive-based demand response (IBDR) are integrated into a multienergy complementary system (MECS) with the implementation of price-based demand response (PBDR). Firstly, the power output model of WPP, PV, and CGT is constructed and the mathematical model of DR is presented. Then, a multiobjective scheduling model is proposed for MECS operation under the objective functions of the maximum economic benefit, the minimum abandoned energy, and the minimum risk level. Thirdly, the payoff table of objective functions is put forward for converting the multiobjective model into a single objective model by using entropy weight method to calculate weighting coefficients of different objective functions. Finally, the improved IEEE 30 bus system is taken as the simulation system with four simulation scenarios for comparatively analyzing the influence of PBDR and IBDR on MECS operation. The simulation results show the following: (1) The MECS fully utilized the complementarity of different power sources; CGT and IBDR can provide peaking service for WPP and PV to optimize overall system operation. (2) The proposed algorithm can solve the MECS multiobjective scheduling optimization model, and the system scheduling results in the comprehensive optimal mode can take into account different appeal. And the total revenue, abandoned energy capacity, and load fluctuation are, respectively, 108009.30¥, 11.62 MW h, and 9.74 MW. (3) PBDR and IBDR have significant synergistic optimization effects, which can promote the grid connection of WPP and PV. When they are both introduced, the peak-to-valley ratio of the load curve is 1.19, and the abandoned energy is 5.85 MW h. Therefore, the proposed MECS scheduling model and solution algorithm could provide the decision basis for decision makers based on their actual situation.

Study on demand response to participate in wind power integration

2013 ◽  
pp. 1077-1080
Author(s):  
Gui-Xiong He ◽  
Xiao-Shuang Chen ◽  
Yu-Hui Zhou ◽  
Deng Pan ◽  
Li-Min Jiang ◽  
...  
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Wind Power Integration ◽  
On Demand

scholarly journals LINC complex-Lis1 interplay controls MT1-MMP matrix digest-on-demand response for confined tumor cell migration

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Elvira Infante ◽  
Alessia Castagnino ◽  
Robin Ferrari ◽  
Pedro Monteiro ◽  
Sonia Agüera-González ◽  
...  
Keyword(s):  
Cell Migration ◽  
Tumor Cell ◽  
Demand Response ◽  
Linc Complex ◽  
Tumor Cell Migration ◽  
On Demand
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