Non-cooperative differential game based energy consumption control for dynamic demand response in smart grid

2019 ◽  
Vol 16 (8) ◽  
pp. 107-114 ◽  
Author(s):  
Manxi Wang ◽  
Haitao Xu ◽  
Shengsong Yang ◽  
Lifeng Yang ◽  
Ruifeng Duan ◽  
...  
2022 ◽  
Vol 19 (3) ◽  
pp. 2403-2423
Author(s):  
Santiago Iturriaga ◽  
◽  
Jonathan Muraña ◽  
Sergio Nesmachnow

<abstract><p>Demand response programs allow consumers to participate in the operation of a smart electric grid by reducing or shifting their energy consumption, helping to match energy consumption with power supply. This article presents a bio-inspired approach for addressing the problem of colocation datacenters participating in demand response programs in a smart grid. The proposed approach allows the datacenter to negotiate with its tenants by offering monetary rewards in order to meet a demand response event on short notice. The objective of the underlying optimization problem is twofold. The goal of the datacenter is to minimize its offered rewards while the goal of the tenants is to maximize their profit. A two-level hierarchy is proposed for modeling the problem. The upper-level hierarchy models the datacenter planning problem, and the lower-level hierarchy models the task scheduling problem of the tenants. To address these problems, two bio-inspired algorithms are designed and compared for the datacenter planning problem, and an efficient greedy scheduling heuristic is proposed for task scheduling problem of the tenants. Results show the proposed approach reports average improvements between $ 72.9\% $ and $ 82.2\% $ when compared to the business as usual approach.</p></abstract>


2015 ◽  
Vol 792 ◽  
pp. 160-166
Author(s):  
Denis Armeev ◽  
Yana Abramova ◽  
Vyacheslav Luzhetsky

The frequency variable drivers of induction motors are typically used to control mechanical load. In the paper a frequency control method is proposed to affect regime of the grid that feeds these motors. The method provides successful self-starting or restarting after significant power disturbance of group induction motors. The proposed strategies are applicable for smart grid, for example, demand response technology works well for industrial loads. It is can be useful not only for normal regimes but in case of emergency, for instance, dynamic demand provides accurate control of the load. Both technologies (demand response or dynamic demand) are well integrated in smart grid concept.


2021 ◽  
Vol 13 (3) ◽  
pp. 1093
Author(s):  
Yunlong Zhao ◽  
Geng Kong ◽  
Chin Hao Chong ◽  
Linwei Ma ◽  
Zheng Li ◽  
...  

Controlling energy consumption to reduce greenhouse gas emissions has become a global consensus in response to the challenge of climate change. Most studies have focused on energy consumption control in a single region; however, high-resolution analysis of energy consumption and personalized energy policy-making, for multiple regions with differentiated development, have become a complicated challenge. Using the logarithmic mean Divisia index I (LMDI) decomposition method based on energy allocation analysis (EAA), this paper aims to establish a standard paradigm for a high-resolution analysis of multi-regional energy consumption and provide suggestions for energy policy-making, taking 29 provinces of China as the sample. The process involved three steps: (1) determination of regional priorities of energy consumption control by EAA, (2) revealing regional disparity among the driving forces of energy consumption growth by LMDI, and (3) deriving policy implications by comparing the obtained results with existing policies. The results indicated that 29 provinces can be divided into four groups, with different priorities of energy consumption control according to the patterns of coal flows. Most provinces have increasing levels of energy consumption, driven by increasing per capita GDP and improving living standards, while its growth is restrained by decreasing end-use energy intensity, improving energy supply efficiency, and optimization of industrial structures. However, some provinces are not following these trends to the same degree. This indicates that policy-makers must pay more attention to the different driving mechanisms of energy consumption growth among provinces.


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