Genetic Based Reinforcement Learning Load Control for Smart Grids

2013 ◽  
Vol 860-863 ◽  
pp. 2423-2426
Author(s):  
Xin Li ◽  
Dan Yu ◽  
Chuan Zhi Zang
Keyword(s):  
Reinforcement Learning ◽  
Electric Charge ◽  
Smart Grids ◽  
Mathematic Model ◽  
Customer Participation ◽  
Load Control ◽  
Demand Side ◽  
Energy Usage ◽  
Take The Best ◽  
Simulation Results

As the improvement of smart grids, the customer participation has reinvigorated interest in demand-side features such as load control for domestic users. A genetic based reinforcement learning (RL) load controller is proposed. The genetic is used to adjust the parameters of the controller. The RL algorithm, which is independent of the mathematic model, shows the particular superiority in load control. By means of learning procedures, the proposed controller can learn to take the best actions to regulate the energy usage for equipments with the features of high comfortable for energy usage and low electric charge meanwhile. Simulation results show that the proposed load controller can promote the performance energy usage in smart grids.

Hierarchical Simulated Annealing-Reinforcement Learning Energy Management for Smart Grids

2013 ◽  
Vol 805-806 ◽  
pp. 1206-1209 ◽  
Author(s):  
Xin Li ◽  
Chuan Zhi Zang ◽  
Xiao Ning Qin ◽  
Yang Zhang ◽  
Dan Yu
Keyword(s):  
Simulated Annealing ◽  
Reinforcement Learning ◽  
Energy Management ◽  
Smart Grids ◽  
Mathematic Model ◽  
Trial And Error ◽  
Fuzzy Information ◽  
Energy Usage ◽  
Take The Best ◽  
Simulation Results

For energy management problems in smart grid, a hybrid intelligent hierarchical controller based on simulated annealing (SA) and reinforcement learning (RL) is proposed. The SA is used to adjust the parameters of the controller. The RL algorithm shows the particular superiority, which is independent of the mathematic model and just needs simple fuzzy information obtained through trial-and-error and interaction with the environment. By means of learning procedures, the proposed controller can learn to take the best actions to regulate the energy usage for equipments with the features of high comfortable for energy usage and low electric charge meanwhile. Simulation results show that the proposed load controller can promote the performance energy usage in smart grids.

scholarly journals SARL: A reinforcement learning based QoS-aware IoT service discovery model

2020 ◽  
Vol 71 (6) ◽  
pp. 368-378
Author(s):  
Selahattin Kosunalp ◽  
Kubilay Demir
Keyword(s):  
Reinforcement Learning ◽  
Service Discovery ◽  
Discovery Process ◽  
Energy Usage ◽  
Proposed Model ◽  
Enormous Amount ◽  
Simulation Results ◽  
Composition Process ◽  
Message Overhead ◽  
Usage Efficiency

AbstractThe IoT environment includes the enormous amount of atomic services with dynamic QoS compared with traditional web services. In such an environment, in the service composition process, discovering a requested service meeting the required QoS is a di cult task. In this work, to address this issue, we propose a peer-to-peer-based service discovery model, which looks for the information about services meeting the requested QoS and functionality on an overlay constructed with users of services versus service nodes, with probably constrained resources. However, employing a plain discovery algorithm on the overlay network such as flooding, or k-random walk could cause high message overhead or delay. This necessitates an intelligent and adaptive discovery algorithm, which adapts itself based on users’ previous queries and the results. To fill this gap, the proposed service discovery approach is equipped with a reinforcement learning-based algorithm, named SARL. The reinforcement learning-based algorithm enables SARL to significantly reduce delay and message overhead in the service discovery process by ranking neighboring nodes based on users’ service request preferences and the service query results. The proposed model is implemented on the OMNet simulation platform. The simulation results demonstrate that SARL remarkably outperforms the existing approaches in terms of message overhead, reliability, timeliness, and energy usage efficiency.

scholarly journals Broadband Power Line Communication for Integration of Energy Sensors within a Smart City Ecosystem

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3402
Author(s):  
Jan Slacik ◽  
Petr Mlynek ◽  
Martin Rusz ◽  
Petr Musil ◽  
Lukas Benesl ◽  
...  
Keyword(s):  
Smart Grids ◽  
High Speed ◽  
Power Line ◽  
Experimental Simulation ◽  
Power Line Communication ◽  
Experimental Measurements ◽  
Simulation Tool ◽  
Smart Metering ◽  
Complex Simulation ◽  
Simulation Results

The popularity of the Power Line Communication (PLC) system has decreased due to significant deficiencies in the technology itself, even though new wire installation is not required. In particular, regarding the request for high-speed throughput to fulfill smart-grid requirements, Broadband Power Line (BPLC) can be considered. This paper approaches PLC technology as an object of simulation experimentation in the Broadband Power Line Communication (BPLC) area. Several experimental measurements in a real environment are also given. This paper demonstrates these experimental simulation results as potential mechanisms for creating a complex simulation tool for various PLC technologies focusing on communication with end devices such as sensors and meters. The aim is to demonstrate the potential and limits of BPLC technology for implementation in Smart Grids or Smart Metering applications.

Collaborative Scheduling of Algorithms for Path Planning of Unmanned Systems

2021 ◽  
Vol 01 ◽  
Author(s):  
Ying Li ◽  
Chubing Guo ◽  
Jianshe Wu ◽  
Xin Zhang ◽  
Jian Gao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reinforcement Learning ◽  
Path Planning ◽  
Unmanned Systems ◽  
Ant Colony Optimization Algorithm ◽  
A Algorithm ◽  
Collaborative Scheduling ◽  
Simulation Results ◽  
Planning Problems ◽  
Effective Path

Background: Unmanned systems have been widely used in multiple fields. Many algorithms have been proposed to solve path planning problems. Each algorithm has its advantages and defects and cannot adapt to all kinds of requirements. An appropriate path planning method is needed for various applications. Objective: To select an appropriate algorithm fastly in a given application. This could be helpful for improving the efficiency of path planning for Unmanned systems. Methods: This paper proposes to represent and quantify the features of algorithms based on the physical indicators of results. At the same time, an algorithmic collaborative scheme is developed to search the appropriate algorithm according to the requirement of the application. As an illustration of the scheme, four algorithms, including the A-star (A*) algorithm, reinforcement learning, genetic algorithm, and ant colony optimization algorithm, are implemented in the representation of their features. Results: In different simulations, the algorithmic collaborative scheme can select an appropriate algorithm in a given application based on the representation of algorithms. And the algorithm could plan a feasible and effective path. Conclusion: An algorithmic collaborative scheme is proposed, which is based on the representation of algorithms and requirement of the application. The simulation results prove the feasibility of the scheme and the representation of algorithms.

Modeling of Aluminum Extrusion Process Using Non-Orthogonal Block Structured Grids Based FVM

2011 ◽  
Vol 189-193 ◽  
pp. 1749-1752
Author(s):  
Rui Wang ◽  
Hong Zhong Li
Keyword(s):  
Mathematic Model ◽  
Extrusion Process ◽  
Special Treatment ◽  
Aluminum Extrusion ◽  
Rigid Plastic ◽  
Structured Grids ◽  
Simulation Results ◽  
Flow Theories ◽  
Volume Method ◽  
Die Extrusion

The mathematic model of 3D aluminum extrusion processes using finite volume method (FVM) was established in this paper. The basic theories and rigid-plastic flow theories of this model were researched and built. Non-orthogonal structured grids were used to match complex geometric boundaries and local refinement of grids was also realized. The collocated arrangement is used to discretize the governing equations on non-orthogonal grids directly, pressure oscillations bring by this arrangement and error caused by grid’s non-orthogonality is eliminated by special treatment. A pocket die extrusion process was simulated using the program developed in this paper. The simulation results were also compared with that simulated by FEM software Deform in the same process, material and die conditions. The feasibility and efficiency of the mathematic model built in this paper was demonstrated by the simulation results and the comparison.

Modeling and Testing of Linear Electric Servo System

2012 ◽  
Vol 241-244 ◽  
pp. 1411-1417
Author(s):  
Xue Jiao Zhao ◽  
Fan Lin
Keyword(s):  
Data Collection ◽  
Data Processing ◽  
Servo System ◽  
Mathematic Model ◽  
Simulation Results ◽  
Processing Steps

A mathematic model of the electric servo system was founded in this paper and several groups of data collection and data processing were executed to check up the model veracity. This paper described the data processing steps and analyzed the contrast of test and simulation results. This model is effectual to describe the performance of this kind of servo in respect that the results are mainly consentaneous.

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