Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Moti, Md Mahraj Murshalin Al, Uddin, Rafsan Shartaj, Anik, Abdul Hai, Saleh, Tanzim Bin
مؤلفون آخرون:	Alam, Md. Golam Rabiul
التنسيق:	أطروحة
اللغة:	English
منشور في:	Brac University 2021
الموضوعات:	Smart Grid Block-chain Price Forecasting Electricity demand and supply Smart Meter Reinforcement Learning Reinforcement learning.
الوصول للمادة أونلاين:	http://hdl.handle.net/10361/14968

id	10361-14968
record_format	dspace
spelling	10361-149682022-01-26T10:13:19Z Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment Moti, Md Mahraj Murshalin Al Uddin, Rafsan Shartaj Anik, Abdul Hai Saleh, Tanzim Bin Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Smart Grid Block-chain Price Forecasting Electricity demand and supply Smart Meter Reinforcement Learning Reinforcement learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 48-51). Electricity is deeply integrated into both our modern society and the economy. However, with our ever-growing society and increasing demand for electricity, the scarcity of resources is deeply felt through load shedding in most third world countries. Moreover, since most of the world depends on electricity systems built around more than 60 years ago, they are becoming increasingly inefficient and fail to solve the problems of modern-day global challenges. A Smart grid is an intelligent electricity network that allows efficient and optimal electricity distribution from source to consumers through smart integration of power technologies, information, and telecommunication through the existing system. The current system is a one-way interaction that only supplies electricity to consumers. That limits the ability to respond to the ever-changing and rising demands of society. However, smart grids allow the exchange of electricity and information between producers and customers. A smart home will communicate with the grid and allow consumers to manage electricity usage through a smart meter efficiently, and that will also efficiently manage electricity bills. Inside a smart home, the Home Area Network (HAN), will integrate all smart appliances into one energy management system so that these appliances can adjust the run schedule to lessen the demand on electricity at peak times, therefore, lowering bills. Reinforcement learning and a decentralized local market through block-chain can be used for electricity load and price forecasting. It is possible to fine-tune parameters to increase overall distribution and performance through efficient feature selection and feature extraction methods. The use of block-chain will connect prosumers and suppliers in a secure and decentralized system that will be used to forecast usage and bills. Also, through the use of reinforcement learning techniques and the block-chain’s information, it will be possible to analyze prosumer behavior. So, the integration of block-chain and smart grids will increase flexibility and scalability, leading to an overall optimized system. Md Mahraj Murshalin Al Moti Rafsan Shartaj Uddin Abdul Hai Anik Tanzim Bin Saleh B. Computer Science 2021-09-04T05:19:45Z 2021-09-04T05:19:45Z 2021 2021 Thesis ID 17101301 ID 17101311 ID 17101312 ID 17101310 http://hdl.handle.net/10361/14968 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 51 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Smart Grid Block-chain Price Forecasting Electricity demand and supply Smart Meter Reinforcement Learning Reinforcement learning.
spellingShingle	Smart Grid Block-chain Price Forecasting Electricity demand and supply Smart Meter Reinforcement Learning Reinforcement learning. Moti, Md Mahraj Murshalin Al Uddin, Rafsan Shartaj Anik, Abdul Hai Saleh, Tanzim Bin Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Alam, Md. Golam Rabiul
author_facet	Alam, Md. Golam Rabiul Moti, Md Mahraj Murshalin Al Uddin, Rafsan Shartaj Anik, Abdul Hai Saleh, Tanzim Bin
format	Thesis
author	Moti, Md Mahraj Murshalin Al Uddin, Rafsan Shartaj Anik, Abdul Hai Saleh, Tanzim Bin
author_sort	Moti, Md Mahraj Murshalin Al
title	Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
title_short	Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
title_full	Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
title_fullStr	Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
title_full_unstemmed	Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment
title_sort	reinforcement learning based electricity price forecasting in blockchain based smart grid environment
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/14968
work_keys_str_mv	AT motimdmahrajmurshalinal reinforcementlearningbasedelectricitypriceforecastinginblockchainbasedsmartgridenvironment AT uddinrafsanshartaj reinforcementlearningbasedelectricitypriceforecastinginblockchainbasedsmartgridenvironment AT anikabdulhai reinforcementlearningbasedelectricitypriceforecastinginblockchainbasedsmartgridenvironment AT salehtanzimbin reinforcementlearningbasedelectricitypriceforecastinginblockchainbasedsmartgridenvironment
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Reinforcement learning based electricity price forecasting in Blockchain based smart grid environment

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