• Title/Summary/Keyword: Smart Microgrid System

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Design and Implementation of Ethereum-based Future Power Trading System (이더리움 기반의 선물(Future) 전력 거래 시스템 설계)

  • Youm, Sungkwan;Lee, Heekwon;Shin, Kwang-Seong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.584-585
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    • 2021
  • As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

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Stochastic Gradient Descent Optimization Model for Demand Response in a Connected Microgrid

  • Sivanantham, Geetha;Gopalakrishnan, Srivatsun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.97-115
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    • 2022
  • Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

The Development of an Intelligent Home Energy Management System Integrated with a Vehicle-to-Home Unit using a Reinforcement Learning Approach

  • Ohoud Almughram;Sami Ben Slama;Bassam Zafar
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.87-106
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    • 2024
  • Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

Semantic Segmentation for Roof Extraction using Official Buildings Information (건물 통합 정보를 이용한 지붕 추출 의미론적 분류)

  • Youm, Sungkwan;Lee, Heekwon;Shin, Kwang-Seong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.582-583
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    • 2021
  • As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

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An Optimal Operation Model of A Centralized Micro-Energy Network (마이크로 에너지 네트워크의 중앙집중형 최적 운영 모델)

  • Lee, Ji-Hye;Kim, Hak-Man;Im, Young Hoon;Lee, Jae Yong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.10
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    • pp.1451-1457
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    • 2013
  • Recently, new concept of energy systems such as microgrid, smart grid, supergrid, and energy network has been introducing. In this paper, the concept of the centralized micro-energy network, which is an energy community of a building group without district heating system, is introduced. In addition, a mathematical model for optimal operation of the micro-energy network as a main function of an energy management system (EMS) for the micro-energy network is proposed. In order to show the validation, the proposed model is tested through the simulation and analyzed.

The Novel Configuration of Integrated Network for Building Energy System (빌딩 에너지시스템 통합네트워크 구축에 관한 연구)

  • Hong, Won-Pyo
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2008.10a
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    • pp.229-234
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    • 2008
  • The new millennium has started with several innovations driven by fast evolution of the technologies in energy sector. A strong impulse towards the diffusion of new economical efficient technologies regulatory incentives related to energy production from renewable source and a small scale building trigeneration and to promotion of more sustainable environmental-friendly generation solutions, the evolution of electricity markets, more and more binding local emission constraints, and the need for improving the security of supply to reduce the energy system vulnerability. The 24 percentage energy quantify of total energy consumption consumes in commercial buildings and residential houses and the 30% portion of total $CO_2$ emissions covers also in the commercial buildings and residential houses sector. To cope with efficiently this energy sinuation in building sector, Building microgrid or building tooling, heating & power(BCHP) system has been interested in recent day due to meeting thermal and electric energy requirements efficiently and with appropriate energy quality. A multi agent system is a collective of intelligent agents that communicate with each other and work cooperatively to achieve common goals. Also, it is to medicate and coordinate communication between Control Areas and Security Coordinators for teal-time control of the BCHP system and the power pid. In this new circumstance, it is very important to integrate the power and energy delivery system and the information system(communication, networks, and intelligent equipment) that controls it. Therefore, development of smart control modules with open communication protocol and seamlessly interchange the data and information between control network and data network including extranet and intranet give a great meanings. We designed and developed the TCP/IP-CAN IED agent modules and ModBus./LonTalk/(TCP/IP) IED agent ones to configure the multi-agent system based smart energy network of commercial buildings and also intelligent algorithms for inverter fault diagnostics which ran be operated in control level or agent level network.

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A Study of Monitoring and Operation for PEM Water Electrolysis and PEM Fuel Cell Through the Convergence of IoT in Smart Energy Campus Microgrid (스마트에너지캠퍼스 마이크로그리드에서 사물인터넷 융합 PEM 전기분해와 PEM 연료전지 모니터링 및 운영 연구)

  • Chang, Hui Il;Thapa, Prakash
    • Journal of the Korea Convergence Society
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    • v.7 no.6
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    • pp.13-21
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    • 2016
  • In this paper we are trying to explain the effect of temperature on polymer membrane exchange water electrolysis (PEMWE) and polymer membrane exchange fuel cell (PEMFC) simultaneously. A comprehensive studying approach is proposed and applied to a 50Watt PEM fuel cell system in the laboratory. The monitoring process is carried out through wireless LoRa node and gateway network concept. In this experiment, temperature sensor measure the temperature level of electrolyzer, fuel cell stack and $H_2$ storage tank and transmitted the measured value of data to the management control unit (MCU) through the individual node and gateway of each PEMWE and PEMFC. In MCU we can monitor the temperature and its effect on the performance of the fuel cell system and control it to keep the lower heating value to increase the efficiency of the fuel cell system. And we also proposed a mathematical model and operation algorithm for PEMWE and PEMFC. In this model, PEMWE gives higher efficiency at lower heating level where as PEMFC gives higher efficiency at higher heating value. In order to increase the performance of the fuel cell system, we are going to monitor, communicate and control the temperature and pressure of PEMWE and PEMFC by installing these systems in a building of university which is located in the southern part of Korea.