Cooperative energy management for a cluster of households prosumers

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe increment of electrical and electronic appliances for improving the lifestyle of residential consumers had led to a larger demand of energy. In order to supply their energy requirements, the consumers have changed the paradigm by integrating renewable energy sources to their power grid. Therefore, consumers become prosumers in which they internally generate and consume energy looking for an autonomous operation. This paper proposes an energy management system for coordinating the operation of distributed household prosumers. It was found that better performance is achieved when cooperative operation with other prosumers in a neighborhood environment is achieved. Simulation and experimental results validate the proposed strategy by comparing the performance of islanded prosumers with the operation in cooperative modePeer ReviewedPostprint (author's final draft

using thermal inertia of buildings with phase change material for demand response

Abstract: In recent years, demand response programs have proved useful in managing peak demand and meeting sustainability goals, enabling an efficient use of the smart grid. Heating, ventilation, and air conditioning (HVAC) loads in buildings constitute a large proportion of the total energy consumption of households, and accordingly, a flexible and efficient operation of these devices can aid power utilities in meeting load management objectives while reducing consumer's electricity bills. With the emergence of promising new technologies, such as phase change materials (PCM), buildings can serve as a virtual thermal energy storage, which improves energy efficiency and also allows occupants to offer grid services like peak demand reduction. The objective of this paper is to establish the effectiveness of PCM as a demand response resource, demonstrating the extent to which it can be used for peak demand reduction. A wide range of scenarios are considered to investigate the impacts of geographical location, PCM melting point, duration of precooling and preheating, setting points of HVAC system, thickness and location of PCM, on the capability of the PCM in reducing or shifting the cooling and heating load. All simulations are performed using the EnergyPlus platform, examining typical residential buildings in five Australian cities: Brisbane, Sydney, Melbourne, Hobart and Perth. The simulation results showed a decrease in the HVAC demand in the buildings with PCM, in all cities, with the highest reductions observed in Hobart and Melbourne. The integration of a 20mm thick PCM in the roof, wall and floor of the building yielded a 21.8% and 16.7% reduction in annual HVAC demand in Hobart and Melbourne respectively, when compared to the building without PCM. However, this is with the assumption that the HVAC system is operating 24 hours a day for a whole year. The PCM-integrated building showed a shift in the HVAC demand in all cities except Perth. A shift by 9 minutes, 3 minutes, 60 minutes and 103 minutes was recorded in the cities of Brisbane, Sydney, Melbourne and Hobart respectively. The simulation results will be used in subsequent research to schedule the HVAC demand using a home energy management system

Design and Construction of Voice Controlled Smart Power Strip

This paper focuses on voice control for smart power strips, which constitutes the crux of the study. As technology develops, it is obvious that there is a swift increase in the development of smart homes. This is why the project is important because it combines voice control with a secure biometric activator and a wireless connection between the voice control system and the power strip. Through a combination of programming, in-depth research, simulations and analysis of the results, the proposed technique exhibited better performance than the current techniques. The voice recognition module sends signals to the first transceiver, which acts as the transmitter, and from there, to the second transceiver, which acts as the receiver. Finally, the signal is sent to the relay module, which controls the socke

Proposal For 6LoWPAN Wireless Network Protocol-Based Street-Light-As-A-Service (SLaaS) Framework To Power Campus Parking Services

A novel IPv6 Over Low Power Wireless Personal Area Network (6LoWPAN) protocol-based Street-Light-As-A-Service (SLaaS) research framework for an integrated cloud-based smart university campus parking platform is being proposed. The Intelligent Connected Street Light infrastructure currently in existence at University Sains Malaysia (USM) is being redesigned. As part of overall parking proposal, approaching object image and video data are being acquired using a range of sensors, including the  passive infrared (PIR) and 3-D Light Detection and Ranging (LIDAR) motion sensors. To acquire and transmit vehicle instrumentation data, ELM327 Onboard Diagnostics 2 (OBD-II) Wi-Fi adapter is being used. For edge computing-based intelligent object detection model processing to synchronize license plate and facial recognition data with USM databases, Nvidia® Jetson Nano is being used. The framework is developed to effect multiple services, including to track and manage university vehicles, to detect and secure pedestrian movement, to trigger lighting commands based on approaching vehicle movement for on-demand parking illumination, to partition digital bounding box perimeter to predict potential vehicle collisions, to detect unregistered and excessive parking time to monitor unattended and illegal vehicles, to enable street-light-located parking-related kiosk services, and consolidate cloud-based human and vehicle data analytics into mobile form-factor dashboards. The proposed design will be evaluated and validated for end-to-end average data propagation rate, data integrity, object-to-human and object-to-vehicle synchronization success rate, electrical power consumption reduction and potential surface attack mitigation and avoidance throughout the network

Smart House Controlling system for Time Critical Appliances Controlling Smart House system with ease Real Time Appliances

The problem of power consumption sounding an audible siren, only the solution is just a modern system would help. The "smart house" concept is a sample of what can be done with home automation these days, and why it's worth doing. The fundamental goal of Smart House is to provide integrated wiring for all current home services and to include provisions for home automation technology. Smart House is promoted for the following major home automation applications: entertainment, lighting, HVAC control, interface between an existing security system and a Smart House control panel. I have been effectively proving by considering both energy consumption and generation. By using of controlling system automatic performances are performed in the Smart house. This system utilizes different sensors to control household appliances. This system also provides the ability to perform automation on smart load controls based on utility signals to the user, customer‘s preference and load priority signals received from HMs. It provides user to know the Demand of the appliances using wireless technology Bluetooth. Consideration of any power cuts or failing of main supplies will switch to the solar system

PEMODELAN MANAJEMEN ENERGI DENGAN KURVA BEBAN LISTRIK MENGGUNAKAN SISTEM FUZZY LOGIC PADA KONSUMEN LISTRIK PERKANTORAN

Mengingat kebutuhan energi listrik yang terus meningkat, diperlukan pola detail penggunaan listrik, untuk mengubah suatu penggunaaan konsumen kelistrikan dan mengurangi konsumsi energi global. Dalam pengelolaan suatu energi, pembebanan listrik diperlukan untuk mengatur jika terjadi peningkatan suatu beban di sektor kelistrikan. Hal ini bertujuan, kurva beban listrik dapat mendeteksi suatu beban puncak dari penggunaan energi yang berlebihan. Penelitian ini, merupakan metode kecerdasan buatan fuzzy logic untuk mengolah suatu aturan variabel input dan menghasilkan sebuah konsumsi energi yang telah dipakai. Pada konsumsi energi yang dihasilkan, kurva beban listrik dipengaruhi oleh suatu faktor variabel seperti periode penggunaan peralatan dan jumlah penghuni. Data input yang digunakan untuk sistem fuzzy logic ini adalah data aktual periode penggunaan waktu peralatan yang dipakai setiap hari dan data input jumlah penghuni memakai peralatan. Dari hasil yang didapatkan, tingkat akurasi antara data aktual dan data fuzzy logic akan diperoleh dari nilai mean absolute percentage error (MAPE). Diharapkan penelitian ini dapat menjadi suatu pemodelan sistem pendeteksi energi listrik pada tempat tinggal atau perkantoran, karena akan memudahkan dalam pemakaian energi suatu peralatan. Remembering the increasing demand for electrical energy, a detailed pattern of electricity use is needed to change a consumer's use of electricity and reduce global energy consumption. In the management of an energy, electrical loading is needed to regulate if there is an increase in a load in the electricity sector. This is intended, through the electrical load curve to detect a peak load from excessive energy use. This research is about fuzzy logic artificial intelligence method to process a rule of input variables and produce an energy consumption that has been used. In the resulting energy consumption, the electric load curve is influenced by a variable factor such as the period of use of the equipment and the number of occupants. The input data used for this fuzzy logic system is the actual data for the period of time used for the equipment used every day and the input data for the number of occupants using the equipment. From the results obtained, the level of accuracy between the actual data and fuzzy logic data will be obtained from the mean absolute percentage error (MAPE). And hoped this research can be a modeling of an electrical energy detection system in a residence or office, because it will facilitate the use of energy in an equipment

Power fluctuation control on a DC-residential network using Tanaka's Optimization and Tabu Search Approach

The power fluctuation problem of renewable energy sources, frequency and voltage deviations are usually occurred in the isolated power systems, in which the ability to maintain stable supply-demand balance is low. Smart grid system is a solution to this problem and because of that the idea of smart grid concept is proposed which cooperatively could balance the supply-demand between power supply side and power demand side. The installation of photovoltaic (PV) system is proposed in a residential building which can be straight forwardly connected to DC sources. DC systems are required to bring lower costs by elimination of inverter and rectifier circuits and it may be possible to operate the PV system with high efficiency. Therefore, this study presents a DC smart grid system for a small residential network that sourced by solar energy which consist of a PV generator, a solar collector (SC), a heat pump (HP) and a battery. Battery and heat pump are used as controllable loads. Then, in order to minimize the interconnection, point power flow fluctuations and its operational cost, Tanaka’s Optimization and Tabu Search Approach is employed. Tanaka’s Optimization is used to obtain the optimal operation of thermal unit and controllable loads. Meanwhile, Tabu Search approach helps to control the power consumption of controllable load and discharge and/or charge output of the battery. From the results it has been found that the interconnection point power flow in the smart house could be controlled within the given bandwidth from the power reference. By smoothing the interconnection point of power flow, the electricity cost could be reduced due to reduction of contract fee with the electricity power company. Consequently, we can expect high quality power supply, higher efficiency of power transfer and lower CO₂ emissions