scholarly journals A multi-level optimization technique for electricity consumption management and pricing in residential neighborhoods

2021 ◽  
Author(s):  
Ramyar Rashed Mohassel
Keyword(s):  
Smart Grids ◽  
New Technologies ◽  
Power Transmission ◽  
Optimization Technique ◽  
Electricity Consumption ◽  
Optimization Method ◽  
Residential Neighborhood ◽  
Upper Level ◽  
Advanced Metering ◽  
Power Management Unit

With the introduction of new technologies, concepts and approaches in power transmission, distribution and utilization such as Smart Grids (SG), Advanced Metering Infrastructures (AMI), Distributed Energy Resources (DER) and Demand Side Management (DSM), new capabilities have emerged that enable efficient use and management of power consumption. These capabilities are applicable at micro level in households and building complexes as well as at macro level for utility providers in form of resource and revenue management initiatives. On the other hand, integration of Information Technology (IT) and instrumentation has brought Building Management Systems (BMS) to our homes and has made it possible for the ordinary users to take advantage of more complex and sophisticated energy and cost management features as an integral part of their BMS. The idea of combining capabilities and advantages offered by SG, AMI, DER, DSM and BMS is the backbone of this thesis and has resulted in developing a unique, two-level optimization method for effective deployment of DSM at households and residential neighborhoods. The work consists of an optimization algorithm for households to maximize utilization of DER as the lower level of the envisioned two-level optimization technique while using a customized Game Theoretic optimization for optimizing revenue of utility providers for residential neighborhood as the upper level. This work will also introduce a power management unit, called Load Moderation Center (LMC), to host the developed optimization algorithms as an integrated part of BMS. LMC, upon successful completion, will be able to automatically plan consumption, effectively utilize available sources including grid, renewable energies and storages, and eliminate the need for residences to manually program their BMS for different market scenarios.

scholarly journals A multi-level optimization technique for electricity consumption management and pricing in residential neighborhoods

2021 ◽  
Author(s):  
Ramyar Rashed Mohassel
Keyword(s):  
Smart Grids ◽  
New Technologies ◽  
Power Transmission ◽  
Optimization Technique ◽  
Electricity Consumption ◽  
Optimization Method ◽  
Residential Neighborhood ◽  
Upper Level ◽  
Advanced Metering ◽  
Power Management Unit

With the introduction of new technologies, concepts and approaches in power transmission, distribution and utilization such as Smart Grids (SG), Advanced Metering Infrastructures (AMI), Distributed Energy Resources (DER) and Demand Side Management (DSM), new capabilities have emerged that enable efficient use and management of power consumption. These capabilities are applicable at micro level in households and building complexes as well as at macro level for utility providers in form of resource and revenue management initiatives. On the other hand, integration of Information Technology (IT) and instrumentation has brought Building Management Systems (BMS) to our homes and has made it possible for the ordinary users to take advantage of more complex and sophisticated energy and cost management features as an integral part of their BMS. The idea of combining capabilities and advantages offered by SG, AMI, DER, DSM and BMS is the backbone of this thesis and has resulted in developing a unique, two-level optimization method for effective deployment of DSM at households and residential neighborhoods. The work consists of an optimization algorithm for households to maximize utilization of DER as the lower level of the envisioned two-level optimization technique while using a customized Game Theoretic optimization for optimizing revenue of utility providers for residential neighborhood as the upper level. This work will also introduce a power management unit, called Load Moderation Center (LMC), to host the developed optimization algorithms as an integrated part of BMS. LMC, upon successful completion, will be able to automatically plan consumption, effectively utilize available sources including grid, renewable energies and storages, and eliminate the need for residences to manually program their BMS for different market scenarios.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals A Data Analytics/Big Data Framework for Advanced Metering Infrastructure Data

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5650
Author(s):  
Jenniffer S. Guerrero-Prado ◽  
Wilfredo Alfonso-Morales ◽  
Eduardo F. Caicedo-Bravo
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart Grids ◽  
Data Analytics ◽  
Electricity Consumption ◽  
Advanced Metering Infrastructure ◽  
Data Interoperability ◽  
Architecture Model ◽  
Data Framework ◽  
Advanced Metering

The Advanced Metering Infrastructure (AMI) data represent a source of information in real time not only about electricity consumption but also as an indicator of other social, demographic, and economic dynamics within a city. This paper presents a Data Analytics/Big Data framework applied to AMI data as a tool to leverage the potential of this data within the applications in a Smart City. The framework includes three fundamental aspects. First, the architectural view places AMI within the Smart Grids Architecture Model-SGAM. Second, the methodological view describes the transformation of raw data into knowledge represented by the DIKW hierarchy and the NIST Big Data interoperability model. Finally, a binding element between the two views is represented by human expertise and skills to obtain a deeper understanding of the results and transform knowledge into wisdom. Our new view faces the challenges arriving in energy markets by adding a binding element that gives support for optimal and efficient decision-making. To show how our framework works, we developed a case study. The case implements each component of the framework for a load forecasting application in a Colombian Retail Electricity Provider (REP). The MAPE for some of the REP’s markets was less than 5%. In addition, the case shows the effect of the binding element as it raises new development alternatives and becomes a feedback mechanism for more assertive decision making.

scholarly journals Quality Control Methods for Advanced Metering Infrastructure Data

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 195-203
Author(s):  
Eric Garrison ◽  
Joshua New
Keyword(s):  
Quality Control ◽  
Missing Values ◽  
Electricity Consumption ◽  
Empirical Validation ◽  
Advanced Metering Infrastructure ◽  
Building Energy Modeling ◽  
Building Type ◽  
Industry Standard ◽  
Advanced Metering ◽  
Electrical Consumption

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

Well Placement Technique and Production Optimization for Mature Field - A Case Study of L-X Field

2020 ◽  
Vol 46 ◽  
pp. 168-179
Author(s):  
Patrick Nwafor ◽  
Kelani Bello
Keyword(s):  
Oil And Gas ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Oil And Gas Industry ◽  
Optimization Method ◽  
Simulation Software ◽  
Production Optimization ◽  
Direct Optimization ◽  
Well Placement ◽  
Local Optimal Solution

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.

scholarly journals A Comprehensive Survey on Cyber-Physical Smart Grid Testbed Architectures: Requirements and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1043
Author(s):  
Abdallah A. Smadi ◽  
Babatunde Tobi Ajao ◽  
Brian K. Johnson ◽  
Hangtian Lei ◽  
Yacine Chakhchoukh ◽  
...  
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Smart Grids ◽  
Data Exchange ◽  
Information Technologies ◽  
New Technologies ◽  
Rapid Development ◽  
Environmental Benefits ◽  
Future Research ◽  
Time Data

The integration of improved control techniques with advanced information technologies enables the rapid development of smart grids. The necessity of having an efficient, reliable, and flexible communication infrastructure is achieved by enabling real-time data exchange between numerous intelligent and traditional electrical grid elements. The performance and efficiency of the power grid are enhanced with the incorporation of communication networks, intelligent automation, advanced sensors, and information technologies. Although smart grid technologies bring about valuable economic, social, and environmental benefits, testing the combination of heterogeneous and co-existing Cyber-Physical-Smart Grids (CP-SGs) with conventional technologies presents many challenges. The examination for both hardware and software components of the Smart Grid (SG) system is essential prior to the deployment in real-time systems. This can take place by developing a prototype to mimic the real operational circumstances with adequate configurations and precision. Therefore, it is essential to summarize state-of-the-art technologies of industrial control system testbeds and evaluate new technologies and vulnerabilities with the motivation of stimulating discoveries and designs. In this paper, a comprehensive review of the advancement of CP-SGs with their corresponding testbeds including diverse testing paradigms has been performed. In particular, we broadly discuss CP-SG testbed architectures along with the associated functions and main vulnerabilities. The testbed requirements, constraints, and applications are also discussed. Finally, the trends and future research directions are highlighted and specified.

Optimization Design of an Axial-Flow Fan Used in Local Ventilation in Mining Industry

2011 ◽  
Author(s):  
Dhaval Desai ◽  
Jiang Zhou
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Mining Industry ◽  
Axial Flow ◽  
Optimization Method ◽  
Low Noise ◽  
Design Constraint ◽  
Engineering Research ◽  
Blade Element Theory ◽  
Local Ventilation

In a world where the increasing demand on developing energy-efficient systems is probably the most stringent design constraint, the trend in engineering research in recent years has been to optimize the existing technologies rather than to implement new ones. The present work addresses a robust axial-type fan design technique developed using an optimization technique. A fan is indispensable equipment for primary and local ventilation in mining industries. We always pursue the fan with high working efficiency and low noise. In this paper, an optimization method is developed to improve the pneumatic properties of the fan based on the blade element theory. A new type of fan used in local ventilation is designed with the help of computer. It is shown that the new design enhanced the efficient up to 88%. Numerical analysis is also conducted to validate the optimization design results.

scholarly journals An enhanced krill herd optimization technique used for classification problem

2021 ◽  
Vol 30 (2) ◽  
pp. 354-364
Author(s):  
Firas Al-Mashhadani ◽  
Ibrahim Al-Jadir ◽  
Qusay Alsaffar
Keyword(s):  
Machine Learning ◽  
Simulated Annealing ◽  
Optimization Technique ◽  
Optimization Method ◽  
Classification Problem ◽  
Test Results ◽  
Internal Evaluation ◽  
Evaluation Measures ◽  
Search Optimization ◽  
Krill Herd

In this paper, this method is intended to improve the optimization of the classification problem in machine learning. The EKH as a global search optimization method, it allocates the best representation of the solution (krill individual) whereas it uses the simulated annealing (SA) to modify the generated krill individuals (each individual represents a set of bits). The test results showed that the KH outperformed other methods using the external and internal evaluation measures.

scholarly journals Smart grids, prosumers and energy management within a smart city integrated system

2020 ◽  
Vol 14 (1) ◽  
pp. 1121-1134
Author(s):  
Marco Savastano ◽  
Marta-Christina Suciu ◽  
Irina Gorelova ◽  
Gheorghe-Alexandru Stativă
Keyword(s):  
Smart Grids ◽  
Smart Cities ◽  
Electricity Consumption ◽  
Energy Transition ◽  
Integrated System ◽  
Renewable Sources ◽  
Electricity Grid ◽  
New Type ◽  
Alternative Sources ◽  
Energy Prosumers

AbstractDue to a significant increase in electricity consumption globally, governments have to look and to identify better, more efficient and effective alternatives and sustainable energy sources to meet this high demand. This becomes more and more important in the context of implementing modern approaches such as those that might be applied in cases of smart cities and cultural and creative communities. Electricity can be produced based on conventional sources, but also on an emergent use of renewable sources. The electricity grid is usually designed as unidirectional. We consider that in case of smart cities and creative-innovative communities there is a need to implement mostly new smart grids that are bidirectional. This may allow and support the emergency of a new type of electricity user, called “prosumers”, who produces electricity from renewable sources, next uses & shares them smartly within the smart grid and finally stores them. Globally, photovoltaic energy prosumers are considered one of the most important actors in the energy transition and seem to be ready to introduce significant amounts of electricity within the grid. We anticipate that people living in households in smart cities and communities among most regions of the world will tend in the future to improve their self-consumption from the production of smart energy. This paper supports the idea that using mostly electricity from renewable alternative sources, especially solar, can be also developed with the help of households acting within smart cities and communities. The paper will also present briefly an overview of the scientific literature dedicated to this topic. We will also provide further interesting insights through a number of case studies representing good practices regarding prosumers in Italy and Romania.

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