scholarly journals Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

2020 ◽  
Vol 12 (14) ◽  
pp. 5561 ◽  
Author(s):  
Bhagya Nathali Silva ◽  
Murad Khan ◽  
Kijun Han
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Management Strategies ◽  
Peak Load ◽  
Critical Discussion ◽  
Future Research ◽  
Smart Environments ◽  
Challenges And Opportunities ◽  
Management Approaches

The emergence of the Internet of Things (IoT) notion pioneered the implementation of various smart environments. Smart environments intelligibly accommodate inhabitants’ requirements. With rapid resource shrinkage, energy management has recently become an essential concern for all smart environments. Energy management aims to assure ecosystem sustainability, while benefiting both consumers and utility providers. Although energy management emerged as a solution that addresses challenges that arise with increasing energy demand and resource deterioration, further evolution and expansion are hindered due to technological, economical, and social barriers. This review aggregates energy management approaches in smart environments and extensively reviews a variety of recent literature reports on peak load shaving and demand response. Significant benefits and challenges of these energy management strategies were identified through the literature survey. Finally, a critical discussion summarizing trends and opportunities is given as a thread for future research.

scholarly journals Comprehensive Imaging Characterization of Colorectal Liver Metastases

2021 ◽  
Vol 11 ◽  
Author(s):  
Drew Maclean ◽  
Maria Tsakok ◽  
Fergus Gleeson ◽  
David J. Breen ◽  
Robert Goldin ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Imaging Techniques ◽  
Management Strategies ◽  
Disease Assessment ◽  
Future Research ◽  
Phenotypic Characterisation ◽  
Challenges And Opportunities ◽  
Advanced Analysis

Colorectal liver metastases (CRLM) have heterogenous histopathological and immunohistochemical phenotypes, which are associated with variable responses to treatment and outcomes. However, this information is usually only available after resection, and therefore of limited value in treatment planning. Improved techniques for in vivo disease assessment, which can characterise the variable tumour biology, would support further personalization of management strategies. Advanced imaging of CRLM including multiparametric MRI and functional imaging techniques have the potential to provide clinically-actionable phenotypic characterisation. This includes assessment of the tumour-liver interface, internal tumour components and treatment response. Advanced analysis techniques, including radiomics and machine learning now have a growing role in assessment of imaging, providing high-dimensional imaging feature extraction which can be linked to clinical relevant tumour phenotypes, such as a the Consensus Molecular Subtypes (CMS). In this review, we outline how imaging techniques could reproducibly characterize the histopathological features of CRLM, with several matched imaging and histology examples to illustrate these features, and discuss the oncological relevance of these features. Finally, we discuss the future challenges and opportunities of CRLM imaging, with a focus on the potential value of advanced analytics including radiomics and artificial intelligence, to help inform future research in this rapidly moving field.

Exploring undergraduates’ money-management life: insight from an emerging economy

2019 ◽  
Vol 20 (3) ◽  
pp. 167-189 ◽  
Author(s):  
Vilani Sachitra ◽  
Dinushi Wijesinghe ◽  
Wajira Gunasena
Keyword(s):  
Financial Literacy ◽  
Psychological Factors ◽  
Management Strategies ◽  
The Body ◽  
Future Research ◽  
Money Management ◽  
Content Type ◽  
Financial Decisions ◽  
Management Behaviour ◽  
Management Approaches

Purpose Undergraduates are expected to be future leaders responsible for business and nations. Given that sound financial decision-making is critical to their success in their careers and lives, it is important to understand the money-management behaviour of undergraduates. In the context of developing countries, the body of knowledge on money-management behaviour is dominated by functional financial literature and there is little research on factors beyond this. This study aims to fill this gap by exploring economic, social and psychological factors that influence money-management behaviour of undergraduates in a developing nation (Sri Lanka) and how undergraduates respond to these influences. Design/methodology/approach The study used a qualitative exploratory approach. Data collection was carried out using focus group discussions and individual interviews amongst undergraduates in a leading Sri Lankan state university. Findings The results indicate that undergraduates adopted both careful and risky money-management approaches. The subthemes, specifically identified under economic, social and psychological factors, revealed how undergraduates responded to each of these factors and the influence of contextual and cultural differences in their money-management behaviour. Research limitations/implications Findings of the study revealed the importance of promoting innovative educational strategies to change the dependability mindset of undergraduates and to promote stress-management strategies that will assist them to enhance their personalities and creativity in making financial decisions. Theoretical and practical implications and future research directions are provided. Originality/value The literature scores in developing context are limited to exploring the existing pattern and the levels of the functional financial literacy. This study has deepened the authors’ understanding of how the developing context affects undergraduates’ response to the factors relating to their money-management behaviour. The findings from this study will be useful to government, financial institutions, educational institutions, parents and those who have a keen interest in encouraging healthy money-management behaviour in undergraduates.

scholarly journals System-Theoretic Process Analysis (STPA) for Hazard Analysis in Complex Systems: The Case of “Demand-Side Management in a Smart Grid”

Systems ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 33 ◽  
Author(s):  
Stylianos Karatzas ◽  
Athanasios Chassiakos
Keyword(s):  
Smart Grid ◽  
Complex Systems ◽  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Process Analysis ◽  
Hazard Analysis ◽  
Energy Market ◽  
System Modelling ◽  
Home Energy Management

Inelasticity of demand along with the distributed energy sources and energy market democratization pose significant challenges which have considerable negative impacts on overall grid balance. The need for increased capacity and flexibility in the era of energy market digitalization has introduced new requirements in the energy supply network which could not be satisfied without continuous and costly local power network upgrades. Additionally, with the emergence of Smart Homes (SHs) and Home Energy Management (HEM) systems for monitoring and operating household appliances, opportunities have arisen for automated Demand Response (DR). DR is exploited for the modification of the consumer energy demand, in response to the specific conditions within the electricity system (e.g., peak period network congestion). In order to optimally integrate DR in the broader Smart Grid (SG) system, modelling of the system parameters and safety analysis is required. In this paper, the implementation of STPA (System-Theoretic Process Analysis) structured method, as a relatively new hazard analysis technique for complex systems is presented and the feasibility of STPA implementation for loss prevention on a Demand Response system for home energy management, and within the complex SG context, is examined. The applied method delivers a mechanism useful in understanding where gaps in current operational risk structures may exist. The STPA findings in terms of loss scenarios can be used to generate a variety of safeguards to ensure secure operational control and in implementing targeted strategies through standard approaches of risk assessment.

scholarly journals A Survey of Communications and Networking Technologies for Energy Management in Buildings and Home Automation

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Aravind Kailas ◽  
Valentina Cecchi ◽  
Arindam Mukherjee
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Energy Management ◽  
Smart Grids ◽  
Energy Demand ◽  
Demand Curve ◽  
Future Research ◽  
Energy Awareness ◽  
Home Energy Management ◽  
Networking Technologies

With the exploding power consumption in private households and increasing environmental and regulatory restraints, the need to improve the overall efficiency of electrical networks has never been greater. That being said, the most efficient way to minimize the power consumption is by voluntary mitigation of home electric energy consumption, based on energy-awareness and automatic or manual reduction of standby power of idling home appliances. Deploying bi-directional smart meters and home energy management (HEM) agents that provision real-time usage monitoring and remote control, will enable HEM in “smart households.” Furthermore, the traditionally inelastic demand curve has began to change, and these emerging HEM technologies enable consumers (industrial to residential) to respond to the energy market behavior to reduce their consumption at peak prices, to supply reserves on a as-needed basis, and to reduce demand on the electric grid. Because the development of smart grid-related activities has resulted in an increased interest in demand response (DR) and demand side management (DSM) programs, this paper presents some popular DR and DSM initiatives that include planning, implementation and evaluation techniques for reducing energy consumption and peak electricity demand. The paper then focuses on reviewing and distinguishing the various state-of-the-art HEM control and networking technologies, and outlines directions for promoting the shift towards a society with low energy demand and low greenhouse gas emissions. The paper also surveys the existing software and hardware tools, platforms, and test beds for evaluating the performance of the information and communications technologies that are at the core of future smart grids. It is envisioned that this paper will inspire future research and design efforts in developing standardized and user-friendly smart energy monitoring systems that are suitable for wide scale deployment in homes.

scholarly journals Opportunities and Challenges in Studies of Host-Pathogen Interactions and Management of Verticillium dahliae in Tomatoes

Plants ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1622
Author(s):  
Bhupendra Acharya ◽  
Thomas W. Ingram ◽  
YeonYee Oh ◽  
Tika B. Adhikari ◽  
Ralph A. Dean ◽  
...  
Keyword(s):  
Verticillium Wilt ◽  
Verticillium Dahliae ◽  
Current Knowledge ◽  
Management Strategies ◽  
Future Research ◽  
Broad Host Range ◽  
Pathogen Virulence ◽  
Solanum Lycopersicum L ◽  
Worldwide Distribution ◽  
Management Approaches

Tomatoes (Solanum lycopersicum L.) are a valuable horticultural crop that are grown and consumed worldwide. Optimal production is hindered by several factors, among which Verticillium dahliae, the cause of Verticillium wilt, is considered a major biological constraint in temperate production regions. V. dahliae is difficult to mitigate because it is a vascular pathogen, has a broad host range and worldwide distribution, and can persist in soil for years. Understanding pathogen virulence and genetic diversity, host resistance, and plant-pathogen interactions could ultimately inform the development of integrated strategies to manage the disease. In recent years, considerable research has focused on providing new insights into these processes, as well as the development and integration of environment-friendly management approaches. Here, we discuss the current knowledge on the race and population structure of V. dahliae, including pathogenicity factors, host genes, proteins, enzymes involved in defense, and the emergent management strategies and future research directions for managing Verticillium wilt in tomatoes.

scholarly journals An Innovative Stochastic Multi-Agent-Based Energy Management Approach for Microgrids Considering Uncertainties

Inventions ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 37 ◽  
Author(s):  
Sajad Ghorbani ◽  
Rainer Unland ◽  
Hassan Shokouhandeh ◽  
Ryszard Kowalczyk
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Search Algorithm ◽  
Renewable Energy Sources ◽  
Management Approach ◽  
Agent Based ◽  
Multi Agent ◽  
Power Outputs ◽  
Microgrid Energy Management

In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt with properly. This paper presents a multi-agent-based energy management approach for a non-isolated microgrid with solar and wind units and in the presence of demand response, considering uncertainty in generation and load. More specifically, a modified version of the lightning search algorithm, along with the weighted objective function of the current microgrid cost, based on different scenarios for the energy management of the microgrid, is proposed. The probability density functions of the solar and wind power outputs, as well as the demand of the households, have been used to determine the amount of uncertainty and to plan various scenarios. We also used a particle swarm optimization algorithm for the microgrid energy management and compared the optimization results obtained from the two algorithms. The simulation results show that uncertainty in the microgrid normally has a significant effect on the outcomes, and failure to consider it would lead to inaccurate management methods. Moreover, the results confirm the excellent performance of the proposed approach.

Lean Management and Supply Chain Management

2014 ◽  
pp. 304-337 ◽  
Author(s):  
Pedro J. Martínez-Jurado ◽  
José Moyano-Fuentes
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Management Strategies ◽  
Future Research ◽  
Lean Management ◽  
Chain Management ◽  
Main Research ◽  
Lean Principles ◽  
Aerospace Sector ◽  
Challenges And Opportunities

This chapter evaluates the state-of-the-art of research on Lean Management and Supply Chain Management strategies in the aerospace sector using Systematic Literature Review methodology. The complementary aims are: a) to identify the topic set studied and to propose a criterion for classifying the literature, and b) to discuss the empirical evidence that identifies existing interrelationships. The analysis has enabled three main topics to be identified: a) adoption and implementation of lean management, b) development of supply chain management, and c) deployment of lean principles and practices across the supply chain. A number of more specific lines of research are also proposed that have been assigned to each of these three main research topics. Finally, a set of challenges and opportunities for future research are set out, along with a range of academic and professional implications that could be useful not only for the aerospace sector but also for other industrial sectors that share similar contingent factors.

scholarly journals Forecasting Algorithms and Optimization Strategies for Building Energy Management & Demand Response

Proceedings ◽  
2018 ◽  
Vol 2 (15) ◽  
pp. 1133 ◽  
Author(s):  
Fanlin Meng ◽  
Kui Weng ◽  
Balsam Shallal ◽  
Xiangping Chen ◽  
Monjur Mourshed
Keyword(s):  
Machine Learning ◽  
Energy Management ◽  
Demand Response ◽  
Learning Algorithms ◽  
Building Energy ◽  
Machine Learning Algorithms ◽  
Future Research ◽  
Research Directions ◽  
Building Energy Management ◽  
Future Research Directions

In this paper, we look at the key forecasting algorithms and optimization strategies for the building energy management and demand response management. By conducting a combined and critical review of forecast learning algorithms and optimization models/algorithms, current research gaps and future research directions and potential technical routes are identified. To be more specific, ensemble/hybrid machine learning algorithms and deep machine learning algorithms are promising in solving challenging energy forecasting problems while large-scale and distributed optimization algorithms are the future research directions for energy optimization in the context of smart buildings and smart grids.

Sign in / Sign up

Export Citation Format

Share Document