Time programmable smart devices for peak demand reduction of smart homes in a microgrid

Abstract: Increasing electricity access through Microgrids for rural areas is often faced with the challenge of increased peak demand through increased electricity demand as more electronic devices will be acquired by the consumers and more small businesses will spring up in the community. If not taken care of, this leads to additional cost of incurring higher peaker plants to meet the peak demand, and the burden of the cost of peaker plants are consequentially transferred to the consumers. Since this load is generated by the consumers, it is most desirable to control the peak demand from the consumers’ side. Therefore, a method of Time Programmable Smart Devices (TPSD) with an efficient Electricity Use Plan (EUP) is proposed in this paper by introducing appliance working knowledge and improving load shifting technique of Demand Side Management for peak demand reduction in a rural Microgrid. This method yielded lower morning and evening peaks, a lower peak-to-peak difference than those available in literature, and a peak period shift from the traditional peak period to traditional off-peak period. These lead to financial savings, reduced cost of peaker plants and a safer environment from less greenhouse gases emissions

Wireless sensor networks and advanced metering infrastructure deployment in smart grid

The increasing demand for has necessitated the introduction of information and communication technologies (ICT) in the development of the smart grid. Advanced Metering Infrastructure (AMI) and Wireless Sensor Networks (WSNs) are contributing technologies. In this paper, a review on AMI and WSN in the smart grid is carried out. Also, the introduction of WSNs with AMI in the in-home energy management system of the smart grid is also presented with challenges faced in the deployment of WSNs for the smart grid. The low power and low-cost nature of WSN has presented itself as a technology that can be used with AMI and smart home appliances in achieving home energy management within the great goal of the smart grid

Optimization of energy expenditure in smart homes under Time-of-Use pricing

Abstract: Growing peak demand has necessitated the introduction of Time-of-Use (TOU) pricing to Demand Side Management (DSM) in order to cause some peak demand to be shifted from peak to off-peak periods. Therefore, in this work, a Daily Maximum Energy Scheduling (DMES) - DSM technique is proposed. The DMES-DSM device is proposed to be installed into consumers’ smart meters and schedule energy consumption for smart appliances. The DMES–DSM technique was verified with real household data and shown to be capable of optimizing households’ monthly energy expenditure below approved national energy expenditure threshold and also offer Peak Demand Reduction (PDR). It offered the household considered an average monthly financial savings of 22.44% and 36.73% in summer and winter respectively on electricity bills. Utility can also benefit from the PDR for grid stability and sustainability. Also, the optimized consumption pattern differs only slightly from initial consumption pattern for enhanced consumer satisfaction

Effective energy consumption scheduling in smart homes

Abstract: Monthly expenditure on electricity by most households in South Africa take beyond acceptable percentage of their income. In order to keep the household energy expenditure below the energy poverty threshold, a daily electricity optimization problem is formulated using mixed integer linear programming (MILP) method. The energy optimization scheduling was carried out by a device called the Daily Maximum Energy Scheduling (DMES) device proposed to be incorporated into smart meters of households. The DMES algorithm was tested with household data set and was shown to be capable of ensuring that households spend less than 10% of their income on electricity bill monthly. This technique therefore, would be beneficial to consumers (for better financial savings and planning), utility (for effective energy and financial savings, and energy network planning) and cleaner environments as proposed for smart grid. Also, number of households in the nation living below the energy expenditure-based poverty threshold would increase

Distributed optimisation algorithm for demand side management in a grid-connected smart microgrid

Abstract: The contributions of Distributed Energy Generation (DEG) and Distributed Energy Storage (DES) for Demand Side Management (DSM) purposes in a smart macrogrid or microgrid cannot be over-emphasised. However, standalone DEG and DES can lead to under-utilisation of energy generation by consumers and financial investments; in grid-connection mode, though, DEG and DES can offer arbitrage opportunities for consumers and utility provider(s). A grid-connected smart microgrid comprising heterogeneous (active and passive) smart consumers, electric vehicles and a large-scale centralised energy storage is considered in this paper. Efficient energy management by each smart entity is carried out by the proposed Microgrid Energy Management Distributed Optimisation Algorithm (MEM-DOA) installed distributively within the network according to consumer type. Each smart consumer optimises its energy consumption and trading for comfort (demand satisfaction) and profit. The proposed model was observed to yield better consumer satisfaction, higher financial savings, and reduced Peak-to-Average-Ratio (PAR) demand on the utility grid. Other associated benefits of the model include reduced investment on peaker plants, grid reliability and environmental benefits. The MEM-DOA also offered participating smart consumers energy and tariff incentives so that passive smart consumers do not benefit more than active smart consumers, as was the case with some previous energy management algorithms

Distributed demand side management with battery storage for smart home energy scheduling

Abstract: The role of Demand Side Management (DSM) with Distributed Energy Storage (DES) has been gaining attention in recent studies due to the impact of the latter on energy management in the smart grid. In this work, an Energy Scheduling and Distributed Storage (ESDS) algorithm is proposed to be installed into the smart meters of Time-of-Use (TOU) pricing consumers possessing in-home energy storage devices. Source of energy supply to the smart home appliances was optimized between the utility grid and the DES device depending on energy tariff and consumer demand satisfaction information. This is to minimize consumer energy expenditure and maximize demand satisfaction simultaneously. The ESDS algorithm was found to offer consumer-friendly and utility-friendly enhancements to the DSM program such as energy, financial, and investment savings, reduced/eliminated consumer dissatisfaction even at peak periods, Peak-to-Average-Ratio (PAR) demand reduction, grid energy sustainability, socio-economic benefits, and other associated benefits such as environmental-friendliness

Editorial: Climate change mitigation and adaptation in power and energy systems

\ua9 2024. This editorial summarizes the papers selected for publication in the Special Issue on Climate Change Mitigation and Adaptation in Power and Energy Systems (CMAP). After a rigorous review of 86 submitted manuscripts, 23 papers were accepted for publication. These accepted papers cover various aspects of climate change mitigation and adaptation and are classified as follows: boosting renewable energy efficiency (two papers), climate resilience strategies (four papers), decarbonization strategies (four papers), renewable energy integration (five papers), policies, incentives, and science communications (four papers), and the role of energy markets (four papers). The Guest Editorial Board is optimistic that this Special Issue will serve as a rich resource, offering invaluable insights to propel future research and advancements in climate change mitigation and adaptation

Reviewing the decision-making behaviour of Irrigators

The contribution of agriculture to society is undeniable, as is its impact on the environment. Irrigators' decisions to follow best management practices or implement a policy change, to accept a technology, or even to exit farming, all affect society. Hence the decision‐making behavior of irrigators is of interest to politicians, policymakers, and researchers due to their impact on resource use and social concerns for their welfare. There are numerous studies available regarding the decision‐making behavior of irrigators. Most of them concentrate on decisions within a single time frame, single decisions with multiple driving forces, or multiple decisions with a single driving force. We have conducted a comprehensive review of the existing literature related to irrigators' decision‐making behavior. We used a systematic method to identify relevant publications and used qualitative data analysis (content analysis) to analyze trends and/or patterns across the selected articles. This research provided a typology and an overarching high‐level framework of irrigators' decision‐making process irrespective of the types of decisions made. The results of the study demonstrate that it is highly beneficial to integrate both qualitative and quantitative methods in a single study to get a complete picture of irrigators' decision‐making process. This allows us to ensure that we have captured the relevant drivers of decision‐making in highly dynamic and complex environments. Better knowledge of irrigators' decision‐making process allows regulators to shape improved agricultural policy and increase acceptance by irrigators of technologies that allow water managers to allocate resources fairly among different stakeholders.Lubna Meempatta, A. James Webb, Avril C. Horne, Louise Anne Keogh, Adam Loch, Michael J. Stewardso

Facial expressions depicting compassionate and critical emotions: the development and validation of a new emotional face stimulus set

Attachment with altruistic others requires the ability to appropriately process affiliative and kind facial cues. Yet there is no stimulus set available to investigate such processes. Here, we developed a stimulus set depicting compassionate and critical facial expressions, and validated its effectiveness using well-established visual-probe methodology. In Study 1, 62 participants rated photographs of actors displaying compassionate/kind and critical faces on strength of emotion type. This produced a new stimulus set based on N = 31 actors, whose facial expressions were reliably distinguished as compassionate, critical and neutral. In Study 2, 70 participants completed a visual-probe task measuring attentional orientation to critical and compassionate/kind faces. This revealed that participants lower in self-criticism demonstrated enhanced attention to compassionate/kind faces whereas those higher in self-criticism showed no bias. To sum, the new stimulus set produced interpretable findings using visual-probe methodology and is the first to include higher order, complex positive affect displays

The factor structure of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen distinct populations

There is considerable evidence that self-criticism plays a major role in the vulnerability to and recovery from psychopathology. Methods to measure this process, and its change over time, are therefore important for research in psychopathology and well-being. This study examined the factor structure of a widely used measure, the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen nonclinical samples (N = 7510) from twelve different countries: Australia (N = 319), Canada (N = 383), Switzerland (N = 230), Israel (N = 476), Italy (N = 389), Japan (N = 264), the Netherlands (N = 360), Portugal (N = 764), Slovakia (N = 1326), Taiwan (N = 417), the United Kingdom 1 (N = 1570), the United Kingdom 2 (N = 883), and USA (N = 331). This study used more advanced analyses than prior reports: a bifactor item-response theory model, a two-tier item-response theory model, and a non-parametric item-response theory (Mokken) scale analysis. Although the original three-factor solution for the FSCRS (distinguishing between Inadequate-Self, Hated-Self, and Reassured-Self) had an acceptable fit, two-tier models, with two general factors (Self-criticism and Self-reassurance) demonstrated the best fit across all samples. This study provides preliminary evidence suggesting that this two-factor structure can be used in a range of nonclinical contexts across countries and cultures. Inadequate-Self and Hated-Self might not by distinct factors in nonclinical samples. Future work may benefit from distinguishing between self-correction versus shame-based self-criticism.Peer reviewe