scholarly journals Demand-side management strategies based on energy key perfomance indicators in real-time: Case study

2020 ◽  
Vol 10 (1) ◽  
pp. 5-16
Author(s):  
Sandra Milena Tellez- Gutierrez ◽  
Oscar German Duarte Velasco ◽  
Javier Rosero García
Keyword(s):  
Real Time ◽  
Performance Indicators ◽  
Energy Savings ◽  
New Technologies ◽  
Management Strategies ◽  
Demand Side Management ◽  
Key Performance Indicators ◽  
Demand Side ◽  
Advanced Metering

This paper sets out features of traditional Energy Key Performance Indicators (KPIs) employed in energy management programs; then, new indicators are proposed based on Advanced Metering Infrastructure (AMI) usage. These indicators make it possible to directly relate the amount of energy, type of end use and user consumption patterns. Analysis of AMI system information enables planning for differentiated Demand-Side Management (DSM) strategies. A case study developed at Universidad Nacional de Colombia - Bogotá campus is presented, which proposes new Energy Key Performance Indicators in Real Time. These indicators enable information analysis and DSM strategies that are appropriate for new technologies and that are aimed at increasing energy efficiency. Additionally, this paper presents the factors that have to be taken into account when implementing KPIs (Key Performance Indicators) and the decision-making process. This results in variable overall energy savings between 5 and 40%, according to the DSM strategy implemented.

A Review and Categorization of Grid-Interactive Efficient Building Technologies for Building Performance Simulation

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
Matt Steen ◽  
Moncef Krarti
Keyword(s):  
New Technologies ◽  
Management Strategies ◽  
Demand Side Management ◽  
Simulation Software ◽  
Building Performance ◽  
Demand Side ◽  
Grid Services ◽  
Building Performance Simulation ◽  
High Penetration ◽  
Grid Operators

Abstract Buildings of the future are expected to not only be energy efficient but also able to offer grid services through implementation of demand-side management strategies by utilizing existing and new technologies that enhance electrical load flexibility. With the high penetration of variable renewables, grid operators have to balance between variable supply with controllable and adaptable demand. This article reviews the current literature on grid-interactive efficient buildings (GEBs) that can provide grid services. In particular, the review identifies categories and examples of measures and technologies that are suitable for GEBs using various criteria. These criteria include demand-side management strategies, potential to provide grid services, technology maturity, as well as ability to model the technologies to perform detailed analyses and assessments in whole-building simulation software.

scholarly journals Key Performance Indicators for an Energy Community Based on Sustainable Technologies

2021 ◽  
Vol 13 (16) ◽  
pp. 8789
Author(s):  
Giovanni Bianco ◽  
Barbara Bonvini ◽  
Stefano Bracco ◽  
Federico Delfino ◽  
Paola Laiolo ◽  
...  
Keyword(s):  
Performance Indicators ◽  
Urban Areas ◽  
High Performance ◽  
Power Plants ◽  
New Technologies ◽  
Storage Systems ◽  
Clean Energy ◽  
Key Performance Indicators ◽  
Energy Performance ◽  
Green Energy

As reported in the “Clean energy for all Europeans package” set by the EU, a sustainable transition from fossil fuels towards cleaner energy is necessary to improve the quality of life of citizens and the livability in cities. The exploitation of renewable sources, the improvement of energy performance in buildings and the need for cutting-edge national energy and climate plans represent important and urgent topics to be faced in order to implement the sustainability concept in urban areas. In addition, the spread of polygeneration microgrids and the recent development of energy communities enable a massive installation of renewable power plants, high-performance small-size cogeneration units, and electrical storage systems; moreover, properly designed local energy production systems make it possible to optimize the exploitation of green energy sources and reduce both energy supply costs and emissions. In the present paper, a set of key performance indicators is introduced in order to evaluate and compare different energy communities both from a technical and environmental point of view. The proposed methodology was used in order to assess and compare two sites characterized by the presence of sustainable energy infrastructures: the Savona Campus of the University of Genoa in Italy, where a polygeneration microgrid has been in operation since 2014 and new technologies will be installed in the near future, and the SPEED2030 District, an urban area near the Campus where renewable energy power plants (solar and wind), cogeneration units fed by hydrogen and storage systems are planned to be installed.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

scholarly journals Misfit? The Use of Metrics in Innovation

2021 ◽  
Vol 14 (8) ◽  
pp. 388
Author(s):  
Ilse Svensson de Jong
Keyword(s):  
Performance Indicators ◽  
Business Performance ◽  
Strategic Change ◽  
Key Performance Indicators ◽  
Significant Degree ◽  
Other Information ◽  
Actual Use ◽  
Sales Organizations ◽  
Organizational Levels

Measuring innovation is a challenging but essential task to improve business performance. To tackle this task, key performance indicators (KPIs) can be used to measure and monitor innovation. The objective of this study is to explore how KPIs, designed for measuring innovation, are used in practice. To achieve this objective, the author draws upon literature on business performance in accounting and innovation, yet moves away from the functional view. Instead, the author focuses explicitly on how organizational members, through their use of KPIs in innovation, make sense of conflicting interpretations and integrate them into their practices. A qualitative in-depth case study was conducted at the innovation department of an organization in the process industry that operates production sites and sales organizations worldwide. In total, 28 interviews and complementary observations were undertaken at several organizational levels (multi-level). The empirical evidence suggests that strategic change, attributed to commoditization, affects the predetermined KPIs in use. Notably, these KPIs in innovation are used, despite their poor fit to innovation subject to commoditization. From a relational perspective, this study indicates that in innovation, KPIs are usually complemented by or supplemented with other information, as stand-alone KPIs exhibit a significant degree of incompleteness. In contrast to conventional studies in innovation and management accounting, this study explores the use of key performance indicators (KPIs) in innovation from an interpretative perspective. This perspective advances our understanding of the actual use of KPIs and uncovers the complexity of accounting and innovation, which involve numerous angles and organizational levels. Practically, the findings of this study will inform managers in innovation about the use of KPIs in innovation and the challenges individual organizational members face when using them. In innovation, KPIs appear to be subjective and used in unintended ways. Thus, understanding how KPIs are used in innovation is a game of reading between the lines, and these KPIs can be regarded as misfits.

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