Prediction of unregulated energy usage in office buildings

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emmanuel Frimpong ◽  
Elvis Twumasi
Keyword(s):  
Energy Consumption ◽  
Prediction Method ◽  
Field Measurements ◽  
Office Buildings ◽  
Nsga Ii ◽  
Content Type ◽  
Active Mode ◽  
Using Data ◽  
Device Operation

PurposeThe paper presents a technique for predicting the energy consumption of unregulated energy loads (UELs) in office buildings. It also presents an approach for determining a set of optimum values required by the technique.Design/methodology/approachThe proposed technique uses the optimum power drawn and optimum usage period in three modes of device operation, for the prediction. The usage modes are active mode, idle (low active) mode and off mode. The optimum powers and usage times are inserted into a linear mathematical equation to predict the energy consumption. Regarding the approach for determining the optimum values, the non-dominated sorting genetic algorithm II (NSGA-II) is applied to a range of values obtained from field measurements. The proposed prediction method and approach for determining optimum values were tested using data of energy consumption of UELs in a case study facility.FindingsTest results show that the method for predicting the energy consumption of UELs in offices is highly accurate and suitable for adoption by energy modelers, building designers and building regulatory agencies. The approach for determining the optimum values is also effective and can aid the establishment of workable benchmark values.Originality/valueA new and simple model has been developed for the prediction of unregulated energy. A method for determining a set of optimum values of power and usage periods required by the model has also been developed. Furthermore, optimum values have been suggested that can be fine-tuned for use as benchmark values. The proposed approaches are the first of their kind.

The use of performance information in local government mergers

2019 ◽  
Vol 31 (3) ◽  
pp. 451-471 ◽  
Author(s):  
Karina Kenk ◽  
Toomas Haldma
Keyword(s):  
Attribution Theory ◽  
Local Governments ◽  
Eastern European Country ◽  
Eastern European ◽  
Performance Information ◽  
Case Study Method ◽  
Content Type ◽  
Different Types ◽  
Using Data

Purpose The purpose of this paper is to study more deeply the use of performance information (PI) in the context of the administrative-territorial reform, e.g. amalgamation in the local governments (LG) with an example of Estonian LGs. Design/methodology/approach The case study method is adopted, using data from publicly available documents and interviews with the politicians and officials at the five merger cases of Estonian LG units. The data are interpreted and analysed using attribution theory. Findings The results show that amalgamation patterns do have an influence on PI use – in particular, the authors see that PI is reported to be used more frequently in cases of voluntary mergers, which may be related to the different motivations to make attributions in cases of voluntary and compulsory mergers. Originality/value The study contributes to the debate on the importance and usefulness of different types of PI, as financial as well as non-financial information and for different information users in the light of LG reform in Estonia as being a Central and Eastern European country.

Impressions in action: the socially situated construction of expertise in the workplace

2015 ◽  
Vol 4 (1) ◽  
pp. 44-63 ◽  
Author(s):  
Aditya Johri
Keyword(s):  
Impression Formation ◽  
Task Assignment ◽  
Ethnographic Study ◽  
Knowledge Generation ◽  
Task Completion ◽  
Content Type ◽  
Using Data ◽  
Workplace Setting ◽  
Socially Situated

Purpose – The impressions of others’ expertise are fundamental to workplace dynamics. Identifying expertise is essential for workplace functions such as task assignment, task completion, and knowledge generation. Although prior work has examined both the nature of expertise and its importance for work, formation of expertise impressions in the workplace has not received much attention. The paper aims to discuss these issues. Design/methodology/approach – In this paper the author addresses the question – how do we form expertise impressions in the workplace – using data from an ethnographic study of a workplace setting. The author employs a case study of project team formation to synthesize a process framework of impression formation. Findings – The author proposes a framework that integrates sociocultural and interactional accounts to argue that actors utilize situational and institutional frames to socially construct their expertise impressions of others. These frames emerge as actors engage in activities within a community of practice. Originality/value – This practice-based explication of expertise construction moves beyond narrow conceptions of personality-based traits or credentials as signals of expertise. It explains why sharing of expertise within organizations through the use of information technology continues to be problematic – expertise is an enactment and therefore it defies reification through knowledge management.

Corruption accounting and growth: towards a new methodology

2020 ◽  
Vol 27 (1) ◽  
pp. 43-57
Author(s):  
Martin Grandes ◽  
Ariel Coremberg
Keyword(s):  
Endogenous Growth ◽  
Public Works ◽  
Public Expenditures ◽  
National Accounts ◽  
Public Officials ◽  
Content Type ◽  
Endogenous Growth Model ◽  
Using Data ◽  
The One

Purpose The purpose of this paper is to demonstrate empirically that corruption causes significant and sizeable macroeconomic costs to countries in terms of economic activity and economic growth. The authors modeled corruption building on the endogenous growth literature and finally estimated the baseline (bribes paid to public officials) macroeconomic cost of corruption using Argentina 2004-2015 as a case study. Design/methodology/approach The authors laid the foundations of a new methodology to account corruption losses using data from the national accounts and judiciary investigations within the framework of the Organisation for Economic Cooperation and Development (OECD) non-observed economy (NOE) instead of subjective indicators as in the earlier literature. They also suggested a new method to compute public expenditures overruns, including but not limited to public works. Findings The authors found the costs stand at a minimum accumulated rate of 8 per cent of gross domestic product (GDP) or 0.8 per cent yearly. These findings provided a corruption cost floor and were consistent with earlier research on world corruption losses estimated at 5 per cent by the World Economic Forum and with the losses estimated at between a yearly rate of 1.3 and 4 per cent and 2 per cent of GDP by Brazil and Peru’s corruption, respectively. Research limitations/implications The authors would need to extend the application of their new suggested methodology to further countries. They are working on this. They would need to develop the methodology in full to compute the public works overruns input to future econometric work. Originality/value In this paper, the authors make a threefold contribution to the literature on corruption and growth: first, they laid the foundations toward a new methodology to make an accounting of the corruption costs in terms of GDP consistent with the national accounts and executed budgets; on the one hand, and the OECD NOE framework, on the other. The authors named those corruption costs as percentage of GDP the “corruption wedge.” Second, they developed an example taking corruption events and a component of their total costs, namely, the bribes paid to public officials, taking Argentina 2004-2015 as a case study. Finally, they plugged the estimated wedge back into an endogenous growth model and calibrated the growth–corruption path simulating two economies where the total factor productivity was different, at different levels of the corruption wedge.

Determinants of bank branch density: a case study of Slovakia

2020 ◽  
Vol 38 (4) ◽  
pp. 933-959
Author(s):  
Martin Boďa ◽  
Katarína Čunderlíková
Keyword(s):  
Regulatory Oversight ◽  
Bank Branch ◽  
Content Type ◽  
Bank Branches ◽  
Five Factors ◽  
Decision Making Processes ◽  
Branch Density ◽  
Using Data ◽  
Practical Implications

PurposeThis paper studies the density of bank branches in districts of Slovakia and aims to identify determinants that explain or justify districtural differences in the density of bank branches.Design/methodology/approachBank branch density is measured by the number of branches in a district, and banks are further differentiated by size and profile. Potential determinants of bank branch density are sought through univariate and bivariate Poisson regressions amongst economic factors, socioeconomic factors, technological factors, urbanization factors, and branch market concentration.FindingsUsing data from 2016, it has been found that branch numbers in districts are determined chiefly by five factors that describe their economic development, population size with its characteristics, and existent branch concentration. The spatial distribution of bank branches in the territory of Slovakia is not random, but is found to be affected by environmental factors measurable at the districtural level. Only 22 Slovak districts representing administrative or economic centers are expected to be over-branched.Practical implicationsThe study helps to identify factors that need be accounted for in planning and redesigning of branch networks or in implementing mergers and acquisitions on a bank level. The results are also useful in regional policy and regulatory oversight.Originality/valueThe present study is unique since the decision-making processes of Slovak commercial banks in planning the location and density of their branch networks have not been rationalized and researched as of yet.

The impact of accreditation agencies and other powerful stakeholders on the performance measurement in Polish universities

2019 ◽  
Vol 14 (1) ◽  
pp. 84-102 ◽  
Author(s):  
Dorota Dobija ◽  
Anna Maria Górska ◽  
Anna Pikos
Keyword(s):  
Performance Measurement ◽  
Performance Information ◽  
Case Study Method ◽  
Content Type ◽  
Additional Layer ◽  
Using Data ◽  
Polish Higher Education ◽  
The Impact ◽  
Collection Methods

Purpose The purpose of this paper is to extend the understanding of how internal organisational processes change in response to external demands, by investigating the changes undertaken by two Polish business schools (b-schools) in anticipation of and in response to the demands of accreditation agencies (AAs) and other powerful stakeholders. Specifically, it examines the internal research-related performance measurement (PM) system and changes in the use of performance information (PI). Design/methodology/approach The case study method is adopted, using data from publicly available documents and interviews with the faculty and management at the two schools. The data are interpreted and analysed using the neo-institutional theory. Findings Powerful stakeholders are the primary reason for changes in PM systems and the manner in which PI is used. Specifically, AAs reflect an additional layer in the PM system, allowing for a downward cascading PI effect. This also leads to a wider use of PI across different organisational levels. Research limitations/implications This study focusses on two case studies in a region still undergoing transition. Thus, this analysis could be reinforced through additional cases, different data collection methods and cross-country and between-country comparative analyses. Originality/value The changes in PM systems and particularly the use of PI are discussed in the context of Polish higher education (HE) and, more broadly, the entire Central and Eastern Europe (CEE) region. Moreover, the consideration of two b-school cases facilitates a comparative analysis of the differences in PM systems and the use of PI in the context of stakeholders’ PI needs.

Using energy profiles to identify university energy reduction opportunities

2016 ◽  
Vol 17 (2) ◽  
pp. 188-207 ◽  
Author(s):  
Nandarani Maistry ◽  
Harold Annegarn
Keyword(s):  
South Africa ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Quantitative Research ◽  
Electricity Consumption ◽  
Working Hours ◽  
Content Type ◽  
Academic Calendar ◽  
The University

Purpose – The purpose of this paper is to outline efforts at the University of Johannesburg, a large metropolitan university in Gauteng province, to examine energy efficiency within the context of the green campus movement, through the analysis of electricity consumption patterns. The study is particularly relevant in light of the cumulative 230 per cent increase in electricity costs between 2008 and 2014 in South Africa that has forced institutions of higher education to seek ways to reduce energy consumption. Design/Methodology/Approach – A quantitative research design was adopted for the analysis of municipal electricity consumption records using a case study approach to identify trends and patterns in consumption. The largest campus of the University of Johannesburg, which is currently one of the largest residential universities in South Africa, was selected as a case study. Average diurnal consumption profiles were plotted according to phases of the academic calendar, distinguished by specific periods of active teaching and research (in-session); study breaks, examinations and administration (out-of-session); and recesses. Average profiles per phase of the academic calendar were constructed from the hourly electricity consumption and power records using ExcelTM pivot tables and charts. Findings – It was found that the academic calendar has profound effects on energy consumption by controlling the level of activity. Diurnal maximum consumption corresponds to core working hours, peaking at an average of 2,500 kWh during “in-session” periods, 2,250 kWh during “out-of-session” periods and 2,100 kWh during recess. A high base load was evident throughout the year (between 1,300 and 1,650 kWh), mainly attributed to heating and cooling. By switching off the 350 kW chiller plant on weekdays, a 9 per cent electricity reduction could be achieved during out-of-session and recess periods. Similarly, during in-session periods, a 6 per cent reduction could be achieved. Practical implications – Key strategies and recommendations are presented to stimulate energy efficiency implementation within the institution. Originality Value – Coding of consumption profiles against the academic calendar has not been previously done in relation to an academic institution. The profiles were used to establish the influence of the academic calendar on electricity consumption, which along with our own observation were used to identify specific consumption reduction opportunities worth pursuing.

Energy Consumption Forecasting Using United Grey System–Bayesian Regularization Neural Network Model

2012 ◽  
Vol 524-527 ◽  
pp. 3087-3092 ◽  
Author(s):  
Xiao Hui Hu ◽  
Lv Jun Zhan ◽  
Yun Xue ◽  
Gui Xi Liu ◽  
Zhe Fan
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Regularization Parameter ◽  
Prediction Method ◽  
Neural Model ◽  
Bayesian Regularization ◽  
Grey System ◽  
Bayesian Regularization Neural Network ◽  
Energy Consumption Prediction

The energy consumption of the enterprise is subject to various factors. To solve the problem, a new grey-neural model is proposed which effectively combines the grey system and Bayesian-regularization neural network and avoids the disadvantages of each other. The case study indicates that the prediction method is not only reasonable in theory but also owns good application value in the energy consumption prediction. Meanwhile, results also exhibit that G-BRNN model has the automated regularization parameter selection capability and may ensure the excellent adaptability and robustness.

A maximal covering facility location model for emergency services within an M (t)/M/m/m queuing system

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Iman Bahrami ◽  
Roya M. Ahari ◽  
Milad Asadpour
Keyword(s):  
Facility Location ◽  
Emergency Services ◽  
Queuing System ◽  
Location Model ◽  
Computational Time ◽  
Nsga Ii ◽  
Content Type ◽  
Maximal Covering ◽  
Proposed Model

Purpose In emergency services, maximizing population coverage with the lowest cost at the peak of the demand is important. In addition, due to the nature of services in emergency centers, including hospitals, the number of servers and beds is actually considered as the capacity of the system. Hence, the purpose of this paper is to propose a multi-objective maximal covering facility location model for emergency service centers within an M (t)/M/m/m queuing system considering different levels of service and periodic demand rate. Design/methodology/approach The process of serving patients is modeled according to queuing theory and mathematical programming. To cope with multi-objectiveness of the proposed model, an augmented ε-constraint method has been used within GAMS software. Since the computational time ascends exponentially as the problem size increases, the GAMS software is not able to solve large-scale problems. Thus, a NSGA-II algorithm has been proposed to solve this category of problems and results have been compared with GAMS through random generated sample problems. In addition, the applicability of the proposed model in real situations has been examined within a case study in Iran. Findings Results obtained from the random generated sample problems illustrated while both the GAMS software and NSGA-II almost share the same quality of solution, the CPU execution time of the proposed NSGA-II algorithm is lower than GAMS significantly. Furthermore, the results of solving the model for case study approve that the model is able to determine the location of the required facilities and allocate demand areas to them appropriately. Originality/value In the most of previous works on emergency services, maximal coverage with the minimum cost were the main objectives. Hereby, it seems that minimizing the number of waiting patients for receiving services have been neglected. To the best of the authors’ knowledge, it is the first time that a maximal covering problem is formulated within an M (t)/M/m/m queuing system. This novel formulation will lead to more satisfaction for injured people by minimizing the average number of injured people who are waiting in the queue for receiving services.

Sensor-based ambient intelligence for optimal energy efficiency

Sensor Review ◽  
2014 ◽  
Vol 34 (2) ◽  
pp. 170-181 ◽  
Author(s):  
David Robinson ◽  
David Adrian Sanders ◽  
Ebrahim Mazharsolook
Keyword(s):  
Energy Efficiency ◽  
Decision Support ◽  
Energy Consumption ◽  
Energy Management ◽  
Research Work ◽  
Management Systems ◽  
Manufacturing Companies ◽  
Content Type ◽  
Energy Management Systems

Purpose – This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation. Design/methodology/approach – A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency. Findings – An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems. Research limitations/implications – The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described). Practical implications – A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved. Originality/value – For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.

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