scholarly journals Demand Side Management in Pellet Production: Internal and External Factors

2014 ◽  
Vol 14 (1) ◽  
pp. 30-35 ◽  
Author(s):  
Haralds Vigants ◽  
Dagnija Blumberga ◽  
Ivars Veidenbergs
Keyword(s):  
Energy Efficiency ◽  
Energy Management ◽  
Energy Demand ◽  
Demand Side Management ◽  
External Factors ◽  
Technological Equipment ◽  
Demand Side ◽  
Improve Energy Efficiency ◽  
Pellet Production ◽  
Internal And External Factors

Abstract This paper demonstrates a demand side management case study: how to save energy and how research and data analysis help to create an energy management system in a pellet production facility; and shows ways to implement the EU energy efficiency directive in production facilities. The study carried out in this research serves as a far-reaching step that can be taken to improve energy efficiency during the operation mode of technological equipment. The benchmarking methodology is used for analysis of results. Internal and external factors and indicators, which affect energy management potential in pellet production are analysed. Analysis of external factors is based on the state legal framework regulating the development of the energy sector. Methodology on the analysis of energy demand includes the internal energy management of an enterprise. The experimental results discussed in this paper show that particular steps, which are oriented to specific use of technological equipment, could play significant role in energy efficiency improvement in industry which is illustrated by the pre-milling process in the pellet production system using power.

scholarly journals Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4539 ◽  
Author(s):  
Kumar ◽  
Brar ◽  
Singh ◽  
Nikolovski ◽  
Baghaee ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Management ◽  
Residential Buildings ◽  
Effective Means ◽  
Demand Side Management ◽  
Demand Side ◽  
Specific System ◽  
Energy Data ◽  
Energy Auditing

With the ever-growing power demand, the energy efficiency in commercial and residential buildings is a matter of great concern. Also, strategic energy auditing (SEA) and demand-side management (DSM) are cost-effective means to identify the requirements of power components and their operation in the energy management system. In a commercial or residential building, the major components are light sources and heating, ventilation, and air conditioning. The number of these components to be installed depends upon the technical and environmental standards. In this scenario, energy auditing (EA) allows identifying the methods, scope, and time for energy management, and it helps the costumers to manage their energy consumption wisely to reduce electricity bills. In the literature, most of the traditional strategies employed specific system techniques and algorithms, whereas, in recent years, load shifting-based DSM techniques were used under different operating scenarios. Considering these facts, the energy data in a year were collected under three different seasonal changes, i.e., severe cold, moderate, and severe heat for the variation in load demand under different environmental conditions. In this work, the energy data under three conditions were averaged, and the DSM schemes were developed for the operation of power components before energy auditing and after energy auditing. Moreover, the performance of the proposed DSM techniques was compared with the practical results in both scenarios, and, from the results, it was observed that the energy consumption reduced significantly in the proposed DSM approach.

scholarly journals Enabling Demand Side Management: Heat Demand Forecasting at City Level

Materials ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 202 ◽  
Author(s):  
Petri Hietaharju ◽  
Mika Ruusunen ◽  
Kauko Leiviskä
Keyword(s):  
Energy Efficiency ◽  
Demand Forecasting ◽  
Demand Side Management ◽  
Measurement Information ◽  
Demand Side ◽  
Demand Forecast ◽  
Building Stock ◽  
Improve Energy Efficiency ◽  
Heat Demand ◽  
The City

Implementation of new energy efficiency measures for the heating and building sectors is of utmost importance. Demand side management offers means to involve individual buildings in the optimization of the heat demand at city level to improve energy efficiency. In this work, two models were applied to forecast the heat demand from individual buildings up to a city-wide area. District heating data at the city level from more than 4000 different buildings was utilized in the validation of the forecast models. Forecast simulations with the applied models and measured data showed that, during the heating season, the relative error of the city level heat demand forecast for 48 h was 4% on average. In individual buildings, the accuracy of the models varied based on the building type and heat demand pattern. The forecasting accuracy, the limited amount of measurement information and the short time required for model calibration enable the models to be applied to the whole building stock. This should enable demand side management and lead to the predictive optimization of heat demand at city level, leading to increased energy efficiency.

Enhancing the firm’s strategic behaviour

2018 ◽  
Vol 34 (8) ◽  
pp. 1-3
Keyword(s):  
Design Methodology ◽  
Reading Time ◽  
External Factors ◽  
Demand Side ◽  
Content Type ◽  
Strategic Behaviour ◽  
Industry Life Cycle ◽  
Pertinent Information ◽  
Internal And External Factors ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context Findings Strategic behaviour is shaped considerably by demand-side internal and external factors. Through appropriate investment to acquire and enhance customer-related capabilities, firms can become better positioned than rivals to make effective decisions during along an industry life cycle. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Production Process Modeling for Demand Side Management

2017 ◽  
Vol 871 ◽  
pp. 77-86
Author(s):  
Stefanie Kabelitz ◽  
Sergii Kolomiichuk
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Supply And Demand ◽  
Demand Side Management ◽  
Mixed Integer ◽  
Mixed Integer Program ◽  
Business Practices ◽  
Demand Side ◽  
Manufacturing Companies ◽  
Consumption Data

The supply of electricity is growing increasingly dependent on the weather as the share of renewable energies increases. Different measures can nevertheless maintain grid reliability and quality. These include the use of storage technologies, upgrades of the grid and options for responsiveness to supply and demand. This paper focuses on demand side management and the use of flexibility in production processes. First, the framework of Germany’s energy policy is presented and direct and indirect incentives for businesses to seek as well as to provide flexibility capabilities are highlighted. Converting this framework into a mixed integer program leads to multi-objective optimization. The challenge inherent to this method is realistically mapping the different objectives that affect business practices directly and indirectly in a variety of laws. An example is introduced to demonstrate the complexity of the model and examine the energy flexibility. Second, manufacturing companies’ energy efficiency is assessed under the frequently occurring conditions of heavily aggregated energy consumption data and of information with insufficient depth of detail to perform certain analyses, formulate actions or optimize processes. The findings obtained from the energy assessment and energy consumption projections are used to model the production system’s energy efficiency and thus facilitate optimization. Methods of data mining and machine learning are employed to project energy consumption. Aggregated energy consumption data and different production and environmental parameters are used to assess indirectly measured consumers and link projections of energy consumption with the production schedule.

Efficient power scheduling in smart homes using a novel artificial ecosystem optimization technique considering two pricing schemes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Souhil Mouassa ◽  
Marcos Tostado-Véliz ◽  
Francisco Jurado
Keyword(s):  
Energy Demand ◽  
Supply And Demand ◽  
Optimization Technique ◽  
Smart Homes ◽  
Demand Side Management ◽  
Time Interval ◽  
Demand Side ◽  
Artificial Ecosystem ◽  
Pricing Schemes ◽  
Operational Time

Abstract With emergence of automated environments, energy demand increased with unexpected ratio, especially total electricity consumed in the residential sector. This unexpected increase in demand in energy brings a challenging task of maintaining the balance between supply and demand. In this work, a robust artificial ecosystem-inspired optimizer based on demand-side management is proposed to provide the optimal scheduling pattern of smart homes. More precisely, the main objectives of the developed framework are: i) Shifting load from on-peak hours to off-peak hours while fulfilling the consumer intends to reduce electricity-bills. ii) Protect users comfort by improving the appliances waiting time. Artificial ecosystem optimizer (AEO) algorithm is a novel optimization technique inspired by the energy flocking between all living organisms in the ecosystem on earth. Demand side management (DSM) program is modeled as an optimization problem with constraints of starting and ending of appliances. The proposed optimization technique based DSM program is evaluated on two different pricing schemes with considering two operational time intervals (OTI). Extensive simulation cases are carried out to validate the effectiveness of the proposed optimizer based energy management scheme. AEO minimizes total electricity-bills while keeping the user comfort by producing optimum appliances scheduling pattern. Simulation results revealed that the proposed AEO achieved a minimization electricity-bill up to 10.95, 10.2% for RTP and 37.05% for CPP for the 12 and 60 min operational time interval (OTI), respectively, in comparison to other results achieved by other optimizers. On the other hand peak to average ratio (PAR) is reduced to 32.9% using RTP and 31.25% using CPP tariff.

scholarly journals Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1309 ◽  
Author(s):  
Tomasz Szul ◽  
Stanisław Kokoszka
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Set Theory ◽  
Rough Set ◽  
Energy Demand ◽  
Rough Set Theory ◽  
Residential Buildings ◽  
Simple Procedure ◽  
Energy Performance ◽  
Improve Energy Efficiency

In many regions, the heat used for space heating is a basic item in the energy balance of a building and significantly affects its operating costs. The accuracy of the assessment of heat consumption in an existing building and the determination of the main components of heat loss depends to a large extent on whether the energy efficiency improvement targets set in the thermal upgrading project are achieved. A frequent problem in the case of energy calculations is the lack of complete architectural and construction documentation of the analyzed objects. Therefore, there is a need to search for methods that will be suitable for a quick technical analysis of measures taken to improve energy efficiency in existing buildings. These methods should have satisfactory results in predicting energy consumption where the input is limited, inaccurate, or uncertain. Therefore, the aim of this work was to test the usefulness of a model based on Rough Set Theory (RST) for estimating the thermal energy consumption of buildings undergoing an energy renovation. The research was carried out on a group of 109 thermally improved residential buildings, for which energy performance was based on actual energy consumption before and after thermal modernization. Specific sets of important variables characterizing the examined buildings were distinguished. The groups of variables were used to estimate energy consumption in such a way as to obtain a compromise between the effort of obtaining them and the quality of the forecast. This has allowed the construction of a prediction model that allows the use of a fast, relatively simple procedure to estimate the final energy demand rate for heating buildings.

scholarly journals Drivers and Barriers to Industrial Energy Efficiency in Textile Industries of Bangladesh

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1775 ◽  
Author(s):  
A S M Monjurul Hasan ◽  
Mohammad Rokonuzzaman ◽  
Rashedul Amin Tuhin ◽  
Shah Md. Salimullah ◽  
Mahfuz Ullah ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Management ◽  
Energy Demand ◽  
Management Practices ◽  
Capital Expenditure ◽  
High Energy ◽  
Industrial Sector ◽  
Energy Prices ◽  
Energy Service ◽  
Textile Industries

Bangladesh faced a substantial growth in primary energy demand in the last few years. According to several studies, energy generation is not the only means to address energy demand; efficient energy management practices are also very critical. A pertinent contribution in the energy management at the industrial sector ensures the proper utilization of energy. Energy management and its efficiency in the textile industries of Bangladesh are studied in this paper. The outcomes demonstrate several barriers to energy management practices which are inadequate technical cost-effective measures, inadequate capital expenditure, and poor research and development. However, this study also demonstrates that the risk of high energy prices in the future, assistance from energy professionals, and an energy management scheme constitute the important drivers for the implementation of energy efficiency measures in the studied textile mills. The studied textile industries seem unaccustomed to the dedicated energy service company concept, and insufficient information regarding energy service companies (ESCOs) and the shortage of trained professionals in energy management seem to be the reasons behind this. This paper likewise finds that 3–4% energy efficiency improvements can be gained with the help of energy management practices in these industries.

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