Economic Optimization of a Cogeneration System for Apartments in Korea

2007 ◽  
Author(s):  
HyonUk Seo ◽  
Jinil Sung ◽  
Si-Doek Oh ◽  
Hoo-Suk Oh ◽  
Ho-Young Kwak
Keyword(s):  
Distributed Generation ◽  
Energy Demand ◽  
Fossil Fuel ◽  
Energy Savings ◽  
Economic Optimization ◽  
Economic Gain ◽  
Residential Areas ◽  
Optimum Configuration ◽  
Cogeneration System ◽  
Fossil Fuel Energy

A cogeneration system which can be used as a distributed generation source produces electricity and heat energy simultaneously from a single source of fuel. For industrial and domestic applications, where both kinds of energy are required, the cogeneration system can return fossil fuel energy savings up to 30%, and can reduce CO2 emissions correspondingly as compared with a conventional system. In this study, eight apartments with residential areas in the range of 7200 m2 to 18200 m2 were chosen to study how much energy savings can be achieved by adoption of the cogeneration system in those apartments. Based on the energy demand data for heat and electricity, an optimum configuration of the cogeneration system for each apartment was determined by a developed computer program. The economic gain achieved by introducing the cogeneration system in those apartments was estimated and the monitored values compared with the estimated ones. By adoption of the cogeneration system, the fossil fuel saved was more than 30% and an average economic gain of $3.6/m2 per year was obtained.

scholarly journals Intelligent Edge-based Recommender System for Internet of Energy Applications

2021 ◽  
Author(s):  
Aya Nabeel Sayed ◽  
Faycal Bensaali ◽  
Yassine Himeur
Keyword(s):  
Energy Saving ◽  
Recommender System ◽  
Energy Demand ◽  
Privacy Preservation ◽  
Energy Savings ◽  
New Technologies ◽  
End Users ◽  
Environmental Data ◽  
Residential Areas ◽  
Increase Energy Efficiency

When investigating how people conserve energy, most researchers and decision-makers render a conceptual distinction between prevention (e.g. unplugging devices) and productivity measures. Nevertheless, such a two-dimensional approach is inefficient from both a conceptual and policy standpoint, since it ignores individual differences that influence energy-saving behavior. Preserving electricity in homes and buildings is a big concern, owing to a scarcity of energy resources and the escalation of current environmental issues. Furthermore, the COVID-19 social distancing policies have resulted in a temporary transition of energy demand from industrial and urban centers to residential areas, resulting in greater consumption and higher costs. In order to promote the sustainability and preservation of resources, the use of new technologies to increase energy efficiency in homes or buildings becomes increasingly necessary. Hence, the goal of the project is to provide consumers with evidence-based data on the costs and advantages of ICT-enabled energy conservation approaches, as well as clear, timely, and engaging information and assistance on how to realize the energy savings that are attainable, in order to boost user uptake and effectiveness of such techniques. End-users can visualize their consumption patterns as well as ambient environmental data using the Home-assistant user interface. More notably, explainable energy-saving recommendations are delivered to end-users in form of notifications via the mobile application to facilitate habit change. In this context, to the best of the authors’ knowledge, this is the first attempt for developing and implementing an energy-saving recommender system on edge devices. Thus, ensuring better privacy preservation since data are processed locally on the edge, without the need to transmit them to remote servers, as is the case with cloudlet platforms.

Analysis of Material Solutions of Exterior Walls with Contact Thermal Insulation System

2014 ◽  
Vol 635 ◽  
pp. 165-168 ◽  
Author(s):  
Silvia Vilčeková ◽  
Anna Sedláková ◽  
Eva Kridlova-Burdova ◽  
Ladislav Ťažký
Keyword(s):  
Energy Demand ◽  
Fossil Fuel ◽  
Residential Building ◽  
Environmental Parameters ◽  
Design Stage ◽  
Exterior Wall ◽  
Insulation System ◽  
Wall Structures ◽  
Heating Energy Demand ◽  
Fossil Fuel Energy

Nowadays, heating energy demand has become a significant estimator used during the design stage of any new building. The residential building sector consumes a significant amount of fossil fuel energy and thereby produces a large percentage of greenhouse gas emissions that contribute to global warming and climate change. The aim of the paper is analysis of thermo-physical and environmental parameters of proposed versions of exterior wall structures.

Environmental impacts and resource use from Australian pork production determined using life cycle assessment. 2. Energy, water and land occupation

2018 ◽  
Vol 58 (6) ◽  
pp. 1153 ◽  
Author(s):  
Stephen G. Wiedemann ◽  
Eugene J. McGahan ◽  
Caoilinn M. Murphy
Keyword(s):  
Fresh Water ◽  
Water Consumption ◽  
Resource Use ◽  
Energy Demand ◽  
Fossil Fuel ◽  
National Average ◽  
Land Occupation ◽  
Pork Production ◽  
Average Value ◽  
Fossil Fuel Energy

Utilisation of water, energy and land resources is under pressure globally because of increased demand for food, fibre and fuel production. Australian pork production utilises these resources both directly to grow and process pigs, and indirectly via the consumption of feed and other inputs. With increasing demand and higher costs associated with these resources, supply chain efficiency is a growing priority for the industry. This study aimed to quantify fresh water consumption, stress-weighted water use, fossil fuel energy use and land occupation from six case study supply chains and the national herd using a life cycle assessment approach. Two functional units were used: 1 kg of pork liveweight (LW) at the farm-gate, and 1 kg of wholesale pork (chilled, bone-in). At the farm-gate, fresh water consumption from the case study supply chains ranged from 22.2 to 156.7 L/kg LW, with a national average value of 107.5 L/kg LW. Stress-weighted water use ranged from 6.6 to 167.5 L H2O-e /kg LW, with a national average value of 103.2 L H2O-e /kg LW. Fossil fuel energy demand ranged from 12.9 to 17.4 MJ/kg LW, with a national average value of 14.5 MJ/kg LW, and land occupation ranged from 10.9 to 16.1 m2/kg LW, with a national average value of 16.1 m2/kg LW and with arable land representing 97% to 99% of total land occupation. National average impacts associated with production of wholesale pork, including impacts from meat processing, were 184 ± 43 L fresh water consumption, 172 ± 53 L H2O-e stress-weighted water, 27 ± 2.6 MJ fossil fuel energy demand and 25.9 ± 5.5 m2 land/kg wholesale pork. Across all categories through to the wholesale product, resource use was highest from the production of feed inputs, indicating that improving feed conversion ratio is the most important production metric for reducing the resource use. Housing type and energy generation from manure management also influence resource use requirements and may offer improvement opportunities.

scholarly journals A comprehensive economic optimization methodology of divided wall columns for biopolyol separation

2020 ◽  
Vol 7 (4) ◽  
pp. 191748
Author(s):  
Tao Chen ◽  
Lingjuan Lv ◽  
Yuanzhi Chen ◽  
Peng Bai
Keyword(s):  
Fossil Fuel ◽  
Energy Savings ◽  
Total Annual Cost ◽  
Economic Optimization ◽  
Efficient Design ◽  
Promising Technique ◽  
Box Behnken Design ◽  
Important Direction ◽  
Optimization Methodology ◽  
The Cost

Global energetic and environmental crises have attracted worldwide attention in recent years. Biomass is an important direction of development for limiting greenhouse gas emissions and replacing fossil fuel. As downstream products of biomass, some industrially valuable polyols are costly to separate via conventional distillation due to their near volatility. The use of fully heat-integrated divided wall columns (DWCs), which carry energy and equipment investment savings, is a promising technique for purifying biopolyol products. However, the design of DWCs is complex because of the greater freedom of units, so the optimization of all variables is essential to minimize the cost of separation. A response surface methodology (RSM)-based Box–Behnken design (BBD) was proposed and applied to study the interactions between groups of factors and the effects of variables on total annual cost (TAC) savings. The optimization of global variables with RSM was confirmed to be a powerful and reliable method, and the TAC savings reached 41.09% compared to conventional distillation. In short, efficient design, lower costs and energy savings for polyol separation will promote the wide application of environmentally friendly biopolyol.

A Case Study of Energy Saving by Cogeneration System in Hospital

2010 ◽  
Author(s):  
S. Okamoto
Keyword(s):  
Energy Demand ◽  
Energy Savings ◽  
High Efficiency ◽  
Hospital Setting ◽  
Electrical Energy ◽  
Electrical Heating ◽  
Public Network ◽  
Heating And Cooling ◽  
Cogeneration System

This paper describes a study that starts with an analysis of typical energy demand profiles in a hospital setting followed by a case study of a cogeneration system (CGS) under an energy service company (ESCO) project. The CGS idea is of an autonomous system for the combined generation of electrical, heating, and cooling energy in a hospital. The driving units are two high-efficiency gas engines that produce the electrical and heat energy. A gas engine meets the requirement for high electrical and heating energy demands; a natural gas-fuelled reciprocating engine is used to generate 735 kW of power. In our case, the electrical energy will be used only in the hospital. A deficit in electricity can be covered by purchasing power from the public network. Generated steam drives three steam-fired absorption chillers and is delivered to individual heat consumers. This system can provide simultaneous heating and cooling. No technical obstacles were identified for implementing the CGS. The average ratio between electric and thermal loads in the hospital is suitable for CGS system operation. An analysis performed for a non-optimized CGS system predicted a large potential for energy savings.

Solar Thermal Energy

2018 ◽  
Author(s):  
E. L. Wolf
Keyword(s):  
Solar Cells ◽  
Thermal Energy ◽  
Fossil Fuel ◽  
Rankine Cycle ◽  
Carnot Cycle ◽  
The Sun ◽  
Solar Thermal Energy ◽  
Heat Engines ◽  
Direct Use ◽  
Fossil Fuel Energy

The Sun’s spectrum on Earth is modified by the atmosphere, and is harvested either by generating heat for direct use or for running heat engines, or by quantum absorption in solar cells, to be discussed later. Focusing of sunlight requires tracking of the Sun and is defeated on cloudy days. Heat engines have efficiency limits similar to the Carnot cycle limit. The steam turbine follows the Rankine cycle and is well developed in technology, optimally using a re-heat cycle of higher efficiency. Having learned quite a bit about how the Sun’s energy is created, and how that process might be reproduced on Earth, we turn now to methods for harvesting the energy from the Sun as a sustainable replacement for fossil fuel energy.

scholarly journals Energy Performance Assessment of Innovative Building Solutions Coming from Construction and Demolition Waste Materials

Materials ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1226
Author(s):  
Beatriz Fraga-De Cal ◽  
Antonio Garrido-Marijuan ◽  
Olaia Eguiarte ◽  
Beñat Arregi ◽  
Ander Romero-Amorrortu ◽  
...  
Keyword(s):  
Thermal Insulation ◽  
Energy Demand ◽  
Energy Savings ◽  
Flow Analysis ◽  
Weather Conditions ◽  
Energy Performance ◽  
Construction And Demolition Waste ◽  
The European Union ◽  
Demolition Waste ◽  
The Impact

Prefabricated solutions incorporating thermal insulation are increasingly adopted as an energy conservation measure for building renovation. The InnoWEE European project developed three technologies from Construction and Demolition Waste (CDW) materials through a manufacturing process that supports the circular economy strategy of the European Union. Two of them consisted of geopolymer panels incorporated into an External Thermal Insulation Composite System (ETICS) and a ventilated façade. This study evaluates their thermal performance by means of monitoring data from three pilot case studies in Greece, Italy, and Romania, and calibrated building simulation models enabling the reliable prediction of energy savings in different climates and use scenarios. Results showed a reduction in energy demand for all demo buildings, with annual energy savings up to 25% after placing the novel insulation solutions. However, savings are highly dependent on weather conditions since the panels affect cooling and heating loads differently. Finally, a parametric assessment is performed to assess the impact of insulation thickness through an energy performance prediction and a cash flow analysis.

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 Interdependencies of Infrastructure Investment Decisions in Multi-Energy Systems—A Sensitivity Analysis for Urban Residential Areas

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 112-145
Author(s):  
Daniel Then ◽  
Johannes Bauer ◽  
Tanja Kneiske ◽  
Martin Braun
Keyword(s):  
Sensitivity Analysis ◽  
Energy Demand ◽  
Business Models ◽  
Linear Optimization ◽  
Investment Decisions ◽  
Energy System ◽  
Mixed Integer ◽  
The European Union ◽  
Residential Areas ◽  
Mixed Integer Linear Optimization

Considering the European Union (EU) climate targets, the heating sector should be decarbonized by 80 to 95% up to 2050. Thus, the macro-trends forecast increasing energy efficiency and focus on the use of renewable gas or the electrification of heat generation. This has implications for the business models of urban electricity and in particular natural gas distribution network operators (DNOs): When the energy demand decreases, a disproportionately long grid is operated, which can cause a rise of grid charges and thus the gas price. This creates a situation in which a self-reinforcing feedback loop starts, which increases the risk of gas grid defection. We present a mixed integer linear optimization model to analyze the interdependencies between the electricity and gas DNOs’ and the building owners’ investment decisions during the transformation path. The results of the investigation in a real grid area are used to validate the simulation setup of a sensitivity analysis of 27 types of building collectives and five grid topologies, which provides a systematic insight into the interrelated system. Therefore, it is possible to identify building and grid configurations that increase the risk of a complete gas grid shutdown and those that should be operated as a flexibility option in a future renewable energy system.

Modelling of an Optimized Microgrid Model by Integrating DG Distributed Generation Sources to IEEE 13 Bus System

2021 ◽  
Vol 5 (2) ◽  
pp. 18-25
Author(s):  
Bisma Imtiaz ◽  
Imran Zafar ◽  
Cui Yuanhui
Keyword(s):  
Renewable Energy ◽  
Distributed Generation ◽  
Energy Demand ◽  
High Reliability ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Efficient Manner ◽  
Matlab Simulink ◽  
Control Scheme ◽  
Power Quality Improvement

Due to the rapid increase in energy demand with depleting conventional sources, the world’s interest is moving towards renewable energy sources. Microgrid provides easy and reliable integration of distributed generation (DG) units based on renewable energy sources to the grid. The DG’s are usually integrated to microgrid through inverters. For a reliable operation of microgrid, it must have to operate in grid connected as well as isolated mode. Due to sudden mode change, performance of the DG inverter system will be compromised. Design and simulation of an optimized microgrid model in MATLAB/Simulink is presented in this work. The goal of the designed model is to integrate the inverter-interfaced DG’s to the microgrid in an efficient manner. The IEEE 13 bus test feeder has been converted to a microgrid by integration of DG’s including diesel engine generator, photovoltaic (PV) block and battery. The main feature of the designed MG model is its optimization in both operated modes to ensure the high reliability. For reliable interconnection of designed MG model to the power grid, a control scheme for DG inverter system based on PI controllers and DQ-PLL (phase-locked loop) has been designed. This designed scheme provides constant voltage in isolated mode and constant currents in grid connected mode. For power quality improvement, the regulation of harmonic current insertion has been performed using LCL filter. The performance of the designed MG model has been evaluated from the simulation results in MATLAB/ Simulink.

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