Energy and Economic Analysis for Greenhouse Envelope Design

2018 ◽  
Vol 61 (6) ◽  
pp. 1795-1810
Author(s):  
James Bambara ◽  
Andreas K. Athienitis

Abstract. The energy consumption of a building is significantly impacted by its envelope design, particularly for greenhouses where coverings typically provide high heat and daylight transmission. Energy and life cycle cost (LCC) analysis were used to identify the most cost-effective cladding design for a greenhouse located in Ottawa, Ontario, Canada (45.4° N) that employs supplemental lighting. The base case envelope design uses single glazing, whereas the two alternative designs consist of replacing the glass with twin-wall polycarbonate and adding foil-faced rigid insulation (permanent or movable) on the interior surface of the glass. All the alternative envelope designs increased electricity consumption for lighting and decreased heating energy use except when permanent or movable insulation was applied to the north wall and in the case of permanent insulation on the north wall plus polycarbonate on the east wall. This demonstrates how the use of reflective opaque insulation on the north wall can be beneficial for redirecting light onto the crops to achieve simultaneous reductions in electricity and heating energy costs. A maximum reduction in LCC of 5.5% (net savings of approximately $130,000) was achieved when permanent insulation was applied to the north and east walls plus polycarbonate on the west wall. This alternative envelope design increased electricity consumption for horticultural lighting by 4.3%, reduced heating energy use by 15.6%, and caused greenhouse gas emissions related to energy consumption to decrease by 14.7%. This analysis demonstrates how energy and economic analysis can be employed to determine the most suitable envelope design based on local climate and economic conditions. Keywords: Artificial lighting, Consistent daily light integral, Energy modeling, Envelope design, Greenhouse, Life cycle cost analysis, Light emitting diode, Local agriculture.

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4046 ◽  
Author(s):  
Sooyoun Cho ◽  
Jeehang Lee ◽  
Jumi Baek ◽  
Gi-Seok Kim ◽  
Seung-Bok Leigh

Although the latest energy-efficient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three different methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major effect on energy consumption and revealed that these key variables alone, not the default values of many different items in simulation analysis, can ensure the reliable prediction of energy consumption.


2021 ◽  
Author(s):  
Amir Fereidouni Kondri

This report presents the methodology for determining least cost energy efficient upgrade solutions in new residential housing using brute force sequential search (BFSS) method for integration into the reference house to reduce energy consumption while minimizing the net present value (NPV) of life cycle costs. The results showed that, based on the life cycle cost analysis of 30 years, the optimal upgrades resulted in the average of 19.25% (case 1), 31% (case 2a), and 21% (case 2b) reduction in annual energy consumption. Economic conditions affect the sequencing of the upgrades. In this respect the preferred upgrades to be performed in order are; domestic hot water heating, above grade wall insulation, cooling systems, ceiling insulation, floor insulation, heat recovery ventilator, basement slab insulation and below grade wall insulation. When the gas commodity pricing becomes high, the more energy efficient upgrades for domestic hot water (DHW) get selected at a cost premium.


Author(s):  
Владимир Борисович Барахнин ◽  
Светлана Валентиновна Мальцева ◽  
Константин Владимирович Данилов ◽  
Василий Вячеславович Корнилов

Современные социотехнические системы в различных областях характеризуются наличием в их составе большого количества интеллектуального оборудования, которое может самостоятельно регулировать собственное потребление энергии, а также взаимодействовать с другими потребителями в процессах принятия решений и управления. Одна из таких отраслей - энергетика, где самоорганизация и системы коллективного потребления являются наиболее перспективными с точки зрения обеспечения эффективности использования энергоресурсов. Рассмотрены подходы к установлению статических и динамических тарифов на электроэнергию. Проведено сравнение двух моделей энергопотребления - статического двухтарифного и динамического, учитывающих рациональное поведение умных устройств, способных выбирать лучшие режимы для потребления электроэнергии. Показано влияние количества таких устройств на возможность достижения равномерного потребления при использовании второй модели. Modern socio-technical systems in various fields include a large number of smart equipment that can independently regulate its own energy consumption, as well as interact with other consumers in decision-making and management processes. Energy is one of these areas. Self-organization and collective self-consumption are the most promising in terms of ensuring the efficiency of energy use. Existing and prospective approaches to using static and dynamic time-based tariffs are under consideration. The paper presents a mathematical description of two models of energy consumption: a static model based on the allocation of two zones with a fixed duration and tariffs for each one and a dynamic model of two-tariff accounting with feedback, which assumes tariffs changing based on the results of the analysis of current electricity consumption. A pilot study of both models was conducted by using energy consumption data and taking into account the rational behavior of smart devices as consumers who can choose the best periods for electricity consumption. During the experiments it was investigated how an increase in the share of smart devices in the composition of electricity consumers as well as options for establishing zones and tariffs, affect the possibility of achieving uniform consumption during the day. Experiments have shown that with a small proportion of smart devices, acceptable results that reduce the variation in the consumption function can favor usage of the model without feedback. An increase in the number of actors in the system inevitably requires including a feedback mechanism into the system that allows the resource supplier to prevent excessive concentration of smart devices during the period of the cheaper tariff. However, when the share of smart devices exceeds a certain critical value, a pronounced inversion of the times of cheap and expensive tariffs occurs in two successive iterations. In this case, in order to ensure a quite even distribution of electricity consumption, it is advisable for the supplier to return to the single tariff rate. Thus, an excessive increase in the number of actors in the system can neutralize the effect of their use


2020 ◽  
Vol 164 ◽  
pp. 01002
Author(s):  
Svetlana Maksimova ◽  
Anna Shkileva ◽  
Ekaterina Verevkina

The main goal of this study is evaluation of reconstruction options for water pumping stations, regarding various factors (equipment purchase cost, maintenance, energy consumption). The search for the most profitable solution was carried out using the life cycle cost methodology for the urban water supply system’s first lift pump station. An analysis of the operating modes of the pumping station was carried out using curves of pumps and system. It was found that the option with a higher purchase price has the best technological indicators, including energy consumption. The expediency of the complete replacement of pumping equipment is confirmed by an analysis of life cycle costs.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Sung-Min Choi ◽  
Yeon-Sil Lee

Currently, repair and maintenance cycles that follow the completion of construction facilities lead to the necessitation of subsequent data on the analysis of study and plan for maintenance. As such, an index of evaluation was drafted and a plan of maintenance cycle was computed using the investigation data derived from surveying target housing units in permanent rental environmental conditions, with a minimum age of 20 years, and their maintenance history. Optimal maintenance and replacement methods were proposed based on this data. Economic analysis was conducted through the Risk-Weighted Life Cycle Cost (RWLCC) method in order to determine the cost analysis of maintenance life cycle methods used for repair. Current maintenance cycle methods that have been used for 20 years were also compared with alternative maintenance cycles.


2016 ◽  
Vol 43 (2) ◽  
pp. 140-147 ◽  
Author(s):  
XIAODONG CHEN ◽  
JENNIFER DE LA ROSA ◽  
M. NILS PETERSON ◽  
YING ZHONG ◽  
CHUNTIAN LU

SUMMARYHousehold consumption is a major contributor to global greenhouse gas emissions. Some behaviours (for example energy use and vehicle use) may have far larger impacts than others (for example green consumerism of household products). Here, the driving forces of green consumerism and two domestic energy uses (electricity consumption and vehicle fuel use) are compared. This study found that environmental attitudes predicted green consumerism, but not electricity consumption or vehicle fuel use. Furthermore, green consumerism was correlated with income and individual level demographic factors, while energy consumption was primarily predicted by household size and structural constraints. Because household energy consumption has greater environmental impacts than green consumerism, policies that aim to improve pro-environmental attitudes may not be effective in mitigating greenhouse gas emissions. Policies should rather aim to change structural constraints influencing transportation and household energy decisions and improve the conspicuousness of household energy consumption.


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