Dissecting Energy Usage in Industrial Buildings - Literature review Example

?Introduction and Background to Problem The use of buildings entails a number of energy based costs including the construction phase, the operation phase, maintenance and refurbishment requirements as well as the demolition phase to remove the building after useful life ends. It is significant to observe that the greatest consumption of energy in buildings occurs in the operation phase. In terms of order of magnitude, operation of buildings tends to consume up to half the energy required by a building throughout its useful life (Cole & Kernan, 1996, p.313). This fact has important implications for energy usage as well as carbon dioxide emissions globally. An estimated 30% to 40% of all primary energy usage stems from building operation along with a large potential to reduce carbon dioxide emissions (Colmenar-Santos et al., 2013, p.66). In a similar manner, other research on the matter shows that buildings tend to consume 40% of the total energy being consumed globally along with 25% of the water and another 40% of other resources. Consequently, buildings are deemed responsible for about one third of all green house gas (GHG) emissions too (Katunsky et al., 2013, p.3). The rapid pace of industrialisation and the requirement for increased industrial buildings also tends to support the idea that building energy usage efficiency is a top priority issue. Projections on urbanisation depict that by 2050; around 67% of the global population will live in urban centres such that nations with the largest urban centres will display urbanisation rates of up to 86%. It would then be reasonable to expect that industrial buildings and their demand for energy would only rise steeply with time (Adriaenssens et al., 2013, p.1945). The operation of buildings entails significant carbon dioxide emissions on account of inefficient insulation, heating and cooling mechanism as well as lighting applications and the use of appliances. It is estimated that more energy efficient buildings have the potential to reduce carbon dioxide emissions by 3.7 giga tonnes every single year where the cost of one tonne of carbon dioxide emissions is an estimated 40 Euros (McKinsey, 2007, p.4). Other research also supports the idea that reduced heating demands, greater emphasis on renewable energy sources and bolstered efficiency of supply chain mechanisms allows for a reduction in the energy demands to operate buildings (Colmenar-Santos et al., 2013, p.66). Building heating requirements reappear repeatedly as a major consumer of energy and thus can be seen as impacting building energy usage significantly. In addition, building energy usage and its efficiency can be seen as dependant on other physical, climatic and human factors (Katunsky et al., 2013, p.3). While one perspective of looking at the problem tends to define energy usage efficiency as a key problem, other research suggests that the use of energy to cool and heat building interiors is unjustified. The use of mechanical heating and cooling measures for thermal comfort are being questioned as valid means to maintain human thermal comfort levels in buildings (Susanti et al., 2011, p.211). This does not imply that energy usage in buildings is unjustified outright, especially for regions with severe heat or cold climates, but rather that energy usage is unjustified for places where the climate can support a lack of heating and cooling requirements. It must also be noted that greener buildings are beginning to create greater commercial value, especially in terms of rent. Research indicates that commercial buildings with lower energy loads tend to command more rent than comparable commercial buildings with higher energy demands (Eicholtz et al., 2009, p.1). This literature review will look into already conducted research to find out the major uses for energy in industrial buildings, the various methods to reduce the consumption of energy in industrial buildings and to discover any research gaps in existing literature. Dissecting Energy Usage in Industrial Buildings In order to allow refurbishment of industrial buildings to promote more efficient energy use during building operation, it would be necessary to look into the major consumers of energy in industrial spaces. There has been more research directed at dealing with heating, ventilation and air conditioning (HVAC) loads than any other consumers of energy in industrial buildings (Colmenar-Santos et al., 2013, p.66) (Gustafsson, 2006, p.67) (Katunsky et al., 2013, p.3) (Susanti et al., 2011, p.212) (Cole & Kernan, 1996, p.311). In comparison, there has been relatively low research on auxiliary areas such as lighting (Adriaenssens et al., 2013, p.1945). One major reason for this observation is that HVAC related functions consume significantly more energy than other processes in industrial buildings and so they are singled out for research more. Alternatively, another reason for this lope sided behaviour is the potential savings that HVAC offers compared to lighting improvements. Since lighting imposes a smaller load, the improvement in energy efficiency obtained would be small as well unlike HVAC improvements. Research indicates that for an industrial building life cycle of 50 years, the greatest consumers of energy are heating, cooling and ventilation requirements. Observations of Cole & Kernan (1996, p.314) of two office spaces in Toronto and Vancouver showed that these office spaces consumed 90% and 80% of their total energy requirements for heating, cooling, lighting and ventilation purposes respectively. It needs to be kept in mind that Cole and Kernan’s observations are valid for a cold climate such as Canada where the research was carried out and variations are possible for more pleasant climate regions. Comparisons of energy usage in buildings and their growth over time indicate that the biggest user of energy in buildings is HVAC. Research places the relative weight of HVAC energy requirements at 50% of the overall energy usage for commercial buildings. In addition, HVAC energy requirements are followed by lighting requirements that consume up to 15% of the entire energy followed closely by appliances at 10% of the overall energy usage (Perez-Lombard et al., 2008, p.397). It could be surmised from such research that the biggest contender for energy are HVAC requirements followed by lighting needs. Energy Usage Reduction Problems and Methods The chief problem in assessing energy usage in industrial buildings is the lack of an integrated building management system (BMS). Most research conducted on refurbishment of industrial buildings tends to skip out on BMS details altogether. It is also typical to notice that BMS based data is cumbersome to deal with since there are few possibilities for graphical visualisation and management of such data (Colmenar-Santos et al., 2013, p.67). Most research conducted on energy efficient refurbishment tends to lose credibility given the lack of details of the BMS. Since the methods to create baselines and form comparisons after refurbishment are rarely described, it tends to create a lot of speculation. A detailed refurbishment scheme for a furniture factory has been presented by Gustafsson (2006) that relies on the use of the OPERA model to achieve improvements in the existing heating system (Gustafsson, 2006, p.2231). The subject research was conducted on the furniture factory of Bringholtz Furniture Limited that had a combination of old and new building sections with the oldest sections dating back to the early twentieth century. The building used a conventional boiler as well as regular electricity based heating to keep the premises heated. The presence of wood chips and saw dust as well as other such by products of wood working allowed the factory to utilise a wood chip boiler to generate heat. Retrofitting research showed that wood chip heating was inefficient since the steam system had a number of leaks such as from steam traps and poorly insulated sections. Using OPERA, a load management scheme was proposed for heating requirements that relied less on electricity and more on wood chip boiler steam for thermal comfort heating. However, it was also realised that the costs associated with the recommended upgrades was a significant capital cost. Proposed retrofitting effort included extra insulation, triple glazed windows in place of double glazed windows, changes in the wood chip transport system and some heating system retrofits such as new steam traps (Gustafsson, 2006, pp.2235-38). Although the proposed retrofitting scheme showed savings in the longer run, but there was no mention of how the initial finances would be derived. It must also be realised that retrofits had not been performed in the system on account of high capital costs that offset long term savings. For example, the factory was using electricity based heating that cost four times as much as wood chip based heating (Gustafsson, 2006, p.239). Another interesting thing that derives from this research is the reliance on situational factors such as the use of wood chips for heating. The recommendations of the research by Gustafsson (2006) are limited to cold climate industrial buildings where wood chips are easily available. These findings cannot be implemented in cases such as a company headquarter building requiring air conditioning (Colmenar-Santos et al., 2013, p.68) or for heating requirements of industrial buildings where by products are not available for burning (Katunsky et al., 2013, p.8). Given this situation, it can be surmised that industrial building refurbishment requires quantitative exploration before quantitative analysis to take advantage of localised possibilities. Figure 1 - Schematic view of the OPERA model sourced from (Gustafsson, 2006, p.2231) Although BMS are present and installed in certain industrial buildings but their degradation over time requires that reassessment be performed in order to discover weaknesses to implement new refurbishment schemes. Colmenar-Santos et al. (2013) investigated the degradation of a BMS installed at the Technology Center of Festo (also known as Festo TC) and researched predictive weather schemes to reduce the HVAC and other energy loads. It was proposed that BMS calculations and actuation tends to suffer over time from (Colmenar-Santos et al., 2013, p.72): component degradation; system errors; false operation due to maintenance failures such as: valves opened for maintenance but not closed; blocked water supply; improper set points. Simulations were performed in order to decipher what the actual BMS behavior ought to be and how BMS was actually performing. Comparison of measurements with the stipulated baselines would provide for error discovery and hence the need for any refurbishment could be investigated further. The basic scheme is presented in the diagram below for explanation. Here it must be taken to note that BMS provides for an extremely efficient energy management methods but the initial costs may be too high to install BMS in smaller industrial buildings such as the furniture factory discussed by Gustafsson (2006, p.2231). This explains why Gustafsson (2006) chose to research using physical observations while Colmenar-Santos et al. (2013) chose to research using simulations. This provides that industrial buildings provide for thresholds where the life cycle cost (LCC) under the OPERA model does not justify the use of BMS for energy management. Figure 2 - Principle of simulation based performance observation sourced from (Colmenar-Santos et al., 2013, p.73) The simulation results highlighted a number of different ambiguities in the overall control scheme such as an error in the heating and cooling coils of an office air handling unit. This allowed detection of the error so that the component could be replaced to bolster heating and cooling efficiency. Similarly, problems were detected with the third floor thermally activated controls (TAC) for ceiling ventilation where the predicted temperature was 2K lower than that being measured. Physical checks showed that the third floor ceiling TAC was out of order due to malfunctioning stopcocks (Colmenar-Santos et al., 2013, pp.74-75). Simulations also provided for different predictive schemes to reduce the energy load of the Festo TC complex. The simplest scheme provided for the TAC to be turned on all day while other schemes advocated time windows where the TAC was turned on. Simulation results provided that if the TAC were turned on between 4 am and 6 pm, it would provide significant energy savings of 37% (Colmenar-Santos et al., 2013, p.76). On the other hand, it would also require major refurbishment of the software being used for BMS as well as extensive testing that may not be feasible under the provided operational constraints such as testing during the operational hours at the site. It can also be realized that energy audits on a regular basis can provide for identifying any malfunctions in an industrial building’s energy load. The findings can be used in turn to generate refurbishment plans to reduce energy losses. In another study, it was observed that the heating and cooling loads in a medical manufacturing facility tended to vary with the production loads as well as with other factors such as weather changes (Hesselbach et al., 2008, p.626). The profiling of production machines indicated that the heat produced by such machines needed dissipation in order to keep produced products at optimal conditions during and after manufacturing. The bifurcation of production loads and technical building services allows for a simpler approach to deal with refurbishment plans to reduce energy inefficiency. However, research proves that bifurcation of the production load from the building services load is not really feasible since building services are being powered from the same sources that are powering the production lines. For example, it may be possible on a hot day that cooling load for both production lines and building services goes up while either system may have been optimized individually. This in turn would lead to a failure since global optimization has not been performed. Simulation results from research tend to reinforce the view that most industrial refurbishment plans for energy efficiency improvements are limited since optimization is performed on isolated systems (Hesselbach et al., 2008, p.627). The nature of industrial systems is complex and tends to vary between industrial establishments leading to further complications in energy usage calculations. This observation would reinforce the idea that refurbishment plans to increase building energy usage efficiency need to account for global minimas and maximas rather than deal with localized optimas. While most research has been diverted to heating and cooling loads for industrial buildings refurbishment, there has been some research on lighting loads as well. Adriaenssens et al. (2013) have researched the possiblity of installing north light roof arrangements at the same latitude around the globe. Research was carried out using computer simulations to determine how a theoretical industrial building’s energy load would change if a north light roof were installed. It is notable that unlike other research on industrial building refurbishment, this research considered the effect of lighting load through a holistic appaorch. In addition, the effect of the lighting load on the heating and cooling loads was also taken into account (Adriaenssens et al., 2013, p.1947). Moreover, the simulations performed compared the performance of convex, concave and flat roof structures for the installation of north light roof. Results of the simulation showed that a saw tooth profile was preferred to other forms of north light roof shapes (Adriaenssens et al., 2013, p.1957). However, the model suffered limitations on account of humidity levels and air conditioning quality levels since they were not considered for the simulations. It is also interesting to note that the final optimisation problem required creating a balance between the HVAC load due to the increased heat input from the north light roof installation. Other research on the matter tends not to optimise solutions on multiple planes perhaps because lighting loads are not considered for research. Research has also been directed at discerning the efficacy of naturally ventilated cavities as means of cooling industrial buildings. A mathematical model for cavities and air flow was created by Susanti et al. (2011) which was later implemented in a factory in Toyohashi for verification. The derivation of the mathematical model relies on the use of cooling load constraints alone without any attention being paid to intervening factors such as escaping air from within the factory building (Susanti et al., 2011, p.213). In addition, the subject research carried out testing of the proposed natural cavity scheme on a limited scale on a factory roof. The results were promising as a 4.4oC reduction in temperature was achieved although it was not discussed if it were possible to integrate such a cavity ventilation system with cooling load limits of less than ambient temperature. The target system for the proposed natural cavity ventilation was meant to be kept at an ambient temperature of 26oC only (Susanti et al., 2011, p.211). Additionally, there was no consideration for costs associated with developing the proposed cavity system and its installation in existing industrial buildings. It might be possible that the manufacturing and installation costs of such a scheme would not be able to justify themselves due to a long payback period or relative complication in retrofitting existing industrial buildings. Findings and Learning Research on BMS did not properly specify the entire BMS scheme in terms of the required hardware, the software used and the associated costs. This in turn tends to reduce the credibility of the BMS since BMS installations are typically expensive and would thus not be suitable for small industrial establishments. BMS does provide for efficient energy control, auditing and affirmative action but the large costs prevent its installation. In addition, the large amount of human expertise required in such installations due to the relative level of complication also tends to act as a stumbling block as a feasible industrial building refurbishment option for energy consumption reduction. Frameworks for industrial buildings refurbishment for energy efficiency increases fail to take into account localised possibilities available in industries to lower the costs for refurbishment. For example, a manufacturing industrial company having a machine shop could augment their refurbishment activities by performing in house fabrication. It could be argued that such fabrication could lead to a loss of production. However, industrial processes tend to vary in terms of the load on the system and so when the fabrication shop or machine shop is lightly loaded, they could be used to produce devices for bolstering energy efficiency. Most research on the matter, which takes onto the financial dimension of refurbishment, tends to see obstacles in terms of high costs of refurbishment. Using localised resources would allow major decreases in refurbishment costs and would make energy efficiency refurbishment more feasible. A review of the current literature provides that BMS have the potential to identify various areas where energy is being lost leading to energy’s inefficient use in industrial buildings. However, it may not be possible to install BMS and the supporting hardware in order to identify such losses in all forms of industrial spaces. It has to be noticed that BMS based solutions are more feasible for relatively large industrial areas such as a manufacturing complex or a large office space. However, the installation and operation of a BMS in a small industrial building such as a small machine shop could not be justified in terms of the payback period. The large costs associated with installing the BMS hardware and software as well as the costly human expertise needed to maintain such systems may not be affordable for small industrial buildings. Hence, it could be surmised that installing a BMS is not a particularly attractive option for refurbishing an industrial building for increasing energy efficiency, especially for smaller industrial buildings. However, it still needs to be discerned what kind of parameters should be considered to classify what industrial buildings warrant a BMS installation and which ones do not. Further research ought to classify how LCC for BMS components can be pitted against building energy loads considering that energy loads tend to change throughout the year. For example, would it be feasible to place greater emphasis on heating and cooling energy load or could lighting energy load be considered as a more fair weather indicator for BMS installation since it does not tend to vary with weather. In addition, another important consideration is the structure of software required to run a BMS. Given the fact that different industrial buildings have different operating characteristics, would it be optimal to use singular BMS software for all industrial buildings or would it be better to use a modular structured BMS that can be customised from one industrial building to another? Refurbishment for industrial buildings energy usage needs to provide due consideration to process loads too unless the equipment for heating, cooling, lighting and ventilation loads is separate for the production lines and the building space. However, this possibility is highly unlikely given the high costs of procuring differentiated equipment, operating and maintaining such equipment and installation of differentiated equipment. Therefore, it would only make sense if building energy usage were optimised while considering process loads. This does not indicate that process loads need to be recalculated and optimised (since it falls outside the scope of the current research) but rather that the overall load’s minimum and maximum levels need to be kept in sight when planning a refurbishment. For example, cooling load optimisation for an industrial building may require the use of a refrigeration compressor that is shared by the process lines as well as the industrial building. The process load needs to be considered in terms of the minimum and maximum loads so that industrial building cooling load optimisation does not infringe on process loads such as during very hot days in a year. Most research on isolated system refurbishment in industrial buildings proposes a change of equipment without considering the attached expense. A refurbishment plan need not alter or replace existing equipment only but could also try to manage the loads more smartly. Industrial building energy load needs to be optimised keeping in purview the largest energy consumers namely heating, cooling, ventilation and lighting. Research shows that optimised natural lighting to reduce lighting loads can have significant negative effects on cooling loads leading to a greater consumption of energy than before the refurbishment. It would follow from this that these major competing variables need to be considered in unison for an effective energy optimisation problem’s solution. Optimising one of these variables at the cost of the other for industrial building energy usage refurbishment can lead to a greater need for energy than before the refurbishment. These factors mix with other factors such as the climate where the industrial building is located to determine how one factor influences the other. However, there is no deniability that these factors influence each other under all circumstances and so need to be considered together for optimisation problems. Bibliography Adriaenssens, S., Liu, H., Wahed, M. & Zhao, Q., 2013. Evaluation and Optimization of a Traditional North-Light Roof on Industrial Plant Energy Consumption. Energies, 6, pp.1944-60. Cole, R.J. & Kernan, P.C., 1996. Life-Cycle Energy Use in Office Buildings. Building and Environment, 31(4), pp.307-17. Colmenar-Santos, A., Lober, L.N.T.d., Borge-Diez, D. & Castro-Gil, M., 2013. Solutions to reduce energy consumption in the management of large buildings. Energy and Buildings, 56, pp.66-77. Eicholtz, P., Kok, N. & Quigley, J.M., 2009. Doing well by doing good? Green Office Buildings. Working Paper Series. Berkeley, California: University of California at Berkeley University of California Energy Institute. Gustafsson, S.-I., 2006. Refurbishment of industrial buildings. Energy Conservation and Management, 47, pp.2223-39. Hesselbach, J. et al., 2008. Energy Efficiency through optimized coordination of production and technical building services. In Conference Proceedings LCE2008 - 15th CIRP International Conference on Life Cycle Engineering. Sydney, 2008. The University of New South Wales. Katunsky, D. et al., 2013. Analysis of thermal energy demand and saving in industrial buildings: A case study in Slovakia. Building and Environment, pp.1-35. McKinsey, 2007. A cost curve for greenhouse gas reduction. The McKinsey Quarterly, 1, pp.1-7. Perez-Lombard, L., Ortiz, J. & Pout, C., 2008. A review on buildings energy consumption information. Energy and Buildings, 40, pp.394-98. Susanti, L., Homma, H. & Matsumoto, H., 2011. A naturally ventilated cavity roof as potential bene?ts for improving thermal environment and cooling load of a factory building. Energy and Buildings, 43, pp.211-18. Read More