Development of a dynamic operational rating system in energy performance certificates for existing buildings: Geostatistical approach and data-mining technique

Koo, Choongwan,Hong, Taehoon Elsevier 2015 APPLIED ENERGY Vol.154 No.-

<P><B>Abstract</B></P> <P>The operational rating system in building energy performance certificates (EPCs) has been used for systematically monitoring and diagnosing the energy performance in the operation and maintenance phases of existing buildings. However, there are several limitations of the conventional operational rating system, which can be subdivided into three aspects: (i) building category; (ii) region category; and (iii) space unit size. To overcome these challenges, this study conducted the problem analysis of the conventional operational rating system for existing buildings by using the statistical and geostatistical approaches. Based on the problem analysis, this study developed the dynamic operational rating (DOR) system for existing buildings by using the data-mining technique and the probability approach. The developed DOR system can be used as a tool for building energy performance diagnostics. To validate the applicability of the developed DOR system, educational facilities were selected as the representative type of existing buildings in South Korea. As a result, it was determined that the developed DOR system can solve the irrationality of the conventional operational rating system (i.e., the negative correlation between the space unit size and the CO<SUB>2</SUB> emission density). Namely, the operational ratings of small buildings were adjusted upward while those of large buildings were adjusted downward. The developed DOR system can allow policymakers to establish the reasonable operational rating system for existing buildings, which can motivate the public to actively participate in energy-saving campaigns.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Problem analysis of the conventional EPCs was conducted in terms of three issues. </LI> <LI> Three issues consist of the building category, region category and space unit size. </LI> <LI> Dynamic operational rating (DOR) system in EPCs for existing building was developed. </LI> <LI> The DOR can be used as a tool for building energy performance diagnostics. </LI> <LI> The DOR can allow policymakers to establish a reasonable operational rating in EPCs. </LI> </UL> </P>

A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects

Koo, ChoongWan,Hong, TaeHoon,Hyun, ChangTaek,Koo, KyoJin Canadian Science Publishing 2010 Canadian journal of civil engineering Vol.37 No.5

<P> Decision-making in the early stage of a project has a significant impact on the project. However, limited and uncertain information on the project and a complex correlation among various factors that affect the project’s construction duration and cost, make it difficult to predict and manage the project. Therefore, this study developed a case-based reasoning (CBR)-based hybrid model with which to predict the construction duration and cost of a project in its early stage. One hundred and one cases among multi-family housing projects that were completed between 2000 and 2005 were used. The CBR-based hybrid model developed in this study is the result of integrating the advantages of (i) prediction methodologies, such as case-based reasoning, multiple regression analysis, and artificial neural networks, (ii) the optimization process using a genetic algorithm, and (iii) the probability distribution and the analysis process of outlier using Monte-Carlo simulation. The results of this study are expected to support the owners and managers who are in charge of estimating budget and construction duration in both public and private sectors, in predicting accurately the construction duration and cost at the business planning or early stage of a project. </P>

An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system

Koo, Choongwan,Hong, Taehoon,Lee, Minhyun,Kim, Jimin Elsevier 2016 RENEWABLE & SUSTAINABLE ENERGY REVIEWS Vol.57 No.-

<P><B>Abstract</B></P> <P>The photovoltaic (PV) system has been highlighted as a sustainable clean energy source. To successfully implement the PV system in a real project, several impact factors should be simultaneously considered. This study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solution in implementing the rooftop PV system. This study was conducted in six steps: (i) establishment of database; (ii) generation of the installation scenarios in the rooftop PV system; (iii) energy simulation using the software program ׳<I>RETScreen</I>׳; (iv) economic and environmental assessment from the life cycle perspective; (v) establishment of the iMOO process using a genetic algorithm; and (vi) systemization of the iMOO model using a <I>Microsoft-Excel-based VBA</I>. Two criteria were used to assess the robustness and reliability of the developed model. In terms of effectiveness, the optimal solution was determined from a total of 399,883,120 (=91×49×19×80×59) possible scenarios by comprehensively considering various factors. In terms of efficiency, it was concluded that the time required for determining the optimal solution was 150s. The developed model makes it possible for final decision-maker such as construction managers or contractors to determine the optimal solution in implementing the rooftop PV system in the early design phase.</P>

Development of the life-cycle economic and environmental assessment model for establishing the optimal implementation strategy of the rooftop photovoltaic system

KOO, Choongwan,HONG, Taehoon,PARK, Joonho Vilnius Gediminas Technical University 2018 TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY Vol.24 No.1

<P>To maximize the life-cycle economic and environmental performance of the rooftop pho­tovoltaic (PV) system in real projects, it is necessary to consider several factors such as regional climate factors (i.e., geographical and meteorological factors) and building characteristics (i.e., on-site installation factors, rooftop area limit, and budget limit). Towards this end, this study aimed to develop the life-cycle economic and environmental assessment model for establishing the optimal implementation strategy of the rooftop PV system. The robustness and reliability of the developed model were evaluated in terms of two perspectives: (i) for the effectiveness of the optimal solution, the optimization results were generated by considering the regional climate factors and building characteristics. Namely, the results for SIR25 (saving to investment ratio at year 25), which was set at the optimization goal, were 2.540 (Busan, southern part of South Korea), 2.485 (Daejeon, central part of South Korea), and 2.266 (Seoul, northern part of South Korea), respectively; and (ii) for the efficient computation time, the time required for determining the optimal solution was only 27 seconds. The developed model can be used to easily and accurately assess the life-cycle economic and environmental performance of the rooftop PV system in the early design phase.</P>

Estimation of the Monthly Average Daily Solar Radiation using Geographic Information System and Advanced Case-Based Reasoning

Koo, Choongwan,Hong, Taehoon,Lee, Minhyun,Park, Hyo Seon American Chemical Society 2013 Environmental science & technology Vol.47 No.9

<P>The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country’s climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/esthag/2013/esthag.2013.47.issue-9/es303774a/production/images/medium/es-2012-03774a_0004.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/es303774a'>ACS Electronic Supporting Info</A></P>

A novel estimation approach for the solar radiation potential with its complex spatial pattern via machine-learning techniques

Koo, Choongwan,Li, Wenzhuo,Cha, Seung Hyun,Zhang, Shaojie Pergamon 2019 RENEWABLE ENERGY Vol.133 No.-

<P><B>Abstract</B></P> <P>As a clean and sustainable energy resource with lower environmental impact, the Chinese government encourages the application of solar energy system. The global solar radiation on the horizontal surface in the specific site should be investigated in advance so that the solar energy system could be implemented properly and efficiently. However, the monthly average daily solar radiation (MADSR) in China has complex spatial patterns, and its observation stations are still lacking due to the high cost of equipment. To address these challenges, this study aimed to develop a novel estimation approach for the MADSR with its complex spatial pattern over a vast area in China via machine-learning techniques (i.e. a clustering method (<I>k-means</I>) and an advanced case-based reasoning (A-CBR) model). The MADSR and the relevant information were collected from 97 cities in China for 10 years (from 2006 to 2015). The average prediction accuracy of the proposed approach was determined at 93.23%, showing a promising way. The proposed novel approach is expected to be generalized via the interpolation methods (e.g. <I>kriging</I> method in a geographical information system) so that decision-makers (e.g. construction manager or facility manager) can determine the appropriate location, size and form in implementing the solar energy system.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A novel estimation approach was proposed to estimate the solar radiation in China. </LI> <LI> <I>k-means</I> method was used to form the solar radiation zones with its spatial pattern. </LI> <LI> The A-CBR model was developed to estimate the monthly solar radiation by zone. </LI> <LI> The proposed approach can accurately estimate the solar radiation with references. </LI> <LI> The average prediction accuracy of the proposed approach was determined at 93.23%. </LI> </UL> </P>

Development of the smart photovoltaic system blind and its impact on net-zero energy solar buildings using technical-economic-political analyses

Koo, Choongwan,Hong, Taehoon,Jeong, Kwangbok,Ban, Cheolwoo,Oh, Jeongyoon Elsevier 2017 ENERGY Vol.124 No.-

<P><B>Abstract</B></P> <P>It is expected that the rooftop photovoltaic (PV) systems can realize net-zero energy solar buildings (nZESBs), but it is not enough by itself. To realize 100% of nZESBs, the smart photovoltaic system blind (SPSB) was proposed to generate electricity in the PV system and to reduce indoor cooling demands through the shading effect in the blind system. Before its implementation, this study aims to investigate the impact of the proposed SPSB on nZESBs, which is conducted in three ways (i.e., technical, economic, and political analyses). The detailed results can be summarized as follows: (i) technical analysis: when applying the SPSB<SUB> <I>CIGS&2-axis</I> </SUB> (which represents the SPSB with the copper-indium-gallium-selenide (CIGS) PV panel and the two-axis tracking system), its energy self-sufficiency rate was determined to be 1.25–2.31 times superior to other alternatives; (ii) economic analysis: in terms of the NPV<SUB>25</SUB> (net present value at year 25), SPSB<SUB> <I>CIGS&2-axis</I> </SUB> was determined to be 1.41–2.97 times superior to others; in terms of the SIR<SUB>25</SUB> (savings-to-investment ratio at year 25), 1.14–1.26 times; and in terms of the break-even point, 1.4–3.0 years; and (iii) political analysis: the grid-connected utilization plan including solar renewable energy certificates (GC<SUB> <I>incl.SREC</I> </SUB> plan) was determined to improve the economic profitability of the proposed SPSB.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The smart photovoltaic system blind was developed as prototype model in four ways. </LI> <LI> The SPSB<SUB> <I>CIGS&2-axis</I> </SUB> was determined to be superior to other prototype models. </LI> <LI> A holistic analysis was conducted to evaluate the impact of the SPSB on nZESBs. </LI> <LI> When implementing the GC<SUB> <I>incl.SREC</I> </SUB> plan, the economic profitability was maximized. </LI> <LI> Results showed the NPV<SUB>25</SUB> (US$2.37/m<SUP>2</SUP>), SIR<SUB>25</SUB> (2.97 times), and BEP (7.6 years). </LI> </UL> </P>

AN INTEGRATED MULTI-OBJECTIVE OPTIMIZATION MODEL FOR SOLVING THE CONSTRUCTION TIME-COST TRADE-OFF PROBLEM

Koo, Choongwan,Hong, Taehoon,Kim, Sangbum Vilnius Gediminas Technical University 2015 Journal of Civil Engineering and Management Vol.21 No.3

<P>As construction projects become larger and more diversified, various factors such as time, cost, quality, environment, and safety that need to be considered make it very difficult to make the final decision. This study was conducted to develop an integrated Multi-Objective Optimization (iMOO) model that provides the optimal solution set based on the concept of the Pareto front, through the following six steps: (1) problem statement; (2) definition of the optimization objectives; (3) establishment of the data structure; (4) standardization of the optimization objectives; (5) definition of the fitness function; and (6) introduction of the genetic algorithm. To evaluate the robustness and reliability of the proposed iMOO model, a case study on the construction time-cost trade-off problem was analyzed in terms of effectiveness and efficiency. The results of this study can be used: (1) to assess more than two optimization objectives, such as the initial investment cost, operation and maintenance cost, and CO2 emission trading cost; (2) to take advantage of the weights as the real meanings; (3) to evaluate the four types of fitness functions; and (4) to expand into other areas such as the indoor air quality, materials, and energy use.</P>

DEVELOPMENT OF THE MONTHLY AVERAGE DAILY SOLAR RADIATION MAP USING A-CBR, FEM, AND KRIGING METHOD

KOO, Choongwan,HONG, Taehoon,JEONG, Kwangbok,KIM, Jimin Vilnius Gediminas Technical University 2018 TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY Vol.24 No.2

<P>Photovoltaic (PV) system could be implemented to mitigate global warming and lack of energy. To maximize its effectiveness, the monthly average daily solar radiation (MADSR) should be accurately estimated, and then an accurate MADSR map could be developed for final decision-makers. However, there is a limitation in improving the accuracy of the MADSR map due to the lack of weather stations. This is because it is too expensive to measure the actual MADSR data using the remote sensors in all the sites where the PV system would be installed. Thus, this study aimed to develop the MADSR map with improved estimation accuracy using the advanced case-based reasoning (A-CBR), finite element method (FEM), and kriging method. This study was conducted in four steps: (i) data collection; (ii) estimation of the MADSR data in the 54 unmeasured locations using the A-CBR model; (iii) estimation of the MADSR data in the 89 unmeasured locations using the FEM model; and (iv) development of the MADSR map using the kriging method. Compared to the previous MADSR map, the proposed MADSR map was determined to be improved in terms of its estimation accuracy and classification level.</P>

Improving the prediction performance of the finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade

Koo, Choongwan,Hong, Taehoon,Oh, Jeongyoon,Choi, Jun-Ki Elsevier 2018 APPLIED ENERGY Vol.215 No.-

<P><B>Abstract</B></P> <P>As interest in the distributed generation of solar power system in a building façade continues to increase, its technical performance (i.e. the amount of electricity generation) should be carefully investigated before its implementation. In this regard, this study aimed to develop the nine-node-based finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade (FEM<SUB>9-</SUB> <I> <SUB>node</SUB> </I>), focusing on the improvement of the prediction performance. The developed model (FEM<SUB>9-</SUB> <I> <SUB>node</SUB> </I>) was proven to be superior to the four-node-based model (FEM<SUB>4-</SUB> <I> <SUB>node</SUB> </I>), which was developed in the previous study, in terms of both prediction accuracy and standard deviation. In other words, the prediction accuracy (3.55%) and standard deviation (2.93%) of the developed model (FEM<SUB>9-</SUB> <I> <SUB>node</SUB> </I>) was determined to be superior to those of the previous model (FEM<SUB>4-</SUB> <I> <SUB>node</SUB> </I>) (i.e. 4.54% and 4.39%, respectively). The practical application was carried out to enable a decision maker (e.g. construction manager, facility manager) to understand how the developed model works in a clear way. It is expected that the developed model (FEM<SUB>9-</SUB> <I> <SUB>node</SUB> </I>) can be used in the early design phase in an easy way within a short time. In addition, it could be extended to any other countries in a global environment.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Distributed generation of solar power system in a building façade was investigated. </LI> <LI> Key design variables largely affect the technical performance of the DGSP system. </LI> <LI> The prediction performance of nine-node finite element model (FEM<SUB>9-</SUB> <I> <SUB>node</SUB> </I>) increased. </LI> <LI> The mean absolute percentage error of the developed model was determined at 3.55%. </LI> <LI> Decision makers can use the developed model by simply entering project information. </LI> </UL> </P>