MODELING OF PREFERENCE IN MULTICRITERIA EVALUATION OF HEATING-VENTILATION SYSTEM OF LOW ENERGY BUILDING

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Miłosz Piotrowski
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1 Multicriteria analysis, preference modeling, system solutions, low energy buildings, Michał KLIMAS* Tomasz M. MRÓZ* MODELING OF PREFERENCE IN MULTICRITERIA EVALUATION OF HEATING-VENTILATION SYSTEM OF LOW ENERGY BUILDING The paper presents a method of modeling decision maker s preferences in multicriteria evaluation of heating and ventilation systems in low energy buildings. The basic idea of constructing low energy buildings is introduced, where quantitative and qualitative improvement of thermal enclosure and technical equipment are set to a level that it will allow to maintain the indoor climate comfort with reasonably low energy consumption. Taking into account: choice of thermal envelope, internal heat gains, building air tightness and range of high-performance HVAC systems leads it to a conclusion that each building must be treated as a complex energy system, where selection of technical equipment and construction method should be based on multicriteria decision making algorithm. This will help in identification of the set of acceptable solutions. The main goal is to recognize and describe the decision maker's preference model. To accomplish this, an example of questionnaire is presented with a description of the statistical method for processing the surveys. 1. INTRODUCTION Because of European Union s directives Poland is obliged to reduce primary energy consumption of buildings to a certain level. It is announced that until 2020 all newly formed buildings will be built at nearly zero energy standard. In June (this year) EU plans to issue guidelines for each country regarding the determination of nearly zero energy standards. To achieve this goal Poland must introduce multitude of latest technologies to the market including: construction technologies, * Politechnika Poznańska, Instytut Inżynierii Środowiska, ul. Piotrowo 3a, Poznań

evaluation of heating and ventilation systems in low energy buildings.

2 heating/ventilation/cooling systems with sun protection devices, controlling systems, etc. All above must be considered as a whole, not as usually - separately. This brings a concept of an integrated design. Choosing the best solution from among available elements must be supported by an additional tool in this case it is a method based on a multicriteria decision making algorithm. The most important criteria in a national policy is to reduce primary energy consumption and CO 2 emissions while the investors are often driven by price of the system and its popularity. Any other aspects tend to be omitted. The aim of this paper is to present tool that combine both approaches, which will help in the choice of the best possible solution among many available. 2. GENRAL ALGORITHM General algorithm of choosing the best compromise solution of the building climate control system in low energy buildings is shown in fig.1 to fig. 3. Three main steps of the algorithm are shown below: creating a data base of building technical requirements and expected operating parameters (fig.1), identification of allowable system solutions (fig. 2), choosing the most compromise solution using multicriteria analysis (fig.3). The set of features of low energy building is derived from an input data created during the design process. System identification is based on simultaneous analysis of solution availability, energy consumption and environmental harmfulness. Analyzed results must be verified by the designer s knowledge, using expert s approach [1]. After defining a set of acceptable technical solutions next step is to identify evaluation criteria to create solution array. Designing process and solution selection procedure strongly depends on chosen decision making preference model which needs to be defined in each case. Eventually multicriteria analysis is applied and in the consequence the best compromise solution is presented.

Choosing the best solution from among available elements must be supported by an additional tool in this case it is a method based on a multicriteria decision making algorithm.

3 Rys. 1. Ogólny algorytm wyboru rozwiązania kompromisowego KROK 1 Fig.1. General algorithm of choosing the best compromise solution STEP 1 Rys. 2. Ogólny algorytm wyboru rozwiązania kompromisowego KROK 2 Fig.2. General algorithm of choosing the best compromise solution STEP 2

Rys. 2. Ogólny algorytm wyboru rozwiązania kompromisowego KROK 2 Fig.

4 Rys. 3. Ogólny algorytm wyboru rozwiązania kompromisowego KROK 3 Fig.3. General algorithm of choosing the best compromise solution STEP 3 Presented algorithm takes into account an assessment of the building's energy needs in the form of final and primary energy. A set of criteria describing the decision problem is introduced to evaluate technically acceptable solutions. Tool supporting selection of a compromise solution is chosen to be one of the multicriteria method called the weighted sum method - an example have been described in [5]. 3. QUESTIONNAIRE In the multicriteria analysis the weakest link is decision makers preference model which cannot be estimated on basis of knowledge of one person or on literature data.

5 To solve this problem it is necessary to process surveys among people who are in charge in this area. To obtain reliable results from the questionnaires it is required to select proper respondents. While preparing a set of questions it is also essential to stick to some important rules (more in [2] [4]): questions must create logical sequence and must be clear and neutral, types of questions: closed (dichotomous, polytomous, ), multiple choice, open, should fit the statistical data analysis, type of scale, index, or typology to be used should be determined for each question. Next step is to conduct a survey, collect data and verify used research tool. The final move is to perform statistical analysis and decide whether the comparative study is necessary. 4. DATA PROCESSING Chosen procedure is based on one of heuristic techniques which relies on a panel of experts ([6],[7]) called the Delphi method. Prepared questionnaire is sent to the experts who answer questions in rounds. After collecting the data (in each round), an anonymous summary is prepared. To verify the differences of experts opinions a statistical analysis is carried out - distribution of opinions and their equality of variance. Correlation coefficients are calculated to know which answers are different from the average. Questionnaires which coefficients are too low are resent to the experts to verify their answers. To improve and simplify the procedure a competence factor is introduced, described in [3]. This process helps to assess the validity of answers and at the same time shortens the response time for valuable answers. To achieve this, last questions in the questionnaire are to self-estimate respondents, their experience, knowledge etc. about given problem. 5. CONCLUSIONS Presented algorithm may be a useful tool which will support the concept of integrated design of building technical equipment. Given solution will ensure a comfortable climate inside the building and at the same time, reasonably low energy consumption. However, there are few points that need to be taken into account. First is careful analysis of availability of technical solutions and validation of its suitability to achieve mentioned purpose. Second is calibration of the method by questionnaires a selected

closed (dichotomous, polytomous, ), multiple choice, open, should fit the statistical data analysis, type of scale, index, or typology to be used should be determined for each question.

6 group of people - decision makers and to appoint their preference model. The final and equally important aspect is a continuous education of people (by experts) at every level of decision-making process. First of all to improve the accuracy of the method and second, to introduce latest technologies to the market. LITERATURE [1] FLOURENTZOU F., ROULET C.A.: Elaboration of retrofit scenarios, Energy and Buildings, 34/2002, p [2] FODDY W., Constructing questions for interviews and questionnaires. Cambridge University Press, [3] KANDORA L., Procedura wyodrębniania i oceny czynników mających znaczenie dla rozwoju wykorzystania odnawialnych źródeł energii w Polsce. Polityka Energetyczna, 2007, Tom 10 Zeszyt 1, p [4] KĘDZIOR Z., KARCZ K., Badania marketingowe w praktyce. PWE, Warszawa 2007 [5] KLIMAS M., MRÓZ T., Wielokryterialna analiza wyboru systemu ogrzewczowentylacyjnego budynku pasywnego. INSTAL 2011/3. [6] LINSTONE H.A, TUROFF M., The Delphi Method. Techniques and Applications. Addison-Wesley Publishing Co. Inc [7] ROGALSKA M., Prognozowanie metodą delficką metoda oceny prawidłowości prognoz. Zeszyty Naukowe WSOWL, Nr 3 (157) STRESZCZENIE MODELOWANIE PREFERENCJI W WIELOKRYTERIALNEJ OCENIE SYSTEM OGRZEWCZO-WENTYLACYJNEGO BUDYNKU O NISKIM ZUŻYCIU ENERGII. W artykule przedstawiono metodę modelowania preferencji decydenta w wielokryterialnej ocenie systemu ogrzewczo-wentylacyjnego budynku o niskim zużyciu energii. Podstawową zasadą konstruowania budynków niskoenergetycznych jest jakościowe oraz ilościowe polepszanie obudowy termicznej budynku oraz systemów wyposażenia do poziomu, przy którym jest możliwe jest jednoczesne utrzymanie komfortu termicznego oraz niskiego zużycia energii. Biorąc pod uwagę: parametry termiczne budynku, wewnętrzne zyski ciepła, szczelność budynku oraz szeroki wybór systemów HVAC budynek musi być oceniany całościowo. Wybór technicznego wyposażenia oraz sposób konstruowania budynku powinien opierać się na wielokryterialnym algorytmie, który wskaże zbiór dopuszczalnych i możliwych wariantów rozwiązań. Głównym celem jest wyznaczenie oraz opisanie modelu preferencji decydenta. W tym celu, aby dokonać ankietyzacji, przedstawiono zasady tworzenia kwestionariusza wraz z opisem statystycznej obróbki danych.

First of all to improve the accuracy of the method and second, to introduce latest technologies to the market. LITERATURE [1] FLOURENTZOU F., ROULET C.A.: Elaboration of retrofit scenarios, Energy and Buildings, 34/2002, p.

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