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A MULTICRITERIA ANALYSIS OF ENERGY SUPPLY OPTIONS FOR MUNICIPAL AND RESIDENTIAL CUSTOMERS

Rzeszow University of Technology Faculty of Electrical and Computer Engineering, Poland. A MULTICRITERIA ANALYSIS OF ENERGY SUPPLY OPTIONS FOR MUNICIPAL AND RESIDENTIAL CUSTOMERS. Tadeusz Bewszko.

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A MULTICRITERIA ANALYSIS OF ENERGY SUPPLY OPTIONS FOR MUNICIPAL AND RESIDENTIAL CUSTOMERS

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  1. Rzeszow University of TechnologyFaculty of Electrical and Computer Engineering, Poland A MULTICRITERIA ANALYSIS OF ENERGY SUPPLY OPTIONS FOR MUNICIPAL AND RESIDENTIAL CUSTOMERS Tadeusz Bewszko ________________________________________________________________________The 20th Workshop on Complex Systems Modeling, IIASA, August 28-30, 2006.

  2. CONTENTS: • Energy planning as a multicriteria problem. • Literature review of application of multi-criteria methods to energy supply of residential customers. • 3. Problem formulation. • New method of selecting energy supplying option for residential customers. • Application of new method to real life problems. • 6. Results, future work.

  3. Investment cost Total operation cost LCC Cost Emission of CO2 Emission of SO2 Emission of NOX Comfort of use Efficiency Used resources ENERGY PLANNING AS A MULTICRITERIA PROBLEM: Coal Biomass Gas LPG Oil District heat Heat pump Electricity Electricity (night)

  4. LITERATURE REVIEW OF APPLICATION OF MULTICRITERIA METHODS TO ENERGY SUPPLY OF RESIDENTIAL CUSTOMERS:

  5. CONCLUSIONS AFTER LITERATURE REVIEW: • Modern, friendly for DM, interactive multi-objective decision making methods have not been used so far to solve decision-making problem of selecting optimal energy supplying option for municipal and residential customers. ·All energy demands for residential customers have not been taken into account.

  6. PROBLEM FORMULATION: Examination of possibility of application and effectiveness of interactive multi-objective decision making methods to solve decision-making problem of selecting optimal energy supplying option for municipal and residential customers. AIM OF WORK: -to build mathematical model of decision problem of selecting optimal energy supplying option for municipal and residential customers, - to make multicriteria analyses with different sets of decision criteria by using existing software implementation of interactive multiobjective decision making method

  7. CHOOSING INTERACTIVE MULTI-OBJECTIVE DECISION MAKING METHOD • There exist a lot of interactive multi-objective decision making methods • A few of existing software implementation of interactive multi-objective decision making methods

  8. CHOOSING INTERACTIVE MULTI-OBJECTIVE DECISION MAKING METHOD

  9. METHOD OF SELECTING ENERGY SUPPLYING OPTION FOR MUNICIPAL AND RESIDENTIAL CUSTOMERS 1. Building a multicriteria model of decision problem of supplying energy to a selected customer. 2. Making multicriteria analyses with different sets of decision criteria. 3. The use of a scenario analysis for supporting decision–making process which involves uncertainty.

  10. DETERMINISTIC MOILP MODEL OF DECISION PROBLEM MULTICRITERIA MODELLING OF DECISION PROBLEM OF SUPPLYING ENERGY TO RESIDENTIAL CUSTOMERS: Verification of the model Define outcome variables Define constrains Define decision variables Specification of: -set of energy demands of customer- set of available energy carriers - set of energy conversion technologies

  11. TYPES OF USERS AND ANALYSES: • Economical customer: economical and comfort criteria • Environmentally friendly customer: economical, ecological, and comfort criteria • Policy maker:economical, ecological, and energy safety criteria

  12. A SCENARIO ANALYSIS FOR SUPPORTING DECISION–MAKING PROBLEM WHICH INVOLVES UNCERTAINTY: • Uncertainty - possibility changes of parameters of the mathematical model (prices of energy carriers, energy demands). • A SCENARIO ANALYSIS – one of the methods of coping with uncertainty. • A scenario analysis includes: • an evaluation of scenarios of changes in future of values of some model parameters, • examination of changes of values of some outcome variables for some solutions taken from multi-criteria analyses.

  13. APPLICATION OF THE METHOD TO REAL LIFE PROBLEMS: • Selecting energy supplying option for: • a single family house (two users: B1, B2), • a flat in multifamily block (two users: M1, M2). • For each decision making problem: • multicriteria model of problem has been built • and used for multicriteria analyses • and scenario analysis.

  14. Design officeAGROBISP Type WB-3344 SELECTING ENERGY SUPPLYING OPTION FOR SINGLE FAMILY HOUSE: • Two single family houses (user B1, B2), • Both buildings take advantage of all available technical solutions to minimize thermal losses, • Number of inhabitants are known, • Energy demands were taken from statistical data, • Investments costs and prices of energy carriers were taken from Rzeszow area.

  15. MODEL DESCRIPTIONS: • Decision variables: xij - energy supplied by the i-th carrier j-th demand

  16. OUTCOMEVARIABLES: • INV - The Investment Cost of a Whole System, [PLN] • OMC – The Total Annual Operation and Maintenance Cost, [PLN] • TAC – The Total Annual Cost of Using Energy System, [PLN] • LCC – The Life Cycle Cost, [PLN] • TotEmk– The Total Emission of Different Pollutants, [kg]; k  POL = {CO2, SO2, NO2, PM} • Inv_TotSysEff – The Total System Efficiency, [-] • TotRes – The Total Amount of Used Resources, [GJ] • ImpRes – The Total Amount of Imported Resources, [GJ] • ComUse – Comfort of Use, [-]

  17. VARIOUS TYPES OF USERS AND ANALYSES: Four types of analyses were carried out: • Analysis A: economical criteria (INV, OMC, TAC)andcomfort criterion (ComUse), • Analysis B: economical criterion (LCC)andcomfort criterion (ComUse), • Analysis C: economical criteria (INV, OMC), comfort criterion (ComUse)andecological criteria (TotEmCO2,TotEmSO2, TotEmPM), • Analysis D: economical criteria (INV, OMC), comfort criterion (ComUse), ecological criteria (TotEmCO2, TotEmSO2)andenergy safety criterion (ImpRes).

  18. RESULTS OF MULTICRITERIA ANALYSIS (1): Table 1. Results of analysis A

  19. RESULTS OF MULTICRITERIA ANALYSIS (2): Table 2. Results of analysis D

  20. Scenarios of prices of energy carriers: • Base • Pessimistic • Optimistic • Gas crisis • Oil crisis • Cheap elect. Scenarios of energy demand: • Long winter, number of inhabitants increases • Normal winter, number of inhabitants increases • Normal winter, fixed number of inhabitants • Warm winter, fixed number of inhabitants THE USE OF SCENARIO ANALYSIS: Two parameters of the mathematical model could change in 15 years’ time: YeEnDe– total energy demand CEi– cost of 1 GJ of i-th energy carrier

  21. Base Pessimistic Optimistic Gas crisis Oil crisis Cheap elect. RESULTS OF SCENARIO ANALYSIS: Fig. 2. Trajectory of values of outcome variable OMC for B1 user for decision: [gas, gas, gas, elect.]

  22. Base Pessimistic Optimistic Gas crisis Oil crisis Cheap elect. RESULTS OF SCENARIO ANALYSIS: Fig. 3. Cost LCC for B1 user for decision: [gas, gas, gas, elect.]

  23. CONCLUSIONS: ·Interactive multi-objective decision making methods could be effectively used to solve decision-making problem of selecting energy supplying option for municipal and residential customers. ·Decision-making process is friendly for DM. ·Problem of selecting energy supplying option for municipal and residential customers is a part of much broader subject: local energy planning.

  24. FUTURE: ·Multicriteria modelling and analyses of many heterogeneous energy users ·Planning energy supply for municipal systems. ·Regional energy planning: - heterogeneity (across temporal and spatial scales) energy users - uncertainty (price of energy carriers and energy demands) - apply new technologies - apply locally available renewable energy resources - model based decision support systems.

  25. MULTI CRITERIA MODEL ANALYSIS: • Various trade-offs criteria • Analysis of various Pareto solutions

  26. VARIOUS TYPES OF ANALYSES: • economical and comfort • economical, ecological, and comfort • economical, ecological, and energy safety

  27. Użyt- kownik MODELOWANIE MATEMATYCZNE ZASILANIA W ENERGIĘ BUDYNKU MIESZKALNEGO JEDNORODZINNEGO: P(x,y) Model matematyczny y = f (x,z) y z gdzie: • x Rnoznacza wektor zmiennych decyzyjnych, • y Rmoznacza wektor rezultatów decyzji (zmiennych wyjściowych), • zwektor parametrów (decyzji zewnętrznych), • P(x,y) preferencje decydenta.

  28. OGÓLNY SCHEMAT INTERAKTYWNEJ WIELOKRYTERIALNEJ METODY ANALIZY MODELU SYTUACJI DECYZYJNEJ : Wybór kryteriów oraz określenie ich typów Określenie preferencji decydenta (poziomy aspiracji i rezerwacji) Znalezienie rozwiązania Pareto optymalnego problemu wielokryterialnego Ocena otrzymanego rozwiązania Pareto optymalnego N T Czy dalejanalizujemy model? Wybór rozwiązania satysfakcjonującego N T Czy zmianazbioru kryteriów? STOP START

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