Multi-criteria evaluation of hydrogen and natural gas fuelled power plant technologies

This paper evaluates nine types of electrical energy generation options with regard to seven criteria. The options use natural gas or hydrogen as a fuel. The Analytic Hierarchy Process was used to perform the evaluation, which allows decision-making when single or multiple criteria are considered. The options that were evaluated are the hydrogen combustion turbine, the hydrogen internal combustion engine, the hydrogen fuelled phosphoric acid fuel cell, the hydrogen fuelled solid oxide fuel cell, the natural gas fuelled phosphoric acid fuel cell, the natural gas fuelled solid oxide fuel cell, the natural gas turbine, the natural gas combined cycle and the natural gas internal combustion engine. The criteria used for the evaluation are CO2 emissions, NOX emissions, efficiency, capital cost, operation and maintenance costs, service life and produced electricity cost. A total of 19 scenarios were studied. In 15 of these scenarios, the hydrogen turbine ranked first and proved to be the most preferred electricity production technology. However since the hydrogen combustion turbine is still under research, the most preferred power generation technology which is available nowadays proved to be the natural gas combined cycle which ranked first in five scenarios and second in eight. The last in ranking electricity production technology proved to be the natural gas fuelled phosphoric acid fuel cell, which ranked in the last position in 13 scenarios

Finding the optimal combination of power plants alternatives: a multi response Taguchi-neural network using TOPSIS and fuzzy best-worst method

With increasing growth of electricity consumption in developed and developing countries, the necessity of constructing and developing of power plants is inevitable. There are two main resources for electricity generation includes fossil and renewable energies which have some different characteristics such as manufacturing technology, environmental issues, accessibility and etc. In developing plans, it is important to consider and address the policy makers’ indicators such as environmental, social, economic and technical criteria. In this paper, an integrated multi response Taguchi-neural network-fuzzy best-worst method (FBWM) -TOPSIS approach is applied to find an optimal level of five different power plants including: gas, steam, combined cycle, wind and hydroelectric. Taguchi method is used to design combinations and calculate some of the signal to noise (S/N) ratios. Then, neural network is applied to estimate the rest of S/N ratios. Finally, FBWM and TOPSIS methods are used for weighing sub-indicators and selecting the best combination, respectively. To illustrate the usefulness of the proposed approach, a case study on the development of power plants in Iran is considered and the results are discussed. According to the results, in general, small size power plants for fossil resources are preferable. In contrast, medium and larger size power plants for renewable resources are preferable

Decision support systems for power plants

The thesis aimed at the development and presentation of the decision support systems for the multicritena evaluation of the ten most important power plant types. There was provision for all appropriate information in the right form so that the decision maker can select the best power plant type in every specific decision context. An original hierarchy tree structure comprising of 27 criteria and subcriteria was developed while the ten types of power plant were evaluated by use of three of the most important multicritena methods (ΑΗΡ PROMETHEE ELECTRE) with different qualitative specifications. An existing software was used for the ΑΗΡ while new software in Visual Basic was developed for PROMETHEE and ELECTRE. Eight scenarios were analyzed (the reference scenario along with seven scenarios of sensitivity analysis) which cover the whole range of possible values for criteria weights. There is no ideal power plant type. An increase in the weight of the criterion of the living standard leads to better evaluation of power plants based on renewable energy except for hydros while nuclear and fossil fuel power plants have worse evaluations except for natural gas turbine power plants. The opposite results apply for the criterion of the technological factors. An increase in the weight of the criterion of the economic factors leads wind nuclear and combined cycle power plants using natural gas in the first three rankings respectively.Η διατριβή είχε ως στόχο την ανάπτυξη και παρουσίαση των συστημάτων υποστήριξης αποφάσεων για την πολυκριτηριακή αξιολόγηση των δέκα σημαντικότερων τύπων ηλεκτροπαραγωγικών μονάδων και την παροχή στον λήπτη αποφάσεων όλων των πληροφοριών στην κατάλληλη μορφή για την επιλογή της βέλτιστης ηλεκτροπαραγωγικής μονάδας στις εκάστοτε επικρατούσες συνθήκες. Αναπτύχθηκε πρωτότυπη δενδρική ιεραρχική δομή 27 κριτηρίων και υποκριτηρίων και χρησιμοποιήθηκαν τρεις από τις σημαντικότερες πολυκριτηριακές μεθόδους (ΑΗΡ PROMETHEE ELECTRE) με διαφορετικά ποιοτικά χαρακτηριστικά. Χρησιμοποιήθηκε υπάρχον λογισμικό για την ΑΗΡ και αναπτύχθηκε νέο λογισμικό σε Visual Basic για την PROMETHEE και την ELECTRE. Αναλύθηκαν οκτώ σενάρια (το σενάριο αναφοράς και τα επτά εναλλακτικά σενάρια της ανάλυσης ευαισθησίας) που καλύπτουν όλο το εύρος διακύμανσης της βαρύτητας των κριτηρίων. Ιδανικός τύπος ηλεκτροπαραγωγικής μονάδας δεν υπάρχει. Αύξηση της βαρύτητας του βιοτικού επίπεδου ευνοεί τις μονάδες ανανεώσιμων πηγών ενέργειας με εξαίρεση τις υδροηλεκτρικές και μειώνει την αξιολόγηση των πυρηνικών και των μονάδων ορυκτών καυσίμων με εξαίρεση τις μονάδες αεριοστροβίλου με καύσιμο φυσικό αέριο. Αντίθετα είναι τα αποτελέσματα για τους τεχνολογικούς παράγοντες. Αύξηση της βαρύτητας των οικονομικών παραγόντων έχει σαν αποτέλεσμα την κατάταξη των αιολικών των πυρηνικών και των μονάδων συνδυασμένου κύκλου με καύσιμο φυσικό αέριο στις τρεις πρώτες θέσεις αντίστοιχα

Sensitivity analysis of technological, economic and sustainability evaluation of power plants using the analytic hierarchy process

Technological, economic and sustainability evaluation of power plants by use of the analytic hierarchy process and nine end node criteria for a reference scenario based on subjective criteria weighting has been presented in a previous paper by authors. However, criteria weight variations may substantially modify overall evaluations and rankings of power plants. The current paper presents a sensitivity analysis with four alternative scenarios (sets of criteria weights) compared with the reference scenario. The results show that priority to "technology and sustainability" favors renewable energy power plants, while priority to "economic" criteria favors mainly nuclear power plants and less the four types of fossil fuel power plant.Sensitivity analysis Power plant evaluation Analytic hierarchy process

Multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process

The purpose of this study is to evaluate 10 types of power plants available at present including fossil fuel, nuclear as well as renewable-energy-based power plants, with regard to their overall impact on the living standard of local communities. Both positive and negative impacts of power plant operation are considered using the analytic hierarchy process (AHP). The current study covers the set of criteria weights considered typical for many local communities in many developed countries. The results presented here are illustrative only and user-defined weighting is required to make this study valuable for a specific group of users. A sensitivity analysis examines the most important weight variations, thus giving an overall view of the problem evaluation to every decision maker. Regardless of criteria weight variations, the five types of renewable energy power plant rank in the first five positions. Nuclear plants are in the sixth position when priority is given to quality of life and last when socioeconomic aspects are valued more important. Natural gas, oil and coal/lignite power plants rank between sixth and tenth position having slightly better ranking under priority to socioeconomic aspects.