engleski

Improvement of smart city energy efficiency planning by including uncertainties: developing methodology for characterization and quantification uncertainties

The smart city represents a big potential for sustainable development and growth of economy including improved quality of citizens' life. Application of new and efficient solutions in the smart city includes lots of risks because it involves many sources of uncertainties. Characterization and assessment of the uncertainty of variables in planning methodology seem necessary in order to quantify results uncertainties and to better present the probability of favorable realization outcome for a smart city project. This work is describing developing methodology to quantify uncertainty for selected conventional planning methodology for smart city development, focusing on the economic analysis for the selected segments, e.g.: smart grid development, smart electric transportation solutions. The main focus is to create a method for systematic characterization of parameters uncertainties in order to identify most critical for model results uncertainty. Uncertainty of the variables depends on its nature but in general, is consisted of stochastic (random, aleatory, not reducible) and knowledge (epistemic, reducible with improved understanding) parts. Both uncertainties could be expressed as some range of values or with defined probability distribution (uniform, normal, triangle, etc.). Some knowledge related uncertainties could be presented as parameters or scenarios (e.g., the share of the capital, the optimistic or pessimistic outcome for usability etc.). This means that uncertainty has to be characterized for example for the cost of technical components, cost of implementation, dynamic of implementation (e.g., duration of realization), realization of the planned effects (e.g., functionality, efficiency) and acceptances of use of realized smart solutions (e.g., willingness of citizens to engage, ergonomics and flexibility for different use cases). Determined uncertainties present input for further analysis with potential that results determine the importance measures of some variables and their impact on the favorable outcome of smart city realization. The developed methodology will be applied in the future on the development of energy-efficient solutions of the city of Ludbreg, for example on the development of smart grid and electricity- related part of smart solutions in transportations. This would allow for better planning and optimization of the smart city realization. In order to include uncertainty in smart city planning, it is important first to characterize related uncertainties.

smart city, characterization of parameters uncertainty, smart grid, smart metering, CBA methodology, Monte Carlo simulation

nije evidentirano