Social Acceptance Optimization of Biomass Plants: a Fuzzy Cognitive Map and Evolutionary Algorithm Application

Abstract

Implementation of biomass plants is often thwarted by public opposition, despite potential technical- economic and normative feasibility. This opposition is generally known as NIMBY effect. One of the most adopted political action able to overcome or to control NIMBY effect is the information of population about ex-ante and ex-post characteristics of the intervention. However, the informative approach is a complex task to achieve. In this process, several ecological, social, normative and economic variables must be properly considered in a unique framework. Moreover, the selection of variables on which concentrate information and the time consumption of knowledge transfer, seem to be additional issues to solve. Thus, the aim of the research is to implement and verify an innovative procedure to assess and minimize the potential NIMBY effect in case of planning of biomass facilities. From the methodological point of view, this study combines Fuzzy Cognitive Map (FCM) procedure and nonlinear modelling solved by the Social Cognitive Optimisation (SCO) evolutionary algorithm. This work focuses on the perception of experts in bioenergy sector about Combined Heat and Power (CHP) plant. The proposed methodology is developed for a theoretical case study in Tuscany (central Italy).