Fuzzy logic is aptly suited to decisions where there is an element of imprecision or uncertainty, such as risk management. However, its application to Project Risk Management (PRM) has been limited to academic research with other research confirming that practitioners rarely adopt fuzzy theory. This chapter demonstrates the application of fuzzy theory to project risk management with the use of a notional bioenergy case study.

In conjunction with the European Union (EU) targets, the United Kingdom (UK) Government has introduced a range of mechanisms to foster the development and deployment of low carbon energy technologies and markets. This study focuses on the three main financial incentive schemes to promote renewable energy sector in the UK for electricity, heat and fuel production from renewables, namely feed-in tariff (FiT), Renewable Heat Incentive (RHI) and Renewables Obligation Certificate (RoC), considering the fact that optimal policy design depends on effective analyses of the impacts of incentives on the performance of renewable energy systems. The effects of potential changes in these incentive schemes on the economic and environmental performance of bioenergy sector are investigated using an analytical methodology. The methodology integrates fuzzy decision making and multi objective mathematical modelling in the same framework to capture uncertainties in the system parameters as well as economic and environmental sustainability aspects. Computational experiments are performed on bioenergy production using the entire West Midlands Region in the UK as case study region. The results reveal that the changes in incentive policies have a significant impact on the profitability of the supply chain, whereas environmental performance of the supply chain in terms of total GHG emissions is the least affected performance indicator by the changes in the incentive policies.

The design of waste to bioenergy supply chains (W-BESC) is critically important for meeting the circular economy (CE) goals, whilst also ensuring environmental sustainability in the planning and operation of energy systems. This study develops a novel optimization methodology to aid sustainable design and planning of W-BESC that comprise multiple technologies as well as multiple product and feedstock types. The methodology identifies the optimum supply chain configuration and plans the logistics operations in a given region to meet the energy demand of specified nodes. A scenario based fuzzy multi objective modelling approach is proposed and utilized to capture the economic and environmental sustainability aspects in the same framework. We test the proposed model using the entire West Midlands (WM) region from the United Kingdom (UK) as a case study. In this scope, a comprehensive regional supply chain is designed to meet the energy and biofertilizer demand of specific nodes considering available waste and crop type biomass in the region. Further analysis is conducted to reveal the impacts of main economic and technological parameters on the supply chain performance indicators.

Developing and employing effective design methodologies can significantly improve the economic and environmental viability of renewable production processes. This study contributes by presenting a novel bi-level decision support system (DSS) to aid modelling and optimization of multi technology, multi product supply chains and co-modal transportation networks for biomass based (bio-based) production combining two multi-objective mathematical models. Considering the supply chain configuration optimized by the first level of the DSS, in the second level, the transportation network is designed specifying the most appropriate transportation mode and related transportation option under transfer station availability limitations. A hybrid solution methodology that integrates fuzzy set theory and ε-constraint method is proposed. This methodology handles the system specific uncertainties addressing the economic and environmental sustainability aspects by capturing trade-offs between conflicting objectives in the same framework. To explore the viability of the proposed models and solution methodology, a regional supply chain and transportation network is designed using the entire West Midlands (WM) region of the UK as a testing ground. Additionally, scenario and sensitivity analyses are conducted to provide further insights into design and optimization of the biomass based supply chains.

Combined heat and power from the intermediate pyrolysis of biomass materials offers flexible, on demand renewable energy with some significant advantages over other renewable routes. To maximise the deployment of this technology an understanding of the dynamics and sensitivities of such a system is required. In the present work the system performance, economics and life-cycle environmental impact is analysed with the aid of the process simulation software Aspen Plus. Under the base conditions for the UK, such schemes are not currently economically Competitive with energy and char products produced from conventional means. However, under certain scenarios as modelled using a sensitivity analysis this technology can compete and can therefore potentially contribute to the energy and resource sustainability of the economy, particularly in on-site applications with low-value waste feed-stocks. The major areas for potential performance improvement are in reactor cost reductions, the reliable use of waste feedstocks and a high value end use for the char by-product from pyrolysis. (C) 2017 Elsevier Ltd. All rights reserved.

Purpose– This paper aims to address the following challenge: the push to widen participation in public consultation suggests social media as an additional mechanism through which to engage the public. Bioenergy companies need to build their capacity to communicate in these new media and to monitor the attitudes of the public and opposition organizations towards energy development projects.Design/methodology/approach– This short paper outlines the planning issues bioenergy developments face and the main methods of communication used in the public consultation process in the UK. The potential role of social media in communication with stakeholders is identified. The capacity of sentiment analysis to mine opinions from social media is summarised and illustrated using a sample of tweets containing the term “bioenergy”.Findings– Social media have the potential to improve information flows between stakeholders and developers. Sentiment analysis is a viable methodology, which bioenergy companies should be using to measure public opinion in the consultation process. Preliminary analysis shows promising results.Research limitations/implications– Analysis is preliminary and based on a small dataset. It is intended only to illustrate the potential of sentiment analysis and not to draw general conclusions about the bioenergy sector.Social implications– Social media have the potential to open access to the consultation process and help bioenergy companies to make use of waste for energy developments.Originality/value– Opinion mining, though established in marketing and political analysis, is not yet systematically applied as a planning consultation tool. This is a missed opportunity.

bCHP (Biomass combined heat and power) systems are highly efficient at smaller-scales when a significant proportion of the heat produced can be effectively utilised for hot water, space heating or industrial heating purposes. However, there are many barriers to project development and this has greatly inhibited deployment in the UK Project viability is highly subjective to changes in policy, regulation, the finance market and the low cost fossil fuel incumbent. The paper reviews the barriers to small-scale bCHP project development in the UK along with a case study of a failed 1.5 MWel bCHP scheme. The paper offers possible explanations for the project's failure and suggests adaptations to improve the project resilience. Analysis of the project's: capital structuring; contract length and bankability; feedstock type and price uncertainty, and; plant oversizing highlight the negative impact of the existing project barriers on project development. The research paper concludes with a discussion on the effects of these barriers on the case study project and this industry more generally. A greater understanding of the techno-economic effects of some barriers for small-scale bCHP schemes is demonstrated within this paper, along with some methods for improving the attractiveness and resilience of projects of this kind. (C) 2014 Elsevier Ltd. All rights reserved.

Renewable energy project development is highly complex and success is by no means guaranteed. Decisions are often made with approximate or uncertain information yet the current methods employed by decision-makers do not necessarily accommodate this. Levelised energy costs (LEC) are one such commonly applied measure utilised within the energy industry to assess the viability of potential projects and inform policy. The research proposes a method for achieving this by enhancing the traditional discounting LEC measure with fuzzy set theory. Furthermore, the research develops the fuzzy LEC (F-LEC) methodology to incorporate the cost of financing a project from debt and equity sources. Applied to an example bioenergy project, the research demonstrates the benefit of incorporating fuzziness for project viability, optimal capital structure and key variable sensitivity analysis decision-making. The proposed method contributes by incorporating uncertain and approximate information to the widely utilised LEC measure and by being applicable to a wide range of energy project viability decisions.

The purpose of this research is to explore the disparity between the existing model-orientated bioenergy decision support system (DSS) functions and what is desired by practitioners, in particular bioenergy project developers.This research has compiled the published bioenergy project development models, to highlight the characteristics emphasised by academics.When contrasted against a UK practitioner's perspective through the administration of a Likert style questionnaire, it is clear that the general DSS issues still persist.Finally, the research suggests how this 'theory-practice' divide could be addressed.The research contributes by giving a unique insight into the demands of a practitioner, but is currently limited by a small sample size.