Locating a bioenergy facility using a hybrid optimization method

In this paper, the optimum location of a bioenergy generation facility for district energy applications is sought. A bioenergy facility usually belongs to a wider system, therefore a holistic approach is adopted to define the location that optimizes the system-wide operational and investment costs. A hybrid optimization method is employed to overcome the limitations posed by the complexity of the optimization problem. The efficiency of the hybrid method is compared to a stochastic (genetic algorithms) and an exact optimization method (Sequential Quadratic Programming). The results confirm that the hybrid optimization method proposed is the most efficient for the specific problem. (C) 2009 Elsevier B.V. All rights reserved

Investment planning in electricity production under CO2 price uncertainty

The scope of this work is to investigate the effect that various scenarios for emission allowance price evolution may have on the future electricity generation mix of Greece. The renewable energy generation targets are taken into consideration as a constraint of the system, and the learning rates of the various technologies are included in the calculations. The national electricity generation system is modelled for long-term analysis and an optimisation method is applied, to determine the optimal generating mix that minimises electricity generation cost, while satisfying the system constraints and incorporating the uncertainty of emission allowance prices. In addition, an investigation is made to identify if a point should be expected when renewable energy will be more cost-effective than conventional fuel electricity generation. The work is interesting for investment planning in the electricity market, as it may provide directions on which technologies are most probable to dominate the market in the future, and therefore are of interest to be included in the future power portfolios of related investors. (C) 2010 Elsevier B.V. All rights reserved

Quantitative risk analysis for road tunnels complying with EU regulations

Tunnels have improved the connection of regions within the European Commission (EC) and have been used lately as a catalyst for economic development of previously isolated regions. However, the increasing number of these important infrastructures is raising upfront an endogenous problem, which is the severity of accidents that may occur. These risks have much greater impact when heavy goods vehicles (HGVs) or dangerous goods (DGs) are involved in the accident. As a result, the EC launched the EC Directive 2004/54/EC. In order to achieve a minimum acceptable level of safety, the EC Directive 2004/54/EC suggests, apart from the measures imposed based on tunnel characteristics, the implementation of a risk analysis in cases such as the opening of the road tunnel to DGs. The most widely accepted method for such quantitative risk analysis (QRA) is the OECD/PIARC QRA Model. This research exploits the QRA Model to perform a QRA for five illustrative cases in order to explore the sufficiency of the minimum tunnel safety measures imposed by the Directive when transportation of HGVs and DGs is allowed through the tunnel. The research concludes that, at least for tunnels with marginal values of the EC Directive classes for length and traffic, the risk exposure (F/N curves) lays over the acceptable safety limits of ALARP (as low as reasonably practicable) models. Thus, the manager of the tunnel should take seriously into account the provision of the Directive for further risk analysis and consider more safety measures as well as take into account the risk associated with the alternative routes

Optimisation of electricity energy markets and assessment of CO2 trading on their structure : a stochastic analysis of the greek power sector

Power production was traditionally dominated by monopolies. After a long period of research and organisational advances in international level, electricity markets have been deregulated allowing customers to choose their provider and new producers to compete the former Public Power Companies. Vast changes have been made in the European legal framework but still, the experience gathered is not sufficient to derive safe conclusions regarding the efficiency and reliability of deregulation. Furthermore, emissions' trading progressively becomes a reality in many respects, compliance with Kyoto protocol's targets is a necessity, and stability of the national grid's operation is a constraint of vital importance. Consequently, the production of electricity should not rely solely in conventional energy sources neither in renewable ones but on a mixed structure. Finding this optimal mix is the primary objective of the study. A computational tool has been created, that simulates and optimises the future electricity generation structure based on existing as well as on emerging technologies. The results focus on the Greek Power Sector and indicate a gradual decreasing of anticipated CO2 emissions while the socioeconomic constraints and reliability requirements of the system are met. Policy interventions are pointed out based on the numerical results of the model. (C) 2010 Elsevier Ltd. All rights reserved