Incorporating life cycle external cost in optimization of the electricity generation mix

The present work aims to examine the strategic decision of future electricity generation mix considering, together with all other factors, the effect of the external cost associated with the available power generation technology options, not only during their operation but also during their whole life cycle. The analysis has been performed by integrating the Life Cycle Assessment concept into a linear programming model for the yearly decisions on which option should be used to minimize the electricity generation cost. The model has been applied for the case of Greece for the years 2012-2050 and has led to several interesting results. Firstly, most of the new generating capacity should be renewable (mostly biomass and wind), while natural gas is usually the only conventional fuel technology chosen. If externalities are considered, wind energy increases its share and hydro-power replaces significant amounts of biomass-generated energy. Furthermore, a sensitivity analysis has been performed. One of the most important findings is that natural gas increases its contribution when externalities are increased. Summing-up, external cost has been found to be a significant percentage of the total electricity generation cost for some energy sources, therefore significantly changing the ranking order of cost-competitiveness for the energy sources examined

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

An optimization model for multi-biomass tri-generation energy supply

In this paper, a decision support system (DSS) for multi-biomass energy conversion applications is presented. The system in question aims at supporting an investor by thoroughly assessing an investment in locally existing multi-biomass exploitation for tri-generation applications (electricity, heating and cooling), in a given area. The approach followed combines use of holistic modelling of the system, including the multi-biomass supply chain, the energy conversion facility and the district heating and cooling network, with optimization of the major investment-related variables to maximize the financial yield of the investment. The consideration of multi-biomass supply chain presents significant potential for cost reduction, by allowing spreading of capital costs and reducing warehousing requirements, especially when seasonal biomass types are concerned. The investment variables concern the location of the bioenergy exploitation facility and its sizing, as well as the types of biomass to be procured, the respective quantities and the maximum collection distance for each type. A hybrid optimization method is employed to overcome the inherent limitations of every single method. The system is demand-driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of an investor to assess and optimize in financial terms an investment aiming at covering real energy demand. optimization is performed taking into account various technical, regulatory, social and logical constraints. The model characteristics and advantages are highlighted through a case study applied to a municipality of Thessaly, Greece. (C) 2008 Elsevier Ltd. 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

Improving safety in Greek road tunnels

Tunnels are regarded as one of the most important infrastructures in Europe, as they may improve the connection of regions and aid economic development through facilitating the transportation of people and goods. In order to achieve a minimum acceptable level of safety, the EC issued Directive 2004/54/EC, which describes specific safety measures that have to be taken for all road tunnels in the trans-European road network. In parallel, there are several qualitative or quantitative methods for measuring road tunnel safety, while the method that seems to be the most accepted by administrative authorities for quantitative risk analysis is the OECD/PIARC QRA Model (QRAM), which has been developed by INERIS, WS-Atkins and the Institute for Risk Research. QRAM is based on engineering software that aids quantitatively assessment of the societal risk due to transporting goods and dangerous goods with Heavy Goods Vehicles (HGV) through road tunnels. The aim of this paper is to expose the effectiveness of the measures imposed by the EC in Greek road tunnels. A typical road tunnel, as designed and implemented after Directive 2004/54/EC, is compared to the same tunnel as if it was developed before the Directive was put into action. The comparison is made on the basis of the societal risk existing in the two cases. The conclusion of the paper, based on the outcome of the risk analysis with the QRAM method, is that the safety of Greek Tunnels is significantly improved due to the implementation of the measures imposed by the EC Directive 2004/54/EC

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

Comparative techno-economic analysis of ORC and gasification for bioenergy applications

The use of biomass for decentralized energy production has undergone a significant development the last years. The fact that this fuel is CO(2)-free provides many advantages in European and world aims for sustainable energy sources. Biomass trigeneration is a relatively new concept, which has the potential to improve the bioenergy economics for areas with warm climate, for which traditional biomass cogeneration was unfeasible. This concept can be applied with various energy conversion technologies, two of which are investigated in this paper: ORC and gasification. Both technologies are applied for a specific case study. The technological and financial comparison of the two technologies shows that gasification offers improved yield for the investment, mainly due to the higher electrical efficiency factor. However, attention should be placed to the increased investment risk of gasification projects, which could be an aversive factor for some investors. (C) 2008 Elsevier Ltd. All rights reserved

Logistics issues of biomass : the storage problem and the multi-biomass supply chain

Biomass is a renewable energy source with increasing importance. The larger fraction of cost in biomass energy generation originates from the logistics operations. A major issue concerning biomass logistics is its storage, especially when it is characterized by seasonal availability. The biomass energy exploitation literature has rarely investigated the issue of biomass storage. Rather, researchers usually choose arbitrarily the lowest cost storage method available, ignoring the effects this choice may have on the total system efficiency. In this work, the three most frequently used biomass storage methods are analyzed and are applied to a case study to come up with tangible comparative results. Furthermore, the issue of combining multiple biomass supply chains, aiming at reducing the storage space requirements, is introduced. An application of this innovative concept is also performed for the case study examined. The most important results of the case study are that the lowest cost storage method indeed constitutes the system-wide most efficient solution, and that the multi-biomass approach is more advantageous when combined with relatively expensive storage methods. However, low cost biomass storage methods bear increased health, safety and technological risks that should always be taken into account. (C) 2008 Elsevier Ltd. All rights reserved

Time-dependent opportunities in energy business : a comparative study of locally available renewable and conventional fuels

This work investigates and compares energy-related, private business strategies, potentially interesting for investors willing to exploit either local biomass sources or strategic conventional fuels. Two distinct fuels and related power-production technologies are compared as a case study, in terms of economic efficiency: the biomass of cotton stalks and the natural gas. The carbon capture and storage option are also investigated for power plants based on both fuel types. The model used in this study investigates important economic aspects using a "real options" method instead of traditional Discounted Cash Flow techniques, as it might handle in a more effective way the problems arising from the stochastic nature of significant cash flow contributors' evolution like electricity, fuel and CO(2) allowance prices. The capital costs have also a functional relationship with time, thus providing an additional reason for implementing, "real options" as well as the learning-curves technique. The methodology as well as the results presented in this work, may lead to interesting conclusions and affect potential private investment strategies and future decision making. This study indicates that both technologies lead to positive investment yields, with the natural gas being more profitable for the case study examined, while the carbon capture and storage does not seem to be cost efficient with the current CO(2) allowance prices. Furthermore, low interest rates might encourage potential investors to wait before actualising their business plans while higher interest rates favor immediate investment decisions. (C) 2009 Elsevier Ltd. All rights reserved

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