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

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

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

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

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 and investment analysis of two biomass-to-heat supply chain structures

As oil prices have risen dramatically lately, many people explore alternative ways of heating their residences and businesses in order to reduce the respective cost. One of the options usually considered nowadays is biomass, especially in rural areas with significant local biomass availability. This work focuses on comparing two different biomass energy exploitation systems, aiming to provide heat to a specific number of customers at a specific cost. The first system explored is producing pellets from biomass and distributing them to the final customers for use in domestic pellet boilers. The second option is building a centralised co-generation (CHP) unit that will generate electricity and heat. Electricity will be fed to the grid, whereas heat will be distributed to the customers via a district heating network. The biomass source examined is agricultural residues and the model is applied to a case study region in Greece. The analysis is performed from the viewpoint of the potential investor. Several design characteristics of both systems are optimised. In both cases the whole biomass-to-energy supply chain is modelled, both upstream and downstream of the pelleting/CHP units. The results of the case study show that both options have positive financial yield, with the pelleting plant having higher yield. However, the sensitivity analysis reveals that the pelleting plant yield is much more sensitive than that of the CHP plant, therefore constituting a riskier investment. The model presented may be used as a decision support system for potential investors willing to engage in the biomass energy field

The experience curve effect on renewable energy penetration

The experience curve effect has always challenged technology-related decisions. In the electricity sector, new renewable electricity generation technologies have shown a considerably high learning rate up to now, which could differentiate the profitability of energy generation technologies in the near future. The scope of this work is to investigate the effect that the Experience Curve of the renewable energy technologies may have on the orders for new electricity generation technologies and therefore, on the future electricity generation mix of Greece. The official renewable energy generation targets are considered as a constraint of the system, and the learning rates of the various technologies are included in the calculations. Three scenarios of learning rates have been applied, to examine the experience curve effect on renewable energy penetration. The national electricity generation system is modelled for long-term analysis and a linear programming method is applied, in order to come up with the optimal generating mix that minimizes electricity generation cost, while satisfying the national emissions reduction targets. In addition, two scenarios for future emission allowance prices are considered, in order to examine the effect of changes in this very volatile parameter. Furthermore, an investigation is made to identify if a point should be expected when renewable energy will be more profitable than conventional fuel electricity generation

Economic evaluation of waste management options for remote areas

Municipal solid waste management is one of the most pressing issues of today’s societies as the consequences of growing economies in waste generation have serious effects on the environment. These effects are even more difficult to tackle in remote areas such as islands or mountainous areas, both types of which are dominant in the Greek topography. More specifically, the current situation is compared financially to a municipal solid waste transportation scenario for treatment in large scale facilities. A statistical analysis of population data and waste generation in the past years will be used to predict the future waste generation in the examined regions. This research concentrates on areas where sanitary landfills are either obsolete or non-existent, and where the common practice is using open dumps. Using geographical data in conjunction with satellite information and some rough estimations for fuel cost in the future, transportation costs are calculated. Advantages of the examined scenario are not limited to monetary terms, but also include social gains for these regions along with new job opportunities. Potential benefits arising from the concentration of transported waste will be explored, and the scope for further research will be presented