Industrial energy efficiency: the need for investment decision support from a manager perspective

Global competition, commitment to the Kyoto Protocol and a deregulated, integrated European electricity market will in all probability increase the demand for energy efficiency on the part of companies in Sweden. Investment decisions are an important part of meeting the new demands, because they decide the future efficiency of industrial energy systems. The objective of this study is to investigate, from a managerial perspective, the need to improve decision support in some industries, which can help to facilitate and improve investment decisions concerning energy efficiency. This work has been conducted through in-depth interviews with representatives for a number of energy-intensive companies and non-energy-intensive companies from different sectors. One need that was identified was the improvement of working methods in order to support the decision-making process. Here, external players seem to be playing an increasingly important role. Access to correct information, better follow-up activities, and transparent, understandable calculations are also considered to be important. The study will form the foundation for subsequent work on decision support and energy efficiency in industry.     

Private sector participation in infrastructure projects: a methodology to analyse viability of BOT

Many developing countries are now attempting to finance new infrastructure projects through private sector participation. This paper outlines a methodology based on financial and risk analyses that a government or a government utility can use to analyse the viability of private sector participation in new infrastructure projects. The water supply projects in Sri Lanka are used for the case study to outline the methodology. Financial analyses of a bulk water supply project and a water distribution project are carried out to estimate subsidy percentages that are required to make the projects viable, using a model developed for the investment analysis of all types of infrastructure project. This analysis looks at four pricing options for the bulk supply project, and sixteen procurement options for the distribution project, from the view point of the utility, for three cases of non-revenue water (35% as base case, 50% and 25% as extreme cases). The risk analysis takes into account the risk and uncertainty in non-revenue water, cost and demand estimates, rate of debt and forecasts of escalation. These analyses show that the best option for the utility is to obtain both bulk supply and distribution projects through private sector participation using BOT arrangements.     

Machine tool justification policies: Their effect on productivity and profitability

The primary purpose for the existence of business in the United States is to create profits for their owners. A major factor in determining a firm's profit level is the extent to which it uses the available manufacturing technology. Therefore, an organization's policy concerning capital equipment purchases (primarily machine tools) will have a direct effect on the firm's profitability, productivity, and ultimately its competitive stature.It is the purpose of this study to determine the effect of the methods being used to analyze potential machine tool investments on profitability and productivity. The methods used to analyze these investments are hereafter referred to as justification policies.This report is divided into three sections. The heart of this study is a survey that was developed specifically for this study. The first section of this report details the purpose and formulation of this survey. The second section includes the survey results and interpretations. The final section offers an example of an optimal justification policy and compares the effect of using this policy on productivity versus the justification policies currently being used in industry.     

Study of Real Options with Exogenous Competitive Entry to Analyze Dispute Resolution Ladder Investments in Architecture, Engineering, and Construction Projects

Architecture, engineering, and construction industry participants often find it pragmatic to implement a project-specific dispute resolution ladder (DRL) as a managerial tool to assist in the prompt resolution of claims and change orders (CCOs) that might arise during the project construction phase. This project-specific DRL consists of a single or multiple alternative dispute resolution (ADR) techniques that require capital expenditures to cover the expenses incurred by the owner’s/contractor’s employees and third-party neutrals. If a project-specific DRL is properly chosen, then the capital expenditures are outweighed by the expected benefits from the DRL implementation; namely, prompt resolution of the CCOs without incurring excessive cost overruns on an already financially stressed project budget, as well as avoiding the escalation of the claims to a dispute that requires long protracted litigation for final settlement. Typically, the decision as to which ADR techniques to include in the project-specific DRL is undertaken during the project planning phase prior to the actual occurrence of the CCOs. In this case, the project owner decide to invest in a DRL in exchange for the expected savings in the project. This decision regarding the project-specific DRL is usually done based on the experience of the project parties with the ADR techniques. However, such a decision needs to be guided by a financial tool that allows the project owner to evaluate alternative DRLs and choose the most economically feasible alternative based on the project and ADR characteristics. In this paper, a financial model is developed to evaluate DRL implementations in construction projects by drawing analogies from real option theory with exogenous competitive entry. More specifically, the occurrence of a given CCO will result in a reduction in the value of expected savings in the project due to DRL implementation. This is similar to the reduction in the gross value of a capital investment project in a commercial property due to competitive entry by another similar commercial property developer in the market. At the same time, the CCO resolution due to an effective DRL implementation will allow project owner to recover part of the losses in the expected savings in the project due to the DRL implementation. The model presented in this paper takes into account the characteristics of the various ADR techniques included in the project-specific DRL, and the characteristics of the CCOs occurring during the construction phase of the project. A case study of a real construction project is used to illustrate the practical implementation of the model. The results indicate that for this case project and from a financial point of view, the investment in the chosen project-specific DRL was not worthwhile because of the high uncertainty in the project, and the low effectiveness of the selected DRL. These conditions did not provide the owner with the anticipated advantage of the DRL implementation in reducing the value of the CCOs occurring in the project. At the same time the cost of the DRL implementation exceeded the actual savings attained in the project.     

Economic Transmission Planning Model Suitable for a Regulated Network Service Provider

Conventional transmission planning models are subject to constant debate in the context of competitive markets, due to the functional unbundling of transmission sector from generation and distribution sectors and due to the new environment regulations. A value-based transmission planning model is proposed, suitable for an unbundled transmission network service provider having no assets in the generation sector. The model minimizes the long-term transmission investment costs and the expected social costs incurred to its clients, energy producers, and consumers, in the power auctions due to transmission bottlenecks. The uncertainties involved when incorporating short-term market models into long-term planning models are modeled with probabilistic representations for the bid prices, the component availabilities, and the hourly load variations. These features make this model suitable in the new environment paradigm. Generalized Benders decomposition technique with nonsequential Monte Carlo technique is employed to solve the final stochastic mixed-integer optimization model. Case studies are given to illustrate the performance of this model by implementing it in the modified Garver’s six-bus test system and the IEEE 24-bus reliability test system for a single planning year.     

Explaining the diversity of motivations behind community renewable energy

Community-based renewable energy initiatives may be important actors in the transition toward low-carbon energy systems. In turn, stimulating investments in renewable energy production at the community level requires a better understanding of investors' motives. This paper aims to study the heterogeneity of motivations that drive individuals to participate in community renewable energy projects and the underlying explanatory factors behind this, as well as the implications for their level of engagement in initiatives. Based on quantitative data from an original survey conducted with two renewable energy cooperatives in Flanders, the statistical analysis shows that cooperative members should not be considered as one homogeneous group. Several categories of members with different motives and levels of engagement can be distinguished. This heterogeneity is explained by contrasts in terms of institutional settings, spatial patterns and attitudes to the diffusion of institutional innovations. Regarding policy implications, the findings suggest that this heterogeneity should be taken into account in designing more effective supporting policies to stimulate investments at the community level. The activation of social norms is also shown to be a promising mechanism for triggering investment decisions, although the implications of its interplay with economic incentives should be further explored.     

A decision support system for generation expansion planning in competitive electricity markets

This paper describes an approach to address the generation expansion-planning problem in order to help generation companies to decide whether to invest on new assets. This approach was developed in the scope of the implementation of electricity markets that eliminated the traditional centralized planning and lead to the creation of several generation companies competing for the delivery of power. As a result, this activity is more risky than in the past and so it is important to develop decision support tools to help generation companies to adequately analyse the available investment options in view of the possible behavior of other competitors. The developed model aims at maximizing the expected revenues of a generation company while ensuring the safe operation of the power system and incorporating uncertainties related with price volatility, with the reliability of generation units, with the demand evolution and with investment and operation costs. These uncertainties are modeled by pdf functions and the solution approach is based on Genetic Algorithms. Finally, the paper includes a Case Study to illustrate the application and interest of the developed approach.     

A compound real option and AHP methodology for evaluating ICT business alternatives

After the liberalization of information and communication technology (ICT) markets many potential providers have appeared. Thus, business complexity, for ICT decision makers, has increased. In this paper, we focus on the problem of selecting the optimal business evolution path for ICT, focusing on the broadband technology (BT) field. Traditional quantitative cost–benefits analysis, such as net present value (NPV), is by no means sufficient for capturing the complexity of the problem in its entire. Researchers suggest the real options (ROs) for valuating ICT investments. However, RO models are strictly quantitative and very often ICT investments may also contain qualitative factors, which cannot be quantified in monetary terms. In addition, ROs analysis itself brings to the “surface” some factors that can be more efficiently treated qualitatively. We combine the ROs and analytic hierarchy process (AHP) into a common decision analysis framework providing an integrated multicriteria model, called ROAHP, for prioritizing ICT business alternatives. The proposed model is applied to a real life BT business case, showing how it can be formulated and solved.     

Investment Model for Power Generation and Transmission Network Expansion in Turkey

Provision of adequate electricity is one of the major factors for industrial and commercial development. However, decisions on the expansion of electricity are bogged down by high investment requirements and nonsynchronized expansion between electricity generation and transmission systems. As a rule, the investment requirements for these types of projects are immediate but their benefits can be obtained only in the long-term basis albeit electricity planners base their decisions on immediate requirements of shorter terms. As investment funds are very hard to come by, the funds, if available, should be utilized to maximum by minimizing the investment through a synchronized expansion planning of both electricity generation and transmission systems. This paper attempts to address this opportunity. We have proposed here a mixed integer model to develop concurrent transmission and generation investments plans. The model selects new generation plants or generation capacity expansions for existing plants that are located on the interconnected network by considering explicitly congestion in the transmission network. Hence the model contributes to this area by filling in the gap between models for developing long-term power generation policies and power flow models focusing on transmission network expansion. The application of the model in Turkey’s electricity network highlights the country’s congested areas in the transmission network, which might lead to loss of load and inefficient generation capacity expansion if not tackled properly. The analysis shows that a cost efficient generation expansion is possible to realize in congested regions if proper transmission expansion decisions are made concurrently with generation expansion decisions.     

Optimization of Investments in Natural Gas Distribution Networks

This paper presents an optimization model and solution procedure for planning investments in gas distribution networks for residential customers. The situation can be considered a capital budgeting problem under uncertainty. There is uncertainty about whether a potential customer will convert to gas service if a distribution main is built, the revenue generated if the household does convert, and the cost of constructing the main. A fixed annual budget is allocated to a set of discrete, competing projects over time. The allocation is done by maximizing the expected net present value (NPV) given the decision-maker’s risk preferences. The probability distribution of the NPV for each competing project is created from two statistical models. A binary probit model is used to estimate the probability of conversion for a potential customer. A random effects regression model is used to estimate the revenue generated should a particular potential customer switch to gas. A rollout value greedy heuristic was devised to solve the resulting optimization formulation. Two case studies based on data from a large gas company illustrate the analysis.