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Abstract Commercial potential in developing countries has always received a great attention from international investors, but this is not the case in Waste-to-Energy sector. Waste-to-Energy is bound up with various uncertainties rooted in its long-term nature therefore incorporating risks regarding political matters in developing countries makes it more complex. The present study substantiates the incompatibility of classic valuation methods in risky projects. Consequently, to deal with the riskiness of Waste-to-Energy investment in less developed countries, the combination of binomial tree analysis and Decoupled NPV is proposed. The hybrid approach is deployed to value a Waste-to-Energy project in Iran, and all evidence attest to the robustness of the method. The contribution of this paper can open up new vistas for investing in Waste-to-Energy industry, thus abating the catastrophic effects of landfill gas emissions.

Abstract Installation of a significant number of distributed generators (DGs), besides the application of non-sinusoidal loads such as; Plug-in Hybrid Electric Vehicles (PHEVs), in the emerging smart distribution networks and the industrial plants have posed a major challenge to the existing methods of optimal transformer sizing (OTS). The harmonic currents generated in these new environments not only substantially increase the transformer load losses, but also cause abnormal winding temperature rise and hence transformer excessive loss of life. Therefore, the harmonic contents of the loads currents should be accounted in choosing the appropriate size of distribution transformers. To address this concern of utilities, this paper introduces a new method to solve the OTS problem in such environments. It takes into account the effects of harmonics currents on excessive heat generation in a transformer and the transformer insulation loss of life due to these thermal stresses. This paper proposes a new dynamic programming (DP) framework to solve the OTS problem. Although the proposed DP method considers the transformer thermal equations, however, by introducing a novel variable named the depreciation cost, the consecutive stages of the proposed DP network are hold independent. Therefore, the proposed DP method does not require any supplementary heuristic algorithm to solve the OTS problem. In response, the proposed method is very fast and easy to implement. Comprehensive studies are carried out to validate the effectiveness of the proposed algorithm.

Public transportation is one of the most promising transportation modes to reduce the environmental emissions of the transportation sector in the U.S. In order to mitigate the environmental impacts brought by the transit bus system, new energy buses are introduced into the vehicle market. The goal of this study is to find an optimal bus fleet combination for different driving conditions to minimize life cycle cost, greenhouse gas emissions, and conventional air pollutant emission impacts. For this purpose, a Multi-Objective Linear Programming approach is used to select the optimum bus fleet combinations. Given different weight scenarios, this method could effectively provide solutions for decision makers with various budget constraints or emission reduction requirements. The results indicate that in heavily congested driving cycles such as the Manhattan area, the battery electric bus is the dominant vehicle type, while the hybrid bus has more balanced performances in most scenarios because of its lower initial investment comparing to battery electric buses. Petroleum powered buses have seldom been selected by the model. The trade-off analysis shows that the overall greenhouse gas impact performance is sensitive to the life cycle cost after certain points, which could provide valuable information for the bus fleet combination planning.

Abstract Discrete choice models are developed for decisions to participate in home energy audit and loan programs. A nested logit model of joint audit and loan decisions is also estimated. The results suggest that attitudinal variables concerning the information value and convenience of audits are the best predictors of the audit choice. A belief that conservation retrofits improve home value is the best predictor of the loan choice. The nested logit model results show that audit and loan choices are independent; this is probably due to a low level of awareness about loan availability.

Abstract The univariate sweeping tests for fuel injection pressure, injection timing and exhaust gas recirculation (EGR) rate were conducted on a three-cylinder gasoline extended range Atkinson cycle engine (ACE). The effects of above parameters on combustion, emission and performance of ACE were studied and some useful conclusions were obtained. In general, injection pressure has little effect on combustion and engine performance except at the injection advance of 280 deg, while its effect on emission is obvious. With injection pressure rising, NOx first increases and then decreases, while CO follows a reverse trend. Compared with injection pressure, injection timing has more significant effects. As injection timing is advanced, the max combustion pressure first increases and then decreases and the peaks appear around 300deg and 320deg. The lower EGR rate reduces BSFC and NOx with little influence on other emissions. At the EGR rate of 7%, NOx decreases significantly (up to 57.5%), CO, particle number (PN) and particle density are almost unchanged, and BSFC decreases by 4 g/(kW·h) at most. As EGR rate increases to 11%, only NOx further decreases, while other emissions become worse. Thus, a lower EGR rate (e.g., 7%) combining with reasonable injection advance (300deg) is suggested to improve ACE performance.

We propose a method for residential end-use load analysis in developing countries. The times of use of home appliances were established by conducting face-to-face surveys, from which typical hourly load curves are obtained. For N. Cyprus, where the winter peak is the critical load, electrical heating of water and space is the dominant activity. DSM measures can reduce the peak by approximately 53 MW at the expense of US$12 million. A capital investment of $100 million for a new power plant may be deferred for 20 years.

Abstract Marginal costs of electricity vary by time and location. In the past, researchers attributed the variations to factors related to electricity generation and transmission. These authors, however, have not analyzed possible variations in marginal distribution capacity costs (MDCC). The objectives of this paper are: 1. (i) to show that large MDCC variations are due to the dispersion in distribution capital expenditures by time and space, 2. (ii) to propose a method for quantifying the area- and time-specific MDCC in the presence of lumpy investments, and 3. (iii) to compare our MDCC estimates to those commonly used in the electric utility industry. Our proposed method and its results were adopted by the California Public Utilities Commission (CPUC) in 1992 for Pacific Gas and Electric Company (PG&E), the largest privately owned electric utility in the U.S.

The Asia-Pacific region has the most rapidly growing energy demand in the world and will continue to have an increasing impact on world energy demand. Given the heterogeneity of economies in the region, any regional demand analysis has to be constructed country by country. In undertaking the demand forecasts provided in this study, scenarios were developed for high, low, and base cases that take into account variations in economic performance, prices, and fuel substitution in individual nations and in the region as a whole. China is included in the aggregate regional data provided in this article. Data from the countries of the former Soviet Union are not included in the regional totals in this article and are discussed separately in article 4.

Abstract Large amounts of heat is wasted through air coolers and water coolers for cooling low temperature ( H ) recovered in the evaporator were 8.0–8.6 MW for ORC using i-pentane as working fluid and 8.2–8.3 MW for Kalina cycle, respectively. Efficiency (η) of selected systems obtained at the highest power generated (W T ) was 10.0% (W T = 862 kW) for ORC and 10.57% (W T = 996 kW) for Kalina cycle within the design boundaries. Calculated carbon dioxide (CO 2 ) emission reduction potential was 2260 t/y for ORC and 2600 t/y for Kalina system, respectively, at advantageous process conditions. Results showed that Kalina cycle provided higher efficiency and power generation ability on expense of higher system pressure (29 bar–7 bar). Economic calculations showed that the payback time is about 5.0 year for both systems.

Abstract Maintenance of distribution systems has become more important due to the need to increase energy availability, quality and safety, and also reduce operation cost. Accordingly, the maintenance strategy in distribution systems is one of the most important decision-making activities. One of the most important evaluations for deciding the adequate performance of power distribution system is the identification of the critical components. On the other hand, the budget for maintenance of components is limited, so the maintenance should only be performed on critical components. Identifying the critical components is used to achieve the objective of minimising the cost for maintenance actions. This paper presents a new weighted importance (WI) reliability index model and proposes an appropriate method in order to prioritise the elements of distribution system for reliability-centered maintenance (RCM) at two different levels. At the first level, the feeders of a sample distribution substation are prioritised for the RCM actions. The second level is more detailed than the first level. At the second level, the components of a sample feeder are prioritised for the RCM actions. The reliability of system can be increased to as much as required level while minimal maintenance to be done by the maintenance prioritisation of the system components and performing the maintenance actions on the critical components. Appropriate maintenance decision-making for the critical components of distribution system can lead to the improvement in the reliability of distribution system.