Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Conse-quently,open access to the transmission system is one of the basic topics to allow compe...     

FRESCO,a simplified code for cost analysis of fusion power plants

FRESCO (Fusion REactor Simplified COsts) is a code based on simplified models of physics, engineering and economical aspects of a TOKAMAK-like pulsed or steady-state fusion power plant. The experience coming from various aspects of ITER design, including selection of materials and operating scenarios, is exploited as much as possible.Energy production and plant power balance, including the recirculation requirements, are derived from two models of the PPCS European study, the helium cooled lithium/lead blanket model reactor (model AB) and the helium cooled ceramic one (model B). A detailed study of the availability of the power plant due, among others, to the replacement of plasma facing components, is also included in the code.The economics of the fusion power plant is evaluated through the levelized cost approach. Costs of the basic components are scaled from the corresponding values of the ITER project, the ARIES studies and SCAN model. The costs of plant auxiliaries, including those of the magnetic and electric systems, tritium plants, instrumentation, buildings and thermal energy storage if any, are recovered from ITER values and from those of other power plants.Finally, the PPCS models AB and B are simulated and the main results are reported in this paper.     

Cost and revenue efficiency in DEA-R models

One of the most important information given by DEA models is the cost and revenue efficiency of decision making units (DMUs). Cost efficiency is defined as the ratio of minimum costs to current costs, while revenue efficiency is defined as the ratio of maximum revenue to current revenue of the DMU. This paper aims to create models for the estimation of cost and revenue efficiency, with particular attention being paid to ratio DEA (DEA-R) models. This group of models eliminates some of the disadvantages associated with standard DEA models. The main contribution is the formulation of linear models for cost and revenue efficiency based on DEA-R models. The results given by the new models, as well as by the standard models are compared to a real data set – the evaluation of 21 medical centers in Taiwan.     

Insight into biochar properties and its cost analysis

Biochars (BCs) are widely produced and used for the remediation of environmental contaminants as bio-sorbents. In this review, statistical analysis of different BC physico–chemical properties was conducted. It was observed that woody materials are the most suitable for preparing BCs, among many other potential raw materials such as food wastes and agricultural materials. Currently BCs are produced through a variety of thermal treatment processes between 300 and 900 °C, among which slow pyrolysis is widely used due to its moderate operating conditions and optimization of BC yields. Hydrothermal carbonisation (HTC) is also an effective approach for BC production under certain conditions. As pyrolysis temperature is increased, the carbon content, ash content, surface area, and pore volume tend to be increased while the yield, hydrogen, oxygen, nitrogen content, and H/C and O/C molar ratios tend to decrease. The economic feasibility of BCs depends on a range of factors from raw material price to efficient production technologies. Thus, the overall cost equation of a pilot BC production plant together with the cost equation for BC regeneration has been proposed. The future research directions of BCs are also elaborated.     

Logistics cost analysis of rice straw pellets for feasible production capacity and spatial scale in heat utilization systems: A case study in Nanporo town,Hokkaido, Japan

Rice straw is a promising renewable energy source because it is abundantly available in Asia. This study conducted a case study of logistics cost analysis for rice straw pellets by considering all stages in the supply chain to define the main factors affecting the selling price of rice straw pellets: collection (job-commission or employment of part-time workers), transportation, storage (vinyl greenhouses or storage buildings with larger capacity), pelletizing, and delivery to users with biomass boilers. The selling price was found to be strongly dependent on the production capacity because the investment cost for the pellet production facility had a significant effect of economies of scale. A production capacity of larger than 1500 t y⁻¹ is required for rice straw pellets to compete with wood pellets and fossil fuels in the studied Japanese context if the subsidy rate for the investment is 50%, part-time workers conduct the collection, and rice straw is stored in the storage buildings. Our sensitivity analysis also showed an economically feasible spatial scale: for example, rice straw should be collected within a 20 km radius and the users should be within a 38 km radius when the production capacity is 1500 t y⁻¹. In addition, other critical factors related to the collection of rice straw from the paddy fields and transportation of rice straw rolls to storage were identified as planning factors to further reduce the total logistics cost of rice straw pellets.     

Probabilistic cost prediction for submarine power cable projects

It is estimated that Europe alone will need to add over 250,000 km of transmission capacity by 2050, if it is to meet renewable energy production goals while maintaining security of supply. Estimating the cost of new transmission infrastructure is difficult, but it is crucial to predict these costs as accurately as possible, given their importance to the energy transition. Transmission capacity expansion plans are often founded on optimistic projections of expansion costs. We present probabilistic predictive models of the cost of submarine power cables, which can be used by policymakers, industry, and academia to better approximate the true cost of transmission expansion plans. The models are both generalizable and well-specified for a variety of submarine applications, across a variety of regions. The best performing statistical learning model has slightly more predictive power than a simpler, linear econometric model. The specific decision context will determine whether the extra data gathering effort for the statistical learning model is worth the additional precision. A case study illustrates that incorporating the uncertainty associated with the cost prediction to calculate risk metrics - value-at-risk and conditional-value-at-risk - provides useful information to the decision-maker about cost variability and extremes.     

Hydrogen production methods efficiency coupled to an advanced high-temperature accelerator driven system

Hydrogen, rather than oil, must be produced in volumes not provided by the currently employed methods. In this work, two high-temperature hydrogen production methods coupled with an advanced nuclear system are presented. A new design of a pebble-bed accelerator nuclear-driven system called TADSEA (Transmutation Advanced Device for Sustainable Energy Applications) was chosen because of the advantages in transmutation and safety. A detailed flowsheet of the high-temperature electrolysis process coupled to TADSEA through a Brayton gas cycle was developed using chemical process simulation software: Aspen HYSYS^®. It is obtained 0.1627 kg/s of hydrogen with the model with optimized operating conditions, resulting in an overall process efficiency of 34.51%, a value in the range of results reported by other authors. A conceptual design of a plant using the iodine-sulfur thermochemical water splitting cycle was carried out producing 5.66e-2 kg/s and electric energy in cogeneration. The overall efficiency was calculated performing an energy balance resulting in 22.56%. A brief hydrogen production cost estimation was performed for both methods obtaining 5.96$/kg for the sulfur-iodine (SI) and 4.8 $/kg for the high-temperature electrolysis (HTE) process.     

The role of decentralized generation and storage technologies in future energy systems planning for a rural agglomeration in Switzerland

This study presents a framework to quantitatively evaluate decentralized generation and storage technology (DGST) performance and policy impacts in a rural setting. The role of DGSTs in the future energy systems planning of a rural agglomeration in Switzerland is examined using a cost optimization modeling approach. Heat and electricity demand for major sectors are considered. Scenarios introduce DGSTs in a stepwise manner to measure incremental impacts on future capacity planning compared to a baseline scenario. Sub-scenarios also examine the impacts of carbon mitigation policies, and a sensitivity analysis is carried out for key energy carriers and conversion technologies. DGSTs enable a significant reduction in electricity grid usage for the community considered. Small hydro with a storage reservoir and photovoltaics enable the community to become largely self-sufficient with over 80% reductions in grid imports by 2050 compared to the baseline scenario. Storage enables maximum usage of the available hydro potential which also leads to network upgrade deferrals and a significant increase in photovoltaic installations. Investment decisions in small hydro are robust against cost variations, while heating technology investment decisions are sensitive to oil and grid electricity prices. Carbon pricing policies are found to be effective in mitigating local fossil fuel emissions.     

The injury profile of a large telecommunication company: a statistical summary

Overexertion injuries have been a major concern to occupational safety and health professionals for quite some time. Over the years, these injuries have continued to increase despite ergonomic interventions to control their frequency of occurrence. It has been speculated that this increase may be due primarily to enhanced awareness and better record-keeping. Many occupational safety and health professionals also presume that overexertion injuries and occupational illnesses are confined to heavy manufacturing industries. This paper reports occupational injury and illness data from a large telecommunication industry, collected over a 7-year period. Three observations were made from the statistical summary: (1) better record keeping may be a reason behind the reported increase in injuries; workday losses decline as a result of improved ergonomic and occupational health interventions; (2) serious injuries are not just limited to heavy manufacturing industries; and (3) reduction in workday losses may not translate in injury cost savings.     

Optimal control of combined heat and power units under varying thermal loads

This paper describes a model based optimizer that allows a combined heat and power (CHP) unit to supply backup power to a Smart Grid on the one hand and minimize the cost for heat and power supply on the other hand. The model of the CHP unit is lean but nevertheless accurately represents the unit behavior, including thermal behavior of the storage as well as the aging effect of engine starts. Thanks to the small model dimension we can solve the optimal dispatch problem efficiently using dynamic programming. Two selected soft- and hard-ware in the loop tests are discussed to demonstrate the performance of the approach. A re-optimization strategy is discussed that allows reactions to wrong predictions of external influences like weather.