Scheduled Shutdown Research Articles

Exit economics: The relatively low cost of Germany’s nuclear phase-out

The decision of the German government, post-Fukushima, to phase out the country’s nuclear power sector by 2022 builds on legislation in place since 2002. This earlier legislation was amended in 2010 to extend the lifetime of the nuclear plants, but the German parliament reversed this extension in the summer of 2011, slightly accelerating the original phase-out schedule; therefore, the market and the nuclear operators were prepared for the shutdown schedule. In this context, it is not surprising that the observed price impacts from the shutdown of 40 percent of the German nuclear power capacity in 2011 are smaller than some modeling exercises had projected. When empirical observation is analyzed in light of a range of economic models, the price effect of the nuclear phase-out can be expected to peak at 5 euros per megawatt-hour or less for a few years around 2020, a reasonably small increase compared with the uncertainties created by other fundamental determinants of Europe’s electricity prices. The macroeconomic effects attributable to the complete shutdown of nuclear power also appear likely to be relatively small, peaking at perhaps 0.3 percent of gross domestic product or less a few years before 2030. In the end, the management of the German transition to an energy mix dominated by renewable energies—and not the use of the existing nuclear reactor fleet for a decade more or less—will be the key determinant of whether that shift has larger or smaller effects on electricity prices or on the German economy overall.

A Proposed Method for Planning the Best Initial Response to Kicks Taken During Managed-Pressure-Drilling Operations

Summary An industry-supported research project has investigated well-control methods for managed-pressure drilling (MPD) using the constant-bottomhole-pressure (CBHP) method. This paper proposes a method for planning the best initial response to be used when a kick occurs during CBHP MPD on the basis of conclusions from the research. That research (Davoudi et al. 2010) concluded that the three most widely applicable initial responses to kicks during MPD were increasing casing pressure until flow out equals flow in, shutting the well in, and using an adaptation of an MPD-pump shutdown schedule to detect and shut in a low-rate kick. Increasing pump rate until flow out equals flow in was concluded to have limited, but potentially still important, applications. The proposed method uses a decision tree during the planning phase of a well to select the best kick response to be used for each hole interval for inclusion in the drilling program. This selection is based on the desired tolerance to kicks, equipment being used, well geometry, and conclusiveness of the kick warning signs. The equations necessary to calculate decision parameters, example calculations for an application of the decision tree, and comparison of simulation results to application of the decision tree are included. The decision tree indicates the response that maximizes kick tolerance within the well design, gives a basis for revising equipment or well design to maximize kick tolerance, and supports calculation of the expected kick-tolerance advantage of the increasing-casing-pressure response vs. a shut-in response.

Analysis of organizational conditions for risk management: the case study of a petrochemical site

This paper presents an ergonomic intervention in the petrochemical sector. The scheduled shutdown of one of the gas production sites has led the management to reduce the number of personnel on site, and then to get new recruits and experienced technicians from other sites as the policy for leaving personnel had not been properly planned, resulting in understaffing on site. Workers with seniority on the site, and who are also the most experienced do not accept the way newcomers are induced on site, whereas the management accuses them of resisting change. The intervention consisted in reconnecting local and corporate management through making the work activity visible and linking two sets of data that they held separately. Different types of analyses were made, work demography, decision making processes and tools used by the management, analysis of the building of career and work logics. Those different levels of analysis are gathered in macro-ergonomics, while showing the possible combinations between top down and bottom up approaches. The intervention resulted in concrete changes: HR simulation tool, training organisation, feedback.

Weathered Ilmenite: Diverse Mechanisms of Sintering and Association with Contaminants

We briefly review the nature and provenance of extremely weathered ilmenite, then investigate its fate when it is 10 % of a blended feed in the reduction kilns of the Becher process. There it is bound, unintentionally and intermittently, in sinter, which is discarded. It takes with it discrete aluminosilicate grains as well as contaminants, adsorbed and occluded within the ilmenite. Two distinct sintering mechanisms are identified. A layered wall accretion forms purely by solid state reaction, and is thickest early in the kiln. It occasionally detaches under its own weight or is eroded, and is tolerated between scheduled shutdowns for maintenance. However, if the weathered ilmenite and accompanying silica escape earlier wall accretion, a transitory aluminosilicate melt may later promote sintering of this material within the bed, adhering catastrophically to constrictions and obstructions on the kiln wall. The mechanisms and controlling factors are discussed.

Proposal and Preliminary Study on Installed Capacity Margin

The capacity of thermal power plants takes up 75 per cent of whole power generation capacity in China, and so a reserve of generation capacity margin that may adapt to the variations in power network load is of paramount importance. This paper proposes a concept: installed capacity margin, and basic mathematic modeling and example is analyzed. It would be supply theoretical help for real little thermal power plants shutdown schedules based on building detailed mathematical models after investigation of region-specific load structure characteristics and installed generator compositions.

Pumped-storage unit commitment with considerations for energy demand, economics, and environmental constraints

Aside from their zero fuel costs, the pumped-storage units can reduce emissions of thermal generating units. The objective of this study is to investigate (a) thermal unit commitment with considerations for environmental constraints (ECUC), and (b) pumped-storage and thermal unit commitment with considerations for environmental constraints (PSECUC) based on a new optimization methodology. The PSECUC determines the start-up and shut-down schedules of pumped-storage and thermal generating units that meet the required demand so that the costs for fuel, start-up, and emissions (TC) are minimized. For the ECUC (thermal generating units only), the results show improvements of 0.03 and 0.50% in TC and excess emissions (EXEM), respectively. For the PSECUC, it is determined that 2-pumped-storage units can simultaneously decrease the TC and EXEM by 1.20 and 60%, respectively.

Yield Stress of Wax Gel using Vane Method

Wax gel formation occurs in pipelines under quiescent conditions during a scheduled or emergency shutdown of flow. Paraffinic wax precipitates from the bulk oil when oil temperature decreases below the characteristic wax precipitation temperature, while the gelling begins as the temperature decreases below the pour point. Further temperature reductions below the pour point result in the development of a stronger gel. In this study, the gel strength was measured by determining the yield stress using the vane method. The method consisted of identifying the maximum torque exerted on the sample at various temperatures. Model oils were prepared by mixing low vacuum gas oil wax, mineral oil, and kerosene. Linear increase in gel strength with decreasing temperature was observed in the measured temperature range. As the wax content increased, so did the yield strength of the gel below the solution pour point. The slope of the yield-stress versus temperature line was also steeper for the model oil containing higher amount of wax. Recovery of gel strength was also examined by aging at the same temperature and by decreasing temperatures after breaking the gel at certain temperature.

Maintenance implications of critical components in ITER CXRS upper port plug design

Already in the early phase of a design for ITER, the maintenance aspects should be taken into account, since they might have serious implications. This paper presents the arguments in support of the case for the maintainability of the design, notably if this maintenance is to be performed by advanced remote methods. This structure is compliant to the evolving maintenance strategy of ITER. Initial results of a Failure Mode Effects and Criticality Analysis (FMECA) and a development risk analysis for the ITER upper port plug #3, housing the Charge Exchange Recombination Spectroscopy (CXRS) diagnostic, are employed for the definition of the maintenance strategy. The CXRS upper port plug is essentially an optical system which transfers visible light from the plasma into a fiber bundle. The most critical component in this path is the first mirror (M1) whose reflectivity degrades during operation due to deposition and/or erosion dominated effects. Amongst other measures to mitigate these effects, the strategy is to allow for a replacement of this mirror. Therefore it is mounted on a retractable central tube. The main purpose of this tube is to make frequent replacements possible without hindering operation. The maintenance method in terms of time, geometry and spare part policy has a large impact on cost of the system and time usage in the hot cell. Replacement of the tube under vacuum and magnetic field seems infeasible due to the operational risk involved. The preferred solution is to have a spare tube available which is replaced in parallel with other maintenance operations on the vessel, as to avoid any interference in the hot cell with the shutdown scheduling. This avoids having to refurbish a full port plug and also allows for a more frequent replacement of M1, as we can replace the mirror anytime the vacuum vessel is vented, estimated to be once a year.

U.S. nuclear plant decommissioning funding adequacy — by individual funds, utilities, reactors, and industry-wide — assessed by Monte Carlo and baseline trend methods: 1998, 2000, 2001, and 2004

This paper assesses, over years 1998, 2000, 2001, and 2004 — using varying sets of assumption values — the adequacy of decommissioning funding (year-end) for United States' nuclear electric power plants. I assess each of the 222 individual trust funds and 99 utility owners (as of August 2003), as well as each of the 122 reactors, and industry-wide. Individual trust fund results are the most important because, in general, dollars may not be transferred from one fund to another to strengthen a less-adequately financed fund. Using stochastic (Monte Carlo) analysis (20,000 iterations) to incorporate risk, or uncertainty, in my simulation modeling, I assess funding adequacy for 2004, but with estimated balances and contributions data for 2004. The paper also assesses the baseline (most likely) trends in funding adequacy, using “point” estimates for years 1998, 2000, 2001, and stochastic medians for 2004. I compute two measures of funding adequacy relative to two respective benchmark levels: (1) adequacy of “current year” fund balances; and (2), adequacy of “recent-year” fund contributions. The former is a more “looking-backward” measure relative to a benchmark (i.e., current balance embodies all past year contributions and rates of return on fund assets); the latter, more “looking-forward” relative to a forward benchmark. I use decommissioning fund balances data for 2000 and 1998, as reported by the utilities to the U.S. Nuclear Regulatory Commission (NRC), as well as additional balances, yearly contributions, rates of return, and cost escalation data over 1997–2001 obtained in a 2002 survey of owners by the U.S. Government Accountability Office (GAO). The most fundamental conclusion that one should draw from my simulation modeling results — whether using Monte Carlo or baseline trend analysis — is that these decommissioning adequacy percentages for the 222 funds are extremely variable, although a sizable majority of funds are likely above benchmark. Reduced variability — but still wide — also pertains to the more aggregated results for utilities, reactors, and industry-wide. This variability applies not only at a given point in time, but also across time. Funding adequacies that are substantially below benchmark may be of concern to regulators and other policymakers because of the increased risk of a funding shortfall at scheduled (or premature) permanent plant shutdown. Moreover, when explicitly considering risk — i.e., Monte Carlo analysis — this variability is extremely large. For example, for 2004, while 35% of fund balances — on average — are below benchmark (median values), 82% are below at the lower 5% confidence level but only 8% are below at the upper 5% level. Future outcomes are obviously very uncertain! The public at large, future ratepayers, and/or utilities (i.e., stockholders) may be assessed for funding shortfalls; but, who should bear such responsibility? Have utilities, NRC, and state Public Utility Commissions (PUCs) adequately assessed risk when formulating, and approving, the future funding plans for these 222 individual decommissioning trust funds?

Designing machine operating strategy with simulated annealing and Monte Carlo simulation

This paper describes a simulation-based parameter design (PD) approach for optimizing machine operating strategy under stochastic running conditions. The approach presents a Taguchi-based definition to the PD problem in which control factors include machine operating hours, operating pattern, scheduled shutdowns, maintenance level, and product changeovers. Random factors include machine random variables (RVs) of cycle time (CT), time-between-failure (TBF), time-to-repair (TTR), and defects rate (DR). Machine performance, as a complicated function of control and random factors, is defined in terms of net productivity (NP) based on three key performance indicators: gross throughput (GT), reliability rate (RR), and quality rate (QR). It is noticed that the resulting problem definition presents both modeling and optimization difficulties. Modeling complications result from the sensitivity of machine RVs to different settings of machine operating parameters and the difficulty to estimate machine performance in terms of NP under stochastic running conditions. Optimization complications result from the limited capability of mathematical modeling and experimental design in tackling the resulting large-in-space combinatorial optimization problem. To tackle such difficulties, therefore, the proposed approach presents a combined empirical modeling and Monte Carlo simulation (MCS) method to model the sensitive factors interdependencies and to estimate NP under stochastic running conditions. For combinatorial optimization, the approach utilizes a simulated-annealing (SA) heuristic to solve the defined PD problem and to provide optimal or near optimal settings to machine operating parameters. Approach procedure and potential benefits are illustrated through a case study example.

Application of an immune algorithm to the short-term unit commitment problem in power system operation

An immune algorithm, which includes a fuzzy system and an annealing immune operator is presented. The proposed immune algorithm (PIA) is applied to the short-term unit commitment (UC) problem in power system operation. The PIA differs from its counterparts in three main aspects: (i) the crossover and mutation ratios are changed from having fixed values and become a variable that is determined by the fuzzy system; (ii) it uses a memory cell; and (iii) it uses an annealing immune operator. These modifications result in three major advantages for the PIA: (i) it does not fall into locally optimum solutions; (ii) it can quickly and correctly find the full set of globally optimum solutions; and (iii) it can easily obtain the most economic solution to the UC problem. In particular it can determine the start-up and shutdown schedules for the generation units so that they are able to meet forecasted demands at the minimum cost while satisfying adverse range of constraints. The PIA is used to generate schedules for cases containing 10, 20, 50, 70 and 90 generators. The schedules generated by the PIA are compared to those generated using the dynamic programming, Lagrangian relaxation, genetic algorithm, simulated annealing and tabu search methods. It is shown that the proposed method is valid and that it is able to produce excellent solutions.

Short-term thermal generation scheduling using improved immune algorithm

This paper proposes a new immune algorithm (NIA), which merges the fuzzy system (FS), the annealing immune (AI) method and the immune algorithm (IA) together, to resolve short-term thermal generation unit commitment (UC) problems. This proposed method differs from its counterparts in three main aspects, namely: (1) changing the crossover and mutation ratios from a fixed value to a variable value determined by the fuzzy system method, (2) using the memory cell and (3) adding the annealing immune operator. With these modifications, we can attain three major advantages with the NIA, i.e. (1) the NIA will not fall into a local optimal solution trap; (2) the NIA can quickly and correctly find a full set of global optimal solutions and (3) the NIA can achieve the most economic solution for unit commitment with ease. The UC determines the start-up and shut-down schedules for related generation units to meet the forecasted demand at a minimum cost while satisfying other constraints, such as each unit's generating limit. The NIA is applied to six cases with various numbers of thermal generation units over a 24-h period. The schedule generated by the NIA is compared with that by several other methods, including the dynamic programming (DP), the Lagrangian relaxation (LR), the standard genetic algorithm (GA), the traditional simulated annealing (SA) and the traditional Tabu search (TS). The comparisons verify the validity and superiority in accuracy for the proposed method.

Using chaos search immune genetic and fuzzy system for short-term unit commitment algorithm

This paper presents a hybrid chaos search (CS) immune algorithm (IA)/genetic algorithm (GA) and fuzzy system (FS) method (CIGAFS) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shut-down schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve and individual units. First, we combined the IA and GA, then we added the chaos search and the fuzzy system approach. This hybrid system was then used to solve the UC problems. Numerical simulations were carried out using three cases: 10, 20 and 30 thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as dynamic programming (DP), Lagrangian relaxation (LR), standard genetic algorithm (SGA), traditional simulated annealing (TSA) and traditional Tabu search (TTS). A comparison with an IGA combined with the chaos search and FS was carried out. The results show that the chaos search and FS all make substantial contributions to the IGA. The result demonstrated the accuracy of the proposed CIGAFS approach.

Using immune genetic algorithm based hybrid techniques for short-term unit commitment problem

This paper presents a hybrid chaos search (CS), immune algorithm (IA)/genetic algorithm (GA), and fuzzy system (FS) method (CIGAFS) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shut-down schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve, and individual units. First, we combined the IA and GA, then we added the CS and the FS approach. This hybrid system was then used to solve the UC problems. Numerical simulations were carried out using three cases: 10, 20, and 30 thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as dynamic programming (DP), Lagrangian relaxation (LR), standard genetic algorithm (SGA), traditional simulated annealing (TSA), and traditional Tabu search (TTS). A comparison with an immune genetic algorithm (IGA) combined with the CS and FS was carried out. The results show that the CS and FS all make substantial contributions to the IGA. The result demonstrated the accuracy of the proposed CIGAFS approach.

Application embedded chaos search immune genetic algorithm for short-term unit commitment

This paper presents a Hybrid Chaos Search (CS) immune algorithm (IA)/genetic algorithm (GA) and Fuzzy System (FS) method (CIGAFS) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shutdown schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve and individual units. First, we combined the IA and GA, then we added the chaos search and the fuzzy system approach. This hybrid system was then used to solve the UC problems. Numerical simulations were carried out using three cases: 10, 20 and 30 thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as dynamic programming (DP), Lagrangian relaxation (LR), Standard genetic algorithm (SGA), traditional simulated annealing (TSA), and Traditional Tabu Search (TTS). A comparison with an IGA combined with the Chaos Search and FS was carried out. The results show that the Chaos Search and FS all make substantial contributions to the IGA. The result demonstrated the accuracy of the proposed CIGAFS approach.

A study of a unit commitment problem with transmission constraints

AbstractUnit commitment problem is an optimization problem to determine the start‐up and shut‐down schedule of thermal units while satisfying various constraints, for example, generation‐demand balance, unit minimum up/down time, system reserve, and so on. Since this problem involves a large number of 0–1 type variables that represent up/down status of the unit and continuous variables expressing generation output, it is a difficult combinatorial optimization problem to solve. The study at present concerns the method for requiring the suboptimum solution efficiently.Unit commitment method widely used solves the problem without consideration of voltage, reactive power, and transmission constraints. In this paper, we will propose a solution of unit commitment with voltage and transmission constraints, based on the unit decommitment procedure (UDP) method, heuristic method, and optimal power flow (OPF). In this method, initial unit status will be determined from random numbers and the feasibility will be checked for minimum start‐up/shut‐down time and demand‐generation balance. If the solution is infeasible, the initial solution will be regenerated until a feasible solution can be found. Next, OPF is applied for each time period with the temporary unit status. Then, the units that have less contribution to the cost are detected and will be shut down based on the unit decommitment rules. This process will be repeated until suboptimal solution is obtained.The proposed method has been applied to the IEEE 118‐bus test system with 36 generating units with successful result. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 144(3): 36–45, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10187

The 7th neutron school for young scientists held in japan

The Neutron School for Young Scientists in Japan, the seventh in a continuing series, was held both at JAERI, with reactor-based neutrons, and at KENS, with accelerator-based pulsed neutrons, from October 21-25, 2002. The Japanese Society for Neutron Science (JSNS), which was newly established in 2001, organized this school for the second time. Until last year, the neutron school was always held in summer; therefore, it was called the Neutron Summer School. Since KENS is usually in a scheduled shutdown in July and August, the educational experiments at KENS were available only once out of six neutron schools. This is the reason why the school was held in October this year in order to use pulsed neutrons.

Characterization of Tokamak Dust Collected from Tore Supra

Tokamak dust, the particulate matter generated during operation of a tokamak fusion device, was collected from Tore Supra in December 1999, during the initial phase of the scheduled shutdown for installation of advanced plasma facing components. Surface mass densities of material collected from locations with measured surface area are 1100 mg/m2 at the vessel bottom and 15 mg/m2 on average for all other locations. The specific surface area of dust collected from several locations is nearly uniform with an average value of 1.32 g/m2. Geometric mean diameters of samples from different locations have an average value of 3.0 μm, although geometric standard deviations vary from 1.93 to 4.03. The dust is composed of various quantities of carbon, iron, nickel, silicon, and chromium, among other trace elements.

Fifth neutron summer school held in Japan

A summer school on neutron scattering for young scientists in Japan, the fifth in a continuing series, was held at KENS' facilities with pulsed neutrons, and JAERI with reactor-based neutrons, during the week of July 24 to 28, 2000. The Neutron Scat tering Association of Japan (NSAJ) organized this annual event. The school attract ed 24 participants, and the program was divided into two parts: the first half was held at KENS (Neutron Scattering Facilities at KEK, Tsukuba) and the other half at JAERI. Unfortunately, at that time, KENS was in a scheduled shutdown for improvement and rearrangement of shielding blocks near the source region, and the JRR-3M reactor at JAERI had shut down out of schedule just one week before the school. We had no neutrons for experiments in this summer school!

Technical Features and Long-term Operating Experience of Mitsubishi Advanced M 501 G Gas Turbine

The combined cycle power plant is recognized as one of the best thermal power plants for its high efficiency and cleanliness. Under these circumstances. Mitsubishi Heavy Industries, Ltd.(MHI) developed large, heavy-duty 1, 200C class M 701 D (for 50Hz utility) gas turbine and 1, 400C class M 501 F (for 60Hz)/M 701 F (for 50Hz) gas turbines. Their high efficiency and reliability for combined cycle applications have been proven in field operations. Based on the fact that the combined cycle efficiency is highly dependent on the gas firing temperature, MHI has newly developed the 1, 500C class M 501 G (for 60Hz)/M 701 G (for 50Hz), which is called “G” series, gas turbines.Development of the “G” series gas turbine was started in early 1990' s and the design was based on the following concepts, which give excellent performance and high reliability to the “G” series.Firstly, proven features from the “F” series are kept. Secondly, the most advanced technologies in aerodynamic design, heat transfer design and new materials for the “G” series are introduced. Thirdly, our conventional design criteria in industrial gas turbines are applied. Fourthly, NOx and the metal temperature remains at the same level as the “F” series by applying steam-cooled combustors even though the turbine inlet temperature is increased. Finally, special measurements and verification tests are carried out before commercial operation to secure their high reliability.The trial operation of the M 501 G was conducted in 1997 in the combined cycle verification plant in MHI Takasago. Japan. It was successful and the commercial operation was started in June 1997. Since then, the detail inspections were conducted and the condition of each component was quite sound. Therefore, the availability. defined as the actual power supply hours over demanded power supply hours excluding scheduled shutdown such as periodical inspection, during the commercial operation was 98.6%.The trial operation of the M 701 G was conducted in October 1998 in the domestic utility company. After completion of plant tests, the commercial operation was started in July 1999. The availability during commercial operation is 100%.This paper describes the technical features and up-to-date operating status of the M 501 G combined cycle power plant in MHI Takasago.