Intermittent renewable generation and maintaining power system reliability

There have been attempts, using various approaches, to assess the additional cost of running an electricity system when intermittent renewable generation is used to provide a significant proportion of the energy. The key issues are the difference, in statistical terms, between the resource availability of the intermittent source and conventional generation and the contribution the intermittent source can make to meet the system peak demand while maintaining system reliability. There is considerable agreement over the capacity credits that can be attributed to renewable energy sources, that is the amount of conventional capacity that renewables can reliably displace, yet the implications for costs have proved more controversial. Approaches to calculate changes in overall system cost are examined and an expression for the additional cost that intermittent generation imposes on a system that is attributable to its intermittent nature is identified. Further, it is shown that this expression can be reconciled with approaches that look at intermittent renewables on a stand-alone basis and factor in the additional costs of 'standby' capacity. It is shown that the main source of divergence between estimates of the cost of intermittency is the load factor implicitly assumed for the conventional plant used as a reference. There is only one consistent way to impute the costs of intermittency when the unit cost of intermittent plant is being compared with that of baseload generation plant.     

Partner selection model for design chain collaboration

Due to increasing global competition and shorter new product life cycles, brand owners collaborate more often with design chain partners to bring a new product to market. This paper proposes a design partner selection model to minimise the overall design chain cost, taking into account communication cost, time-to-market, and quality. The model can be formulated as a stagecoach problem. Next, a dynamic programming algorithm is developed for this model to select the optimal partners through the design chain. Finally, a numerical example and a sensitivity analysis are presented. The results also reveal that design quality and manufacturing quality positively influence the total cost, and when brand owners need to speed up time-to-market to keep up with a competitor, the design quality will become less important.     

Energy transition toward carbon-neutrality in China: Pathways,implications and uncertainties

Achieving carbon neutrality in China before 2060 requires a radical energy transition. To identify the possible transition pathways of China’s energy system, this study presents a scenario-based assessment using the Low Emissions Analysis Platform (LEAP) model. China could peak the carbon dioxide (CO₂) emissions before 2030 with current policies, while carbon neutrality entails a reduction of 7.8 Gt CO₂ in emissions in 2060 and requires an energy system overhaul. The assessment of the relationship between the energy transition and energy return on investment (EROI) reveals that energy transition may decrease the EROI, which would trigger increased energy investment, energy demand, and emissions. Uncertainty analysis further shows that the slow renewable energy integration policies and carbon capture and storage (CCS) penetration pace could hinder the emission mitigation, and the possible fossil fuel shortage calls for a much rapid proliferation of wind and solar power. Results suggest a continuation of the current preferential policies for renewables and further research and development on deployment of CCS. The results also indicate the need for backup capacities to enhance the energy security during the transition.     

Life cycle assessment and optimization of an iron making system with a combined cycle power plant: a case study from China

In the steel industry, the iron making system deals with large quantities of materials and energy and so it can play a critical role in reducing emissions and production costs. More specifically, excess by-product gases should be used for electricity generation; otherwise, they lead to pollution. A life cycle analysis is performed to compare the environmental impact of an iron making system with a combined cycle power plant (CCPP), to a system producing the same amount of electricity in a coal power plant. The results for a Chinese steel plant show a 33% reduction in the energy conservation and emission reduction potential for the CCPP system, which is thus more environmentally friendly. A mathematical programming formulation is then proposed for optimal scheduling. It incorporates key technological constraints and is sensitive to hourly changing electricity prices. The outcome is a 19% increase in revenue from electricity sales compared to a schedule that does not dynamically adjust to the price profile. The results also show that emissions from by-product gases can be avoided completely. The paper ends with a sensitivity analysis to evaluate the impact of changes in product demand, gas storage and CCPP capacity, and emission cost.     

Decision analysis of multi-pollutant control strategy for coal-fired power plant in Malaysia

The promulgation of Environmental Quality (Clean Air) Regulations 2014 on emissions from coal-fired power plants in Malaysia has prompted power plant operators to adopt emission control strategy that complies with the new emission limits. Currently, various emission control strategies are available to achieve the desired emission level. Each strategy offers unique advantages and disadvantages, depending on the objective of emissions control, process nature, and constraints on the resources incurred. To address this challenge, a proper decision-making analysis needs to be performed. In this paper, a systematic decision analysis methodology is proposed to select the most effective multi-pollutant control strategy that is compatible for coal-fired power plants in Malaysia. The methodology includes: (1) identification of pollutant emission from the plant under study and comparison with the stipulated emission limits, (2) establishment of emission factors, (3) selection of multi-pollutant control strategy, (4) identification of emission reduction factor for the pollutants and control technologies of interest, (5) determination of emission level from the selected multi-pollutant control strategy, and (6) prediction of ground-level concentration of pollutants. The decision analysis methodology is applied to a real case study of coal-fired power plant in Malaysia, which also currently faces a dilemma to comply with the additional and more stringent emission limits stipulated in the Environmental Quality (Clean Air) Regulations 2014. The proposed method is applicable for both the process concept under the design phase as well as the existing process plant.     

Differential evolution algorithm for static and multistage transmission expansion planning

A novel differential evolution algorithm (DEA) is applied directly to the DC power flow-based model in order to efficiently solve the problems of static and multistage transmission expansion planning (TEP). The purpose of TEP is to minimise the transmission investment cost associated with the technical operation and economical constraints. Mathematically, long-term TEP using the DC model is a mixed integer nonlinear programming problem that is difficult to solve for large-scale real-world transmission networks. In addition, the static TEP problem is considered both with and without the resizing of power generation in this research. The efficiency of the proposed method is initially demonstrated via the analysis of low, medium and high complexity transmission network test cases. The analysis is performed within the mathematical programming environment of MATLAB using both DEA and conventional genetic algorithm and a detailed comparative study is presented.     

Energy,exergy, environment and economic analyses and optimization of two-stage absorption–compression combined refrigeration system

In the present paper, integration of a two-stage absorption refrigeration system with a compression refrigeration system is proposed for utilizing low-temperature heat and reducing electric energy consumption. The proposed system is analyzed and compared with vapor compression system from the viewpoint of energy, exergy, environment and economics. The proposed system reduces the electricity consumption by 89.3% and CO₂ emission from 112.6 to 12.1 ton/year. The size and cost of the system are determined by designing the heat exchangers. The optimization is also performed with the objective of minimizing the annual cost of plant operation which includes fuel exergy cost, initial investment and maintenance cost and environmental damage cost due to CO₂ emission. The annual cost of its operation is 21.6% less than equivalent vapor compression refrigeration system which is further reduced by 18.2% through system optimization.     

Managing information and supplies inventory operations in a manufacturing environment. Part 1: An action research study

In the first part of this research study, we describe the application of the action research method in the nuclear fuel manufacturing industry to process information and to develop a lean operating supplies inventory program. The motivation for our work stems from the interaction we had with AREVA Richland, the nuclear reactor fuel production site located in the state of Washington to investigate the important role that information processing and maintenance inventory play in keeping the production process functioning on schedule. AREVA's data systems are not well documented. Hence, designing a methodology to obtain good data and perform any validity checks was critical for the company. Additionally, the importance of meeting delivery schedules to nuclear power plants throughout the world cannot be overestimated. Late deliveries of fuel can easily destroy the precise schedules for power plant outages designed to minimise plant downtime and maximise electric power output. Therefore, AREVA cannot tolerate significant production schedule deviations. Maintenance items play a key role in ensuring that production schedules are met. AREVA has about $700,000 tied up in maintenance inventory at their Washington state plant. Hence driving this investment down, while maintaining a high fill-rate, is crucial. Through the deployment of process maps, failure mode effect analysis and cause-and-effect diagram, we managed an action research project that helped process information flow along the company's supply chain and generated a 27% reduction in inventory relative to the system that was currently in place at AREVA.     

Assessment of bioenergy production from mid-rotation thinning of hardwood plantation: life cycle assessment and cost analysis

Forestry thinning logs, a low-value by-product of the forestry industry, present an opportunity for bioenergy production. It can be converted into solid, liquid, and gaseous fuels via different conversion techniques. Comparative life cycle assessment and life cycle costing (LCC) analysis were conducted to evaluate six options: woodchip gasification for power generation; wood pellets gasification in combined heat and power plant; wood pellet combustion for domestic water and space heating; pyrolysis for power generation; pyrolysis with bio-oil upgrading to transportation fuels; and ethanol production for transportation fuel mix. The functional unit used in this study was the treatment of 1 Mg of biomass. Global warming; acidification; eutrophication; fossil depletion, human toxicity; and land use impact categories were considered. The LCC also included greenhouse gas (GHG) emissions costs. The effects of uncertainties in the system on the overall performance of the scenarios were also evaluated. The results showed that all options except for ethanol production are GHG emission negative. Woodchips gasification performed best in all environmental impact categories and had the lowest LCC ($177.6/Mg). Biomass drying consumed more than 50% of the energy requirement for all options except for production of liquid transportation fuels via upgrading of pyrolytic oil, in which case the fuel upgrading process was the most energy intensive. In terms of energy return, all options, except electricity production through pyrolysis, offered positive return. The results highlight the importance of using biomass with least possible processing in order to maximise environmental and energy return and minimise LCC.     

基于碳排放权交易的发电用煤价格模型

2017年12月我国正式下发《全国碳排放权交易市场建设方案（发电行业）》,发电企业率先开展全国碳排放权交易,碳排放权交易价格将显著影响发电企业的燃料总成本。通过分析国内主要碳排放权交易市场现状、核算燃煤发电企业碳排放量以及分析现有煤炭交易价格变化,探讨了典型煤炭平仓价格模型,建立了燃煤发电企业在碳排放权交易约束条件下的煤炭平仓价格主要模型。碳成本占燃料成本约20%,新模型综合考虑碳排放权交易的需求,为燃煤发电企业完善燃料采购策略和抵御碳排放权交易风险提供了新的核算方法。     

电厂宽负荷运行下蒸汽喷射器对低温多效蒸馏系统的影响

淡水资源匮乏问题日益严重,火电厂耦合低温多效蒸馏（low-temperature multi-effect distillation,LT-MED）海水淡化技术因可有效降低制水成本而被广泛利用。利用Ebsilon软件对某电厂和低温多效蒸馏海水淡化耦合系统进行建模,分析了电厂宽负荷下蒸汽喷射器对水电联产系统热经济性的影响规律。研究结果表明：基于单级蒸汽喷射器的水电联产系统,以电厂75% THA工况设计下的蒸汽喷射器的性能最佳。对于带两级蒸汽喷射器的水电联产系统,当电厂负荷在75% THA工况时系统的制水电耗量相比单级蒸汽喷射器系统降低了13.65%,并且电厂负荷在50% THA工况以上时,带两级蒸汽喷射器系统的制水电耗量较单级蒸汽喷射器系统的低。     

超临界循环流化床机组全负荷段深度调峰方法研究

随着新能源发电装机容量不断扩大,火力发电市场受到严重挤压,为了满足电网深度调峰的需求,火电厂需要承担起深度调峰的重任,循环流化床机组可以采用停炉不停机的方式参与深度调峰。以山西某电厂超临界350 MW循环流化床机组为研究对象,分析了超临界循环流化床机组2种典型汽水系统全负荷段深度调峰方法,对其中的操作要点进行了详细的阐述,并就操作过程中需要特别关注的问题进行了分析,也提出了相应的防控措施。分析表明:超临界循环流化床机组可以采用2种典型汽水系统实现全负荷段深度调峰;加装炉水循环泵系统投资大、操作复杂,增设贮水箱到除氧器管路投资小、操作简单,但是加装炉水循环泵系统参与全负荷段调峰时,各系统稳定性较好。     

Thermoeconomic evaluation and optimization of an aqua-ammonia vapour-absorption refrigeration system

In this paper, the thermoeconomic concept is applied to the optimization of an aqua-ammonia vapour-absorption refrigeration (VAR) system—aimed at minimizing its overall product cost. The thermoeconomic concept based simplified cost minimization methodology calculates the economic costs of all the internal flows and products of the system by formulating thermoeconomic cost balances. The system is then thermoeconomically evaluated to identify the effects of design variables on costs and thereby enables to suggest values of design variables that would make the overall system cost-effective. Based on these suggestions, the optimization of the system is carried out through an iterative procedure. The results show a significant improvement in the system performance without any additional investment. Finally, sensitivity analysis is carried out to study the effect of the changes in fuel cost to the system parameters.     

Impacts of collaborative investment and inspection policies on the integrated inventory model with defective items

For an imperfect production system, to reduce quality-related costs, a manager may consider investing capital in quality improvement. In general, the investment expense in reducing the defective rate of items is often paid by the vendor. On the other hand, the buyer may inspect the product quality as the order is received which implies it incurs an inspection cost. In a supply chain integrated system, to accomplish global optimisation, the vendor and buyer can agree to jointly invest capital to improve the imperfect production processes, and the buyer can remove the inspection programme as the defective rate reaches a certain low-level. Hence, this paper investigates the impacts of collaborative investment and inspection policies on an integrated inventory model with defective items. The objective of this study is to seek the optimal order quantity, shipping times from the vendor to the buyer per production run, and the defective rate that minimise the joint total cost per unit time. An algorithm is developed to find the optimal solution. Several numerical examples are presented to demonstrate the proposed model and solution procedure, and then several management insights are obtained from the numerical examples.     

Impact of the use-based maintenance policy on the performance of cellular manufacturing systems

In this paper, a multi-objective integer programming approach is developed to investigate the impact of the use-based preventive maintenance (UPM) policy on the performance of the cellular manufacturing system (CMS). Under the UPM policy a maintenance schedule is established which provides for the performance of preventive maintenance (PM) only after a predetermined number of operating hours of machine use. This research indicates how PM and failure repair (FR) actions affect the effective availability of the machines and accordingly the machine and inter/intra-cell material handling costs under the UPM policy. The objective is to minimise the machine cost, inter- and intra-cell material handling and PM/FR costs. The proposed model is solved by an interactive fuzzy programming (IFP) approach to determine the best compromise solution from the decision maker point of view. IFP assumes that each objective function has a fuzzy goal and focuses on minimising the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. Compromise solutions are prioritised by two efficiency criteria, i.e. grouping efficiency and system availability. The performance of the proposed model is verified by a comprehensive numerical example.     

An analysis of warehouse and distribution strategies

We consider a case where seven retailers, all belonging to the same organization, order independently from the manufacturer. The organization wants to evaluate the advantage of creating a centralized warehouse facility. However, the investment costs for such a warehouse are considerable and the organization is thus cautious that any cost savings must outweigh the investment cost. The multi-echelon inventory control literature does not indicate when a centralized warehouse is clearly the best option. However, there is evidence that a centralized warehouse may be advantageous for low demand items which are expensive, as opposed to inexpensive fast moving items. Also the costs of the additional warehouse (i.e., capital investment and operating costs) play an important role. Hence, whether or not a warehouse can reduce overall cost depends heavily on the additional cost of the centralized warehouse. In order to keep the investment cost low we consider an alternative to the centralized warehouse, called virtual centralized warehousing. In the latter system no additional investment costs are necessary (i.e., the existing retailers have excess capacity at their current facilities) and the benefits of central warehousing are achieved.     

Age replacement policy in the case of no data: the effect of Weibull parameter estimation

Age replacement is a common maintenance policy when wear-out failures occur, and it is characterised by periodic replacement of components. Data on time to failure (TTF), often modelled with the Weibull function, are necessary for estimating optimal replacement intervals to minimise the total maintenance costs. In many cases, such as new components, new machines or new installations, no TTF data are available, so the Weibull parameters and optimal replacement interval cannot be estimated. To overcome this problem, these parameters can be assessed from the experience of the maintenance engineers and technicians. The aim of this study is investigating the relationship between the error in parameter estimation and additional maintenance costs related to this error. Analysis of variance (ANOVA) and multifactorial analysis are carried out for investigating the influence of these estimations on the final costs. Economic decision maps are introduced for supporting maintenance engineering in defining the maintenance policy with minimal additional cost in the case of no data being available. The analysis shows that, when no data are available, the application of the age replacement policy can result in a global saving of more than 50% compared with corrective maintenance.     

Application of genetic algorithm for reliability allocation in nuclear power plants

Reliability allocation is an optimization process of minimizing the total plant costs subject to the overall plant safety goal constraints. Reliability allocation was applied to determine the reliability characteristics of reactor systems, subsystems, major components and plant procedures that are consistent with a set of top-level performance goals; the core melt frequency, acute fatalities and latent fatalities. Reliability allocation can be performed to improve the design, operation and safety of new and/or existing nuclear power plants. Reliability allocation is a kind of a difficult multi-objective optimization problem as well as a global optimization problem. The genetic algorithm, known as one of the most powerful tools for most optimization problems, is applied to the reliability allocation problem of a typical pressurized water reactor in this article. One of the main problems of reliability allocation is defining realistic objective functions. Hence, in order to optimize the reliability of the system, the cost for improving and/or degrading the reliability of the system should be included in the reliability allocation process. We used techniques derived from the value impact analysis to define the realistic objective function in this article.     

Rethinking investment planning and optimizing net zero emission buildings

Increased awareness of climate change has precipitated more stringent mitigation targets. Public sector institutions in Canada are committed to becoming carbon neutral to attain a leadership position in climate change mitigation-related initiatives. Recent statistics reveal that buildings account for the majority of the corporate carbon footprint of public sector institutions. Hence, there is an increasing interest towards developing net zero energy and net zero emission buildings to comply with climate action targets. With limited financial resources, public sector institutions must optimize investments into building energy retrofits by considering lifecycle cost (LCC), overall energy performance, and related greenhouse gas (GHG) emission. The aim of this paper is to develop an investment planning approach for net zero emission buildings (NZEB). First, an investment planning approach for NZEB is proposed. A typical recreational centre building in British Columbia, Canada, was used as the archetype to demonstrate the concept. Second, innovative and proven building energy retrofits were analysed using energy simulation software to assess the impact on energy consumption reduction, GHG emissions, and LCC. Third, impacts of geographical location, tariff regimes, and grid emission factors on energy retrofits were studied by locating the same building in other provinces of Canada. This study revealed that net zero energy investment has a strong correlation to the grid emission factor. The proposed approach in this paper will assist building managers and owners in retrofitting and budget planning.     

SMV model-based safety analysis of software requirements

Fault tree analysis (FTA) is one of the most frequently applied safety analysis techniques when developing safety-critical industrial systems such as software-based emergency shutdown systems of nuclear power plants and has been used for safety analysis of software requirements in the nuclear industry. However, the conventional method for safety analysis of software requirements has several problems in terms of correctness and efficiency; the fault tree generated from natural language specifications may contain flaws or errors while the manual work of safety verification is very labor-intensive and time-consuming. In this paper, we propose a new approach to resolve problems of the conventional method; we generate a fault tree from a symbolic model verifier (SMV) model, not from natural language specifications, and verify safety properties automatically, not manually, by a model checker SMV. To demonstrate the feasibility of this approach, we applied it to shutdown system 2 (SDS2) of Wolsong nuclear power plant (NPP). In spite of subtle ambiguities present in the approach, the results of this case study demonstrate its overall feasibility and effectiveness.