Biomass gasification in district heating systems – The effect of economic energy policies

Biomass gasification is considered a key technology in reaching targets for renewable energy and CO₂ emissions reduction. This study evaluates policy instruments affecting the profitability of biomass gasification applications integrated in a Swedish district heating (DH) system for the medium-term future (around year 2025). Two polygeneration applications based on gasification technology are considered in this paper: (1) a biorefinery plant co-producing synthetic natural gas (SNG) and district heat; (2) a combined heat and power (CHP) plant using integrated gasification combined cycle technology. Using an optimisation model we identify the levels of policy support, here assumed to be in the form of tradable certificates, required to make biofuel production competitive to biomass based electricity generation under various energy market conditions. Similarly, the tradable green electricity certificate levels necessary to make gasification based electricity generation competitive to conventional steam cycle technology, are identified. The results show that in order for investment in the SNG biorefinery to be competitive to investment in electricity production in the DH system, biofuel certificates in the range of 24–42 EUR/MWh are needed. Electricity certificates are not a prerequisite for investment in gasification based CHP to be competitive to investment in conventional steam cycle CHP, given sufficiently high electricity prices. While the required biofuel policy support is relatively insensitive to variations in capital cost, the required electricity certificates show high sensitivity to variations in investment costs. It is concluded that the large capital commitment and strong dependency on policy instruments makes it necessary that DH suppliers believe in the long-sightedness of future support policies, in order for investments in large-scale biomass gasification in DH systems to be realised.     

Time-dependent opportunities in energy business: A comparative study of locally available renewable and conventional fuels

This work investigates and compares energy-related, private business strategies, potentially interesting for investors willing to exploit either local biomass sources or strategic conventional fuels. Two distinct fuels and related power-production technologies are compared as a case study, in terms of economic efficiency: the biomass of cotton stalks and the natural gas. The carbon capture and storage option are also investigated for power plants based on both fuel types. The model used in this study investigates important economic aspects using a “real options” method instead of traditional Discounted Cash Flow techniques, as it might handle in a more effective way the problems arising from the stochastic nature of significant cash flow contributors’ evolution like electricity, fuel and CO₂ allowance prices. The capital costs have also a functional relationship with time, thus providing an additional reason for implementing “real options” as well as the learning-curves technique. The methodology as well as the results presented in this work, may lead to interesting conclusions and affect potential private investment strategies and future decision making. This study indicates that both technologies lead to positive investment yields, with the natural gas being more profitable for the case study examined, while the carbon capture and storage does not seem to be cost efficient with the current CO₂ allowance prices. Furthermore, low interest rates might encourage potential investors to wait before actualising their business plans while higher interest rates favor immediate investment decisions.     

Solving the blocking flow shop scheduling problem with makespan using a modified fruit fly optimisation algorithm

The flow shop scheduling problem with blocking has important applications in a variety of industrial systems but is under-represented in the research literature. In this paper, a modified fruit fly optimisation (MFFO) algorithm is proposed to solve the above scheduling problem for makespan minimisation. The MFFO algorithm mainly contains three key operators. One is related to the initialisation scheme in which a problem-specific heuristic is adopted to generate an initial fruit fly swarm location with high quality. The second is concerned with the smell-based search in which a neighbourhood strategy is designed to generate a new location. To further enhance the exploitation of the proposed algorithm considered, a speed-up insert-neighbourhood-based local search is applied with a probability. Finally, the last is for the vision-based search in which an update criterion is proposed to induce the fruit fly into a better searching space. The simulation experimental results demonstrated the efficiency of the proposed algorithm, in spite of its simple structure, in comparison with a state-of-the-art algorithm. Moreover, new best solutions for Taillard’s instances are reported for this problem, which can be used as a basis of comparison in future studies.     

求解有限缓冲区流水线调度问题的混合蝙蝠算法

针对最小化最大完成时间的有限缓冲区流水线调度问题(LBPFSP),提出一种混合蝙蝠算法(HBA)。在算法设计中,采用基于SPV的编码规则以实现连续的实数向离散的作业序列的转变,在种群初始化时引入NEH启发式算法,为提高算法的搜索效率,以一定的概率执行基于Pairwise的邻域搜索。对标准测试问题在不同缓冲区下的最优值进行仿真并与其他算法进行对比,并对基于Pairwise的邻域搜索的执行概率值对算法性能的影响进行讨论,其结果验证了HBA求解LBPFSP的有效性。     

A framework for designing robust supply chains considering product development issues

The primary objective of the design for supply chain (DFSC) is the selection of an appropriate product family. Moreover, it deals with the selection of the optimal combination among the different conflicting criteria while making a trade-off between the supply chain cost, sales profit and the product design complexities. In this research, to address the DFSC issues a product platform approach has been proposed which amalgamates the component modularity as well as the function modularity in the product design. The optimisation model proposed in this paper for the product development and the supply chain design is based on a generic bill of materials (GBOM) representation. The complete framework includes vital decision-making needed for designing a robust supply chain such as locating plants to alleviate the likely dominance of production cost and market mediation cost on product variety and imparting process flexibility of the located plants. The optimisation model proposed in this paper, models the supply chain cost, sales profit and product design complexity as three criteria that altogether determine the robustness of the supply chain and the underlying product development approach. Certain parameters like process flexibility, flow types and drivers of the product variety dominance have been controlled in the design framework. To resolve the complexity of the proposed model a genetic algorithm (GA) technique has been proposed. The proposed GA adopts an arithmetic crossover, a dynamic mutation and a variable penalty strategy to produce optimal results in a very short computational time. To validate the proposed model, a simulated case study of the wiring harness supplier of an AGV manufacturer has been studied.     

A three-dimensional slope stability analysis method using the upper bound theorem Part II: numerical approaches, applications and extensions

The second part of this paper provides the numerical procedures that implement the three-dimensional upper-bound slope stability analysis method described in Part I. A three-dimensional failure surface is generated by elliptical lines based on the slip surface in the neutral plane and extended in the z direction. This failure surface is mathematically represented by a series of variables including the co-ordinates of the nodal points that define the slip surface at the neutral plane, the inclinations of the row-to-row interfaces and the coefficients that define the ratio of the long axis over the low one of the elliptic. A method of optimisation is followed in order to find a set of these variables that offers the minimum factor of safety. A computer program EMU-3D is coded to perform the calculation for practical problems. Applications and extensions of the method presented in this paper include a case study of the Tianshenqiao Landslide, the stability analysis of the right abutment of the Xiaowan arch dam, and the portal of the Hongjiadu hydropower project.     

A techno-economic analysis of biodiesel biorefineries: Assessment of integrated designs for the co-production of fuels and chemicals

In this work we explore the concept of integrated biorefineries, and we examine alternative schemes for the co-production of biofuels (biodiesel) and chemicals (succinic acid). Four different biorefinery schemes considering the different uses of crude glycerine from the biodiesel process are simulated and compared: (i) the disposal of crude glycerine as a waste, (ii) the purification (through distillation) of crude glycerine to 80%, (iii) the purification of glycerine to 95%. and (iv) the production of succinic acid from glycerine through fermentation. For the latter, we consider the bioprocess that converts the glycerol to succinate, and a downstream separation process that purifies and crystallises our product to the final succinic acid crystals. To apply complex kinetics for the fermentation we have linked Aspen Plus (2006.5) with Matlab (R2007b), where we have used the experimentally-based unstructured model from Vlysidis et al., 2009 and 2010. We first determine the operating parameters of the fermentor that have a significant effect on the economics of this scenario, i.e. the cycle time of the batch fermentation and the water flowrate entering the bioreactor. Subsequently, we perform single- and multi-objective optimisation to maximise the profit and/or to minimise the environmental impact of the overall process. We then analyse and compare the economics of the four different biorefinery schemes by using well-known profitability and/or emission criteria. Furthermore, we carry out sensitivity analysis that takes into consideration price variations for the most important materials and we extract firm conclusions about the profitability of each scenario. It is found that succinic acid co-production can enhance the profit of the overall biorefinery by 60% for a 20 years plant lifetime. These results indicate the importance of glycerol when it is utilised as a key renewable building block for the production of commodity chemicals.     

Optimization of constraint engineering problems using robust universal learning chimp optimization

Due to the challenging constraint search space of real-world engineering problems, a variation of the Chimp Optimization Algorithm (ChOA) called the Universal Learning Chimp Optimization Algorithm (ULChOA) is proposed in this paper, in which a unique learning method is applied to all previous best knowledge obtained by chimps (candid solutions) to update prey’s positions (best solution). This technique preserves the chimp’s variety, discouraging early convergence in multimodal optimization problems. Furthermore, ULChOA introduces a unique constraint management approach for dealing with the constraints in real-world constrained optimization issues. A total of fifteen commonly recognized multimodal functions, twelve real-world constrained optimization challenges, and ten IEEE CEC06-2019 suit tests are utilized to assess the ULChOA's performance. The results suggest that the ULChOA surpasses sixteen out of eighteen algorithms by an average Friedman rank of better than 78 percent for all 25 numerical functions and 12 engineering problems while outperforming jDE100 and DISHchain1e + 12 by 21% and 39%, respectively. According to Bonferroni-Dunn and Holm's tests, ULChOA is statistically superior to benchmark algorithms regarding test functions and engineering challenges. We believe that the ULChOA proposed here may be utilized to solve challenges requiring multimodal search spaces. Furthermore, ULChOA is more widely applicable to engineering applications than competitor benchmark algorithms.     

Multi-objective optimisation of batch separation processes

This paper considers for the first time the simultaneous multi-objective optimisation of design and operation of batch distillation as well as of batch hybrid distillation/pervaporation processes. The overall problem is formulated as a multi-objective mixed integer dynamic optimisation (MO-MIDO) problem. The optimisation strategy comprises of different ranking procedures that allow the determination of the Pareto optimal set. A case study for the separation of a homogeneous tangent-pinch (acetone–water) mixture is presented for a dual-criteria optimisation case of minimising capital investment while at the same time minimising the energy consumption rate during the batch. It is found that the proposed distance ranking procedure yields the best Pareto optimal set when compared to other non-dominated sorting procedures. Furthermore, the distance ranking procedure was found to be further improved when used with an elitism operator.     

—种枪械总体动态优化设计的新方法

针对枪械产品的设计复杂性，结合多个学科领域优化的特点，提出应用多学科优化设计方法(MDO)来设计和优化武器产品。首先归纳分析了MDO方法，给出其在枪械设计过程中的应用框架，在此基础上开发了应用平台。最后给出了一个机枪的四个子系统两级优化模型的算例。说明在该平台上应用MDO方法于机枪的总体优化设计是可行的。