多目标灰色关联度决策模型分析

本文针对多目标决策的复杂性,运用灰色系统分析方法和物元分析理论,建立了决策方案的评价体系并对评价指标进行规范化处理。以决策方案的灰色关联度作为评判准则,建立了一种目标灰色关联度决策模型。     

基于遗传算法的可持续土地利用动态规划

在建立和求解多目标可持续土地利用动态规划模型过程中,采用遗传算法并结合多目标模糊优选理论处理多目标土地利用结构优化问题。其详细步骤为：在分析区域特征基础上构建时间序列;通过现状分析设置土地利用类型决策变量,确定优化目标和约束条件,构建土地利用结构多目标优化模型;用灰色GM(1,1)预测模型对土地利用结构优化多目标模型参数进行预测;用遗传算法多目标优化方法对土地利用结构优化模型求解得pareto解集;最后运用多目标模糊优选动态规划方法对规划期内各时间段的pareto解集进行模糊动态优选,以最大优属度判定原则确定出最优决策序列。自贡市的实例表明,该方法有助于解决多目标协调问题,并通过提供多方案选择性,从而使规划更具灵活性,同时又便于充分吸纳公众参与,减少规划中的不确定性,增加规划的科学性、现实性和可操作性。     

基于灾害风险评估的山地城市固定避难场所布局优化研究——以东川区为例

研究以各区域灾害风险评估系数作为权重系数,对山地小城市各区域避难场所进行优化布局。首先,通过风险值=危险性*脆弱性/抗灾救灾能力机理表达式构建灾害风险评估指标体系,并以模糊综合评价法得出灾害风险评估数值,在此基础上通过多目标选址优化模型来构建山地城市避难场所的优化模型,其中灾害风险评估系数作为影响布局的权重因素纳入其中。最后,以东川区为研究对象,对其固定避难场所进行优化布局研究,结果表明:东川区城区固定避灾场所数量可在接近最优解的情况下达到效果最优。     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

多目标规划在产业结构优化中的应用——以秦皇岛市为例

秦皇岛是缺水城市，水资源短缺已成为制约经济发展的瓶颈。合理利用水资源对经济发展意义重大。本文采用多目标规划方法，构建了秦皇岛市水资源约束条件下的产业结构优化模型，提出了秦皇岛市产业结构优化方案。     

Integrated model for renewable energy planning in Turkey

All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements.     

碳中和趋势下数学模拟在污水处理系统中的发展与综合应用

数学模拟技术在污水处理方面被广泛应用,为了系统总结相关技术,本文回顾了污水处理系统中数学模拟技术的发展历程;综述了活性污泥模型(ASM)与机器学习(ML)在水质预测及参数工况优化领域中的应用;重点探究了污水处理系统中温室气体排放模型,以及多目标优化模型在污水处理系统中温室气体排放(GHG)、出水质量(EQI)和运行成本(OCI)的权衡问题;归纳了数学模拟技术在实现污水厂能量自给与资源回收的应用发展.研究结果表明数学模拟技术能准确预测出水水质、快速优化工艺参数、权衡温室气体排放、出水水质与运行成本之间的关系、以及提高资源回收效率等.因此,数值模拟技术可有效指导污水处理工艺的运行优化以及管理,为污水处理行业减污降碳协同增效提供技术支撑.     

基于不同电力需求的中国减污降碳协同增效路径

当前我国同时面临改善生态环境质量和实现碳达峰碳中和两大战略任务,协同推进减污降碳已成为我国经济社会发展全面绿色转型的必然选择,电力部门在转型过程中将发挥重要作用.面向不同的电力需求情景,构建低成本实现碳达峰、碳中和的多目标模型,求解得出减污降碳协同增效最优路径方案.结果表明,在如期实现碳达峰、碳中和目标的前提下,减污和降碳协同性较好,两者协同控制可高效助力低碳转型的实现;优化电力部门发电结构是实现减污降碳协同增效的关键措施,研究期火电占比不断下降,清洁电力占比超过92.5%;不同电力需求下二氧化碳和主要大气污染物排放量有明显差异,其中二氧化碳排放量受电力需求影响最大,低电力需求、中等电力需求和高电力需求情景下峰值二氧化碳排放量分别为94.16亿、 104.09亿和107.46亿t,主要污染物二氧化硫、氮氧化物和颗粒物的排放同样表现出在低电力需求、中等电力需求和高电力需求情景下依次递增的趋势.电力需求的提高仅增加了电力部门内部发电结构调整的压力,未影响到其他部门的产量和活动水平,即电力需求导致的电力部门减排压力未表现出部门间传递的趋势.     

Using many-objective trade-off analysis to help dams promote economic development,protect the poor and enhance ecological health

Allocating water to different uses implies trading off the benefits perceived by different sectors. This paper demonstrates how visualising the trade-offs implied by the best performing water management options helps balance water use benefits and find sustainable solutions. The approach consists of linking a water resources model that can simulate many management policies and track diverse measures of system performance, to a many-objective evolutionary optimisation algorithm. This generates the set of Pareto-optimal management alternatives for several simultaneous objectives. The relative performance of these efficient management alternatives is then visualised as trade-off curves or surfaces using visual analytic plots. Visually assessing trade-offs between benefits helps select policies that achieve a decision-maker-selected balance between different metrics of system performance. We apply this approach to a multi-reservoir water resource system in Brazil's semi-arid Jaguaribe basin where current water allocation procedures favour sectors with greater political power and technical knowledge. The case study identifies promising reservoir operating policies by exploring trade-offs between economic, ecological and livelihood benefits as well as traditional hydropower generation, irrigation and water supply. Results show optimised policies can increase allocations to downstream uses while increasing median land availability for the poorest farmers by 25%.     

Increasing the microbial activity in activated sludge by the phenomenon of 'biological resonance

Mechanical oscillations as well as electrical oscillations (e.g. in an electrical oscillatory circuit) can lead to resonance conditions by external agitation with the natural frequency of the system. During the microbial protein synthesis, the induction and repression mechanisms also cause oscillations in the form of varying protein concentrations. The aim of this work concentrates on an induced resonance case of the biological system, comparable with physical resonance phenomena, by external periodic stimulations. For this, system theoretical computer simulations with a structured genetic model were carried out, which built the theoretical fundament for describing the effect of 'Biological Resonance'. Based on that, lab-scale experiments using a mixed microbial culture (activated sludge) and skimmed milk as an inducing substrate revealed an enhanced microbial productivity of around 60%-75% compared to values of the productivity under steady-state conditions in a narrow range of process parameters. The optimum (resonance case) was confirmed by a repetition of the variation experiments and is characterised by a substrate supply period of approx. 18 min and a following starvation period of about 9 min. Long-term investigations under optimised process conditions indicate adaptation mechanisms of the microorganisms to evade the imposed stress conditions. The productivity will not remain constant without additional stimulation and declines to its original level. However, temporal modulation of the starvation period permanently increases the productivity (elevated catabolism) to about 60%, which was observed over a period of several weeks.