基于多模型随机组合的水文集合预报方法研究

准确、可靠的水文预报是水资源开发利用的基础。集合预报以概率或区间的形式表征预报的不确定性,是未来水文预报研究的重点发展方向。本文提出了一种基于多模型随机组合的水文集合预报方法。首先通过加权形式将多种预报模型进行组合;再采用多目标优化算法率定各成员模型权重的上、下限;最后在优化的上、下限内随机生成权重以构建集合预报。以汉江黄金峡水库中长期径流预报为研究对象,考虑月、旬两种预见期,构建了六种单一预报模型,采用非支配排序遗传算法对权重进行优化后得到集合预报样本。结果表明：所提方法能更好地反映预报的不确定性,且均值预报结果明显优于贝叶斯模型平均法和单一确定性预报模型,具有一定竞争力。     

西江流域压咸风险调度及其时空传递规律研究

枯水期珠江河口咸潮情势日益加重,径流不确定加剧了压咸风险,严重威胁沿线的供水安全。本文基于概率密度分布描述径流不确定性,构建了单源风险调度基本框架。以西江流域五座水库为研究对象,量化了预报误差与压咸风险的响应关系;揭示了压咸风险的时空传递规律;将压咸风险划分为3个等级;确定出各级风险越级传递的临界阈值。研究表明：随预报误差的增大,压咸风险提前且持续天数增加、风险率增大;压咸风险呈逐时段累积和从上游向下游、从支流向干流的时空传递规律;当预报误差超过±16%、±21%时,压咸风险从轻险越级至中险、中险越级至重险。研究成果对于西江流域压咸风险的调控和粤港澳大湾区的供水安全具有重要的应用价值。     

基于恢复价值动态评估的配电网恢复控制决策

配电网停电后,停电场景、恢复进程和应急情况下的负荷职能等均会影响负荷恢复供电的紧急程度,通常根据待恢复对象自身的恢复价值静态设置其重要等级或重要度,这制约了有限恢复资源的精细化管理.为此,考虑冷负荷启动特性与负荷间职能耦合关系对负荷单位恢复价值的影响,考虑间歇性电源出力的可控性对电源恢复价值的影响,结合母线恢复为周边其他待恢复对象带来的潜在恢复价值,同时计及系统供电缺额、恢复代价和恢复操作的不确定性,提出了综合恢复收益、代价和风险的负荷及电源母线恢复价值动态评估方法.以此为基础,建立了配电网供电恢复多进程优化模型及分区并行恢复决策方法.最后,通过仿真分析验证了所提策略能够有效提高恢复资源的利用率.     

多类型源储协调互动的配电网分布鲁棒优化调度

分布式光伏、风电等可再生能源出力具有较强的随机性和不确定性,其大量并网给配电网的运行带来了极大的挑战。本文提出了一种多类型源储协调互动的配电网分布鲁棒优化调度方法,基于分布鲁棒优化理论,对配电网中传统离散设备、可再生能源以及储能决策进行协调优化,提高配电网运行的经济性和安全性,实现了配电网运行决策保守性与鲁棒性的有效平衡。首先,考虑多类型源储资源的协调互动,建立配电网优化调度模型,并将其转化为混合整数二阶锥规划的形式;其次,利用可再生能源出力场景集进行不确定性刻画,建立分布鲁棒优化模型,并通过列和约束生成算法进行求解;最后,在PG&E69节点系统上进行算例分析,验证了所提方法的可行性与准确性。     

考虑新能源消纳及需求响应不确定性的配电网主从博弈经济调度

针对当前配电网侧风电消纳率较低的问题,运用Stackelberg动态博弈理论,提出一种以配电网侧为主体、负荷侧为从体的主从博弈模型.通过分析用户负荷特性,建立用户负荷特性模型;运用三角模糊数描述需求响应的不确定性,建立价格型需求响应不确定性模型;以配电网侧配电网运行成本最小及风电消纳最大、负荷侧用户电费最低为目标建立配电网主从博弈经济模型,二者通过优化配电网侧的准实时电价策略集及负荷侧需求响应策略集达到博弈均衡;以修改后的IEEE 30节点系统为算例,采用改进型教与学优化算法求得该主从博弈模型的均衡解.算例仿真分析表明,所建模型能够有效提高配电网风电消纳能力,减少配电网运行成本和用户电费,实现主、从体双方社会效益与经济效益最优化.     

基于深度强化学习的光储充电站储能系统优化运行

优化储能充放电策略有利于提升光储充电站运行经济性,但是现有模型驱动的随机优化方法无法全面考虑储能系统的复杂运行特性以及光伏发电功率、电动汽车充电负荷的不确定性.因此,提出一种基于深度强化学习的光储充电站储能系统全寿命周期优化运行方法.首先对储能运行效率模型和容量衰减模型进行精细化建模.然后考虑电动汽车充电需求、光伏出力和电价的不确定性,在满足电动汽车充电需求和光伏消纳的条件下,以光储充电站收益最大化为目标,建立了基于强化学习的储能优化运行问题.考虑到储能充放电决策动作的连续性,采用双延迟深度确定性策略梯度算法进行求解.采用实际历史数据对模型进行训练,根据当前时段状态对储能充放电策略进行实时优化.最后,对所提方法及模型进行测试,并将所提出的方法与传统模型驱动方法进行对比,结果验证了所提方法及模型的有效性.     

SEBF/SLF系列重防腐涂料的特性和分析

本文介绍2种SEBF熔融结合环氧粉末涂料和2种SLF双组份液体涂料,辽宁的物理和化学性能及部分测试和评价方法.     

Regional mass flux balancing for controlling gentle soil remediation operations

Extraction of heavy metals by accumulating plants is a method which is currently in development for the "gentle" remediation of contaminated agricultural soils (phytoremediation, see [2]). Areal contaminant mass flux balances are basic criteria for the design of such remediations and their control. A framework for the integration of contaminant balances relating the field scale of remediation with the regional scale of soil monitoring networks is provided by the recently developed method PROTERRA [3]. The objective of the study presented in this paper was to test the suitability of PROTERRA for planning and monitoring gentle soil remediations. For this purpose we applied the PROTERRA method to the contaminated agricultural land in and around Dornach, Switzerland, to assess copper flux balances.The calculations showed that atmospheric deposition and the application of pesticides and manure are important pathways for the inputs of copper. The copper export with a special maize cultivar accumulating heavy metals would be about three times higher than the average metal export with crops. A moderate increase of sewage sludge application would lead to a substantial increase of the copper input. Decisions to remediate the soil should take the uncertainty of mass flux balances both on field scale as well as on regional scale into account. Therefore, an important need of further development of the PROTERRA method is the integration of uncertainty analysis on both scales.     

Comments on “Necessary and sufficient stability condition of fractional-order interval linear systems” [Automatica 44 (2008), 2985–2988]

This paper shows that the main thesis of the article “Necessary and sufficient stability condition of fractional-order interval linear systems” by Ahn and Chen (Automatica, vol. 44, pp. 2985–2988) is only a sufficient (and not a necessary) condition for the robust stability of fractional-order linear systems.     

Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.