Real-Time Modelling and Optimisation for Water and Energy Efficient Surface Irrigation

The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurised systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30% to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption. A balance between the improvement in water use and the potential increase in energy consumption is required. When surface water is used, pressurised irrigation systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation systems so their use should be carefully planned keeping in view adverse impact of carbon emissions on the environment and threat of increasing energy prices. With gravity-fed surface irrigation methods, the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimisation and gravity fed surface irrigation with real-time optimisation has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is equivalent to that given by pressurised systems. The real-time optimisation and control thus offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

DISPATCHING REAL-TIME MODEL OF COMPUTER-CONTROLLED TRUCK

In order to recover ore as much as possible, a computer-controlled truck real-time dispatching model is conducted under the conditions of Qidashan lron Mine. It can not only acquire the optimization of shovel and truck operation, but also satisfy requirements of blending ores.The simulation results indicate the effectiveness of the model developed.

Real-time Risk-averse Dispatch of an Integrated Electricity and Natural Gas System via Condi-tional Value-at-risk-based Lookup-table Ap-proximate Dynamic Programming

The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.

Development of a concentration method for detection of tobacco mosaic virus in irrigation water

Tobacco mosaic virus(TMV) causes significant yield loss in susceptible crops irrigated with contaminated water. However, detection of TMV in water is difficult owing to extremely low concentrations of the virus. Here, we developed a simple method for the detection and quantification of TMV in irrigation water. TMV was reliably detected at concentrations as low as 10 viral copies/μL with real-time PCR. The sensitivity of detection was further improved using polyethylene glycol 6000(PEG6000, MW 6000) to concentrate TMV from water samples. Among the 28 samples from Shaanxi Province examined with our method, 17 were tested positive after virus concentration. Infectivity of TMV in the original water sample as well as after concentration was confirmed using PCR. The limiting concentration of TMV in water to re-infect plants was determined as 102 viral copies/mL. The method developed in this study offers a novel approach to detect TMV in irrigation water, and may provide an effective tool to control crop infection.

TRUCK DISPATCHING CRITERIA AND THEIR APPLICATIONS

Along with the development of automatical truck dispatching in open pits, it is important to es-tablish general-gurpose criteria for truck dispatching optimization. The existing dispatching criteria are briefly introduced and optimal dispatching criteria for different haulage systems are recommended. Obvious economic results have been obtained from case studies applying the recommended dispatching criteria.

Segmented Real-time Dispatch Model and Stochastic Robust Optimization for Power-gas Integrated Systems with Wind Power Uncertainty

This paper develops a segmented real-time dispatch model for power-gas integrated systems(PGISs), where power-to-gas(P2G) devices and traditional automatic generation control units are cooperated to manage wind power uncertainty. To improve the economics of the real-time dispatch in regard to the current high operation cost of P2Gs, the wind power uncertainty set is divided into several segments, and a segmented linear decision rule is developed, which assigns adjustment tasks differently when wind power uncertainty falls into different segments. Thus, the P2G operation with high costs can be reduced in real-time adjustment. Besides, a novel segmented stochastic robust optimization is proposed to improve the efficiency and robustness of PGIS dispatch under wind power uncertainty, which minimizes the expected cost under the empirical wind power distribution and builds up the security constraints based on the robust optimization. The expected cost is formulated using a Nataf conversion-based multi-point estimate method, and the optimal number of estimate points is determined through sensitivity analysis. Furthermore, a difference-ofconvex optimization with a partial relaxation rule is developed to solve the non-convex dispatch problem in a sequential optimization framework. Numerical simulations in two testing cases validate the effectiveness of the proposed model and solving method.

Coupling real-time simulation of power supply,trains and dispatching for urban rail transit

In order to study the interaction among the traction power supply,the train group and the operation dispatching of urban rail transit,a coupling simulation system of power supply system,trains and dispatching management is constructed.In order to solve the problems of different timescales and difficult cooperation operation for related subsystems,a multi-bus distributed real-time network architecture based on hierarchical management of communication data is established,and simulation management software is developed to facilitate the free expansion of the simulation system.Meanwhile,the track line,train operation and other large timescale subsystems are realized by the pure digital simulation.And the time-sensitive subsystems,such as train traction system,braking system,auxiliary power supply system and network system etc.,are built by the semi-physical simulation.In this article,the system structure and the main implementation principle of each simulation subsystem are given in detail,and the system is tested and verified at the end.The results show that the simulation system can meet the expected requirements.

基于SHAP重要性排序和机器学习算法的灌区渠道调度流量预测

渠道泄水闸能够快速排除灌区入渠洪水,避免渠道漫顶。研究以淠史杭灌区灌口集泄水闸为例,以闸门调度流量为目标变量,以不同时段过去和未来降雨量、泄水闸闸上实时水位及其变化量为特征变量,比较8种机器学习算法的预测精度,同时采用shapley additive explanations(SHAP)法分析特征变量重要性。结果表明:1)集成学习算法预测评价指标优于传统回归算法,8种机器学习算法中随机森林回归(random forest regression,RFR)算法预测精度最高(训练集均方根误差、平均绝对误差、均方误差及决定系数分别为0.146 m^(3)/s、0.094 m^(3)/s、0.021 m^(3)/s、0.976;测试集分别为0.306 m^(3)/s、0.197 m^(3)/s、0.093 m^(3)/s、0.931);2)采用SHAP法确定的特征变量重要性排序表明灌口集泄水闸闸上水位对于泄水闸调度流量的预测结果影响最大,占特征重要性值总和的34.6%;3)以过去6 h降雨量、过去9 h降雨量、未来6 h降雨量、灌口集泄水闸闸上水位作为输入变量的RFR算法预测灌口集泄水闸调度流量效果最佳,训练集均方根误差、平均绝对误差、均方误差及决定系数分别为0.126 m^(3)/s、0.080 m^(3)/s、0.016 m^(3)/s、0.982;测试集分别为0.263 m^(3)/s、0.164 m^(3)/s、0.069 m^(3)/s、0.950,研究结果对灌区防洪调度决策具有重要参考价值。

灌区用水调度的知识图谱模型构建——以淠史杭灌区瓦西干渠灌域为例

【目的】人工智能技术以全新的自适应学习视角为灌区智慧化建设带来了异于传统的研究范式,迄今已有众多智能算法与技术应用于灌区用水调度决策研究中,但已有成果缺乏便利性和易操作性,无法真正落地。【方法】为此,本文通过对比分析人工智能技术中的随机森林和BP神经网络模型,发现融合SHAP(Shapley additive explanation,SHAP)方法的随机森林模型具有更优的灌区用水调度预测效果。在此基础上,基于历史实测数据将灌区用水调度变量划分为不同梯度,表征出9.82×10^(11)组用水调度场景样本,并采用预先训练的随机森林模型获得了各样本对应的调度流量预测值,由此形成了灌区用水调度场景与调度流量值之间映射关系的基础数据库,即在现有调度历史数据的基础上利用机器学习模型丰富和加密了调度场景,得到了能实现基本覆盖现实调度场景的调度场景库。基于该场景数据库,利用Neo4j图形库构建出淠史杭灌区用水调度流量预测值知识图谱模型。【结果】利用该图谱模型,灌区用水调度管理人员仅需确认目标调度场景中各调度变量在知识图谱模型中的近似梯度值,即可检索获得调度流量预测值。【结论】经应用验证表明,由该知识图谱模型获得的调度流量预测值误差在淠史杭灌区用水管理人员的经验认知范围内,且可实现调度流量值的实时检索。

漳河水库灌溉调度运用与效益分析

漳河水库位于湖北省江汉平原西北部,总库容21.13亿m^(3),是1座以农业灌溉为主,兼有防洪、城镇用水、发电供水、水产养殖、航运、旅游、生态补水等综合效益的大型水利工程。基于近20年水库管理单位精心调度,强化各项管理措施,精心调配水源,编制调度方案与应急预案,实行计划供水,充分利用信息化手段管水,注重用水计量,促进节约用水,保证了各部门的用水要求,充分发挥了水库抗御灾害和综合兴利的作用,取得了巨大的社会与经济效益。

A retroactive approach to microgrid real-time scheduling in quest of perfect dispatch solution

As an emerging paradigm in distributed power systems,microgrids provide promising solutions to local renewable energy generation and load demand satisfaction.However,the intermittency of renewables and temporal uncertainty in electrical load create great challenges to energy scheduling,especially for small-scale microgrids.Instead of deploying stochastic models to cope with such challenges,this paper presents a retroactive approach to real-time energy scheduling,which is prediction-independent and computationally efficient.Extensive case studies were conducted using 3-year-long real-life system data,and the results of simulations show that the cost difference between the proposed retroactive approach and perfect dispatch is less than 11%on average,which suggests better performance than model predictive control with the cost difference at 30%compared to the perfect dispatch.

Dynamic-decision-based Real-time Dispatch for Reducing Constraint Violations

This paper proposes a dynamic-decision-based realtime dispatch method to coordinate the economic objective with multiple types of security dispatch objectives while reducing constraint violations in the process of adjusting the system operation point to the optimum.In each decision moment,the following tasks are executed in turn:①locally linearizing the system model at the current operation point with the online model identification by using measurements;②narrowing down the gaps between unsatisfied security requirements and their security thresholds in order of priority;③minimizing the generation cost;④minimizing the security indicators within their security thresholds.Compared with the existing real-time dispatch strategies,the proposed method can adjust the deviations caused by unpredictable power flow fluctuations,avoid dispatch bias caused by model parameter errors,and reduce the constraint violations in the dispatch decision process.The effectiveness of the proposed method is verified with the IEEE 39-bus system.

Two-stage Correction Strategy-based Real-time Dispatch for Economic Operation of Microgrids

Given the different energy rates of multiple types of power generation units,different operation plans affect the economy of microgrids.Limited by load and power generation forecasting technologies,the economic superiority of day-ahead plans is unable to be fully utilized because of the fluctuation of loads and power sources.In this regard,a two-stage correction strategy-based real-time dispatch method for the economic operation of microgrids is proposed.Based on the optimal day-ahead economic operation plan,unbalanced power is validly allocated in two stages in terms of power increment and current power,which maintains the economy of the day-ahead plan.Further,for operating point offset during real-time correction,a rolling dispatch method is introduced to dynamically update the system operation plan.Finally,the results verify the effectiveness of the proposed method.

再生水灌区水资源联合调度研究

以北京市再生水灌区为研究对象,灌区再生水、地表水以及地下水的联合调度为研究内容,结合系统分析的思想,提出了再生水灌区水资源联合调度的数学模型。采用逐时段动态分析的方法,得出典型年北京市再生水灌区水资源的配置方案,其中特枯水年、枯水年、平水年和丰水年地下水开采量为21 626.08、14 616.39、11 928.83和7 262.05万m3,分别仅占全年总灌溉需水量的44.35%、37.61%、41.09%和34.04%。研究表明,通过联合调度有效缓解了灌区地下水过量开采的问题,同时提高了灌区的灌溉保证率,优化了供水结构,是一种科学可行的再生水灌区水资源联合调度方法。

灌区水资源实时优化调度

根据实时调度原理及农业水资源配置特点,建立了分层耦合的水资源实时优化调度模型,该模型包括供需水中长期预测、中长期优化配置、供需水实时预报、短期渠系配水和基于模糊识别的实时修正5个模块,应用该模型可实现对预报、决策、实施、修正的滚动向前调度。在中长期优化调度模块中提出了利用模糊聚类和马尔科夫时间序列的预测方法对有效降水量进行预测,并根据预测的年型计算作物需水量和地下水可开采量。实例计算表明,应用该模型实行的实时优化调度与各种供水已知情况下的理想最优调度方案偏差较小。

B/S模式实时灌溉调度系统框架设计

在水资源短缺问题加剧和农业用水不可能大幅度增加的大背景下,利用计算机技术在Internet平台上进行B/S模式实时灌溉调度系统框架的设计研究具有较强的现实意义。通过与C/S模式系统的比较,显示出B/S模式系统的优越性。系统包括9大功能模块,通过建立通用的系统模型,实现实时灌溉。

宝鸡峡灌区多水库优化调度研究

针对宝鸡峡灌区缺水现状,从充分利用水资源的角度出发,对宝鸡峡林家村枢纽工程和4个灌区水库、魏家堡渠首进行优化调度研究,通过优化配水,充分发挥蓄水工程的调蓄功能,使水资源的利用量最大。基于大系统分解协调技术中的目标规划法,用模拟技术生成子系统非劣解集,提出目标规划模拟方法,建立以供水量最大为目标的多水库供水系统目标规划模型,进行了灌区多水库优化调度计算,对结果进行了分析。

灌区多水库联合优化调度研究

针对调水量与调水时机不确定的问题,建立基于供水系统全局风险最小化的多水库联合模拟优化调度模型,采用并行多种群混合进化的粒子群算法(PMSE-PSO)全局优化确定满足各水库供水要求的水库群调水规则和供水规则,并优化确定调水水库的最大调水规模,最后根据优化规则及调水规模进行水库调度计算,进而求出各计算时段调水量以及各水库区用水户供水量。本模型从缺水区域风险最优化的角度,优化确定水库供水限制线、调水控制线和调水水库的最大调水规模,模拟各时段实际调水量和不同用水户供水优先次序的供水量,实现了多水库联合调度的技术突破,为水库调度决策部门提供了一个新的调度思路。通过高关-短港水库灌区的实例应用,证明了该模型的科学性和有效性。

位山灌区渠系泥沙淤积的主要问题与治理措施

根据实测资料,分析位山灌区渠系泥沙淤积问题。结果表明:西输沙渠尾沉沙池口淤高导致水面比降远小于设计比降是西输沙渠泥沙严重淤积的主要原因;西输沙渠的泥沙淤积主要是溯源淤积,由于入池水流不畅、出口处落差较小、日常引沙量较大导致泥沙淤积严重是造成西沉沙池淤沙容积严重不足的主要原因。建议改造输沙渠、优化灌区引水引沙调度方式、实现西沉沙池的动态调控,采用提水或扬水灌溉方式治理位山灌区的泥沙淤积问题。

灌区污水灌溉补偿效益初探

我国水资源紧缺,城市生活和工业大量挤占农业用水并产生大量污水,致使农业清水灌溉用水危机加重。在这种情况下,我国的污水灌溉面积随着城市化加快和工业发展而迅速扩大。为了研究灌区污水灌溉相关各方效益变化,通过把灌区污水灌溉运行与梯级库群中龙头水库运行相比较,分析结果表明灌区污水灌溉存在补偿效益。文章给出了灌区污水灌溉补偿效益的概念和内涵。接着,进一步指出灌区污灌补偿效益相关研究内容,包括灌区污灌补偿相关对象分析、相关对象的效益变化研究和灌区多水源污灌补偿调度研究,并对它们进行了定性分析。最后指出下一步灌区污灌补偿研究任务和方向。