State estimation for one-dimensional agro-hydrological processes with model mismatch

The importance of accurate soil moisture data for the development of modern closed-loop irrigation systems cannot be overstated. Due to the diversity of soil, it is difficult to obtain an accurate model for agro-hydrological system. In this study, soil moisture estimation in 1D agro-hydrological systems with model mismatch is the focus. To address the problem of model mismatch, a nonlinear state-space model derived from the Richards equation is utilized, along with additive unknown inputs. The determination of the number of sensors required is achieved through sensitivity analysis and the orthogonalization projection method. To estimate states and unknown inputs in real-time, a recursive expectation maximization (EM) algorithm derived from the conventional EM algorithm is employed. During the E-step, the extended Kalman filter (EKF) is used to compute states and covariance in the recursive Q-function, while in the M-step, unknown inputs are updated by locally maximizing the recursive Q-function. The estimation performance is evaluated using comprehensive simulations. Through this method, accurate soil moisture estimation can be obtained, even in the presence of model mismatch

State of energy estimation in electric propulsion systems with lithium-sulfur batteries

Lithium-Sulfur (Li-S) batteries are an emerging and appealing electrical energy storage technology. The literature on the Stateof- charge (SoC) estimation of Li-S is readily available. In real-world, battery operated vehicles and equipment need to monitor the electrical energy. This paper focuses on State-of-Eneergy (SoE) estimation of Li-S battery based electric propulsion system. This paper bridges literature gap of the SoE estimation of Li-S battery. While comparing mathematically, the definition of the SoC and SoE batteries are different. Reviewing the SoC estimation, this paper compares the SoC and SoE estimation for same data set. The challenges in Li-S SoC and SoE estimation include battery modelling and time-varying parameters and nonlinear voltage measurement, which has deeply skewed high-plateau and flatted low-plateau characteristics. Modelling Li-S battery as a Thevenin’s equivalent circuit network (ECN), the battery parameters are estimated using Predict Error Minimization (PEM) approach. For estimate SoC and SoE, the extended Kalman filter (EKF) is used. Since the parameters are high sensitive to battery current, the estimators use parameters obtained by polynomial fitting model. A simple switching logic based on SoCmeasurement voltage is used to join the high- and low-plateau. The degree of observability analysis is used to investigate the performance of SoE estimation by the EKF. Using experiment test data, simulation results demonstrate the performance of both SoC and SoE estimators. Results show that the SoE estimation is as close to the SoC estimatio

Optimal Mechanisms for Heterogeneous Multi-cell Aquifers

Standard economic models of groundwater management impose restrictive assumptions regarding perfect transmissivity (i.e., the aquifer behaves as a bathtub), no external effects of groundwater stocks, observability of individual extraction rates, and/or homogenous agents. In this article, we derive regulatory mechanisms for inducing the socially optimal extraction path in Markov perfect equilibrium for aquifers in which these assumptions do not hold. In spite of the complexity of the underlying system, we identify an interesting case in which a simple linear mechanism achieves the social optimum. To illustrate potential problems that can arise by erroneously imposing simplifying assumptions, we conduct a simulation based on data from the Indian state of Andhra Pradesh.Common Property Resource, Differential Games, Groundwater Extraction, Imperfect Monitoring, Markov Perfect Equilibrium

State and parameter estimation of the AquaCrop model for winter wheat using sensitivity informed particle filter

Crop models play a paramount role in providing quantitative information on crop growth and field management. However, its prediction performance degrades significantly in the presence of unknown, uncertain parameters and noisy measurements. Consequently, simultaneous state and parameter estimation (SSPE) for crop model is required to maximize its potentials. This work aims to develop an integrated dynamic SSPE framework for the AquaCrop model by leveraging constrained particle filter, crop sensitivity analysis and UAV remote sensing. Both Monte Carlo simulation and one winter wheat experimental case study are performed to validate the proposed framework. It is shown that: (i) the proposed framework with state/parameter bound and parameter sensitivity information outperforms conventional particle filter and constrained particle filter in both state and parameter estimation in Monte Carlo simulations; (ii) in real-world experiment, the proposed approach achieves the smallest root mean squared error for canopy cover estimation among the three algorithms by using day forward-chaining validation method

Um estudo sobre métodos de determinação de estados e parâmetros de máquinas síncronas de polos salientes

Orientador: Mateus GiesbrechtDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: As máquinas síncronas de polos salientes desempenham um papel fundamental na análise de estabilidade de sistemas elétricos de potência, especialmente em países cuja maior parte da energia gerada provém de fontes hidráulicas. Os modelos elétricos equivalentes que descrevem o comportamento dessas máquinas são compostos por diversos parâmetros, os quais são utilizados em uma ampla gama de estudos. No presente trabalho, estudam-se e propõem-se técnicas de estimação de estados e parâmetros de máquinas síncronas de polos salientes. A princípio, as equações de tensão, de fluxos concatenados, de potência e de movimento são desenvolvidas com as devidas unidades de medida, tanto em variáveis de máquina quanto em variáveis projetadas sobre um plano ortogonal que gira na velocidade elétrica do rotor. Na maior parte da literatura, essas unidades não são explicitadas no equacionamento. Dentre os parâmetros elétricos dos modelos das máquinas síncronas de polos salientes, as reatâncias de magnetização são os que mais influenciam o comportamento da máquina em condições de regime permanente senoidal. Desta forma, apresenta-se uma nova abordagem à estimação do ângulo de carga dessas máquinas e o subsequente cálculo das reatâncias de magnetização a partir de condições de carga específicas -- o desempenho do método proposto é avaliado em dados de simulação e em dados reais de operação de um gerador síncrono de grande porte. Algumas abordagens à determinação de parâmetros requerem que a máquina seja posta fora de operação para que ensaios específicos possam ser realizados. Dentre eles, um dos mais empregados na determinação de parâmetros transitórios e de regime permanente é o ensaio de rejeição de carga; assim, este ensaio também é analisado e aperfeiçoado por um método automatizado de separação de soma de exponenciais baseado em projeção de variáveis. Por tratar-se de um sistema multivariável e altamente não linear, diferentes observadores de estado também são utilizados para se determinarem estados e parâmetros de máquinas síncronas em tempo hábil e com precisão satisfatória. Este trabalho apresenta uma abordagem não linear recursivamente aplicável à estimação de fluxos concatenados, correntes de enrolamentos amortecedores, ângulo de carga e reatâncias de magnetização de máquinas síncronas de polos salientes por meio da filtragem de partículas. Um modelo não linear de oitava ordem é considerado e apenas as medições realizadas nos terminais da armadura e do campo durante regime permanente se fazem necessárias para estimar as referidas grandezasAbstract: Salient-pole synchronous machines play a fundamental role in the stability analysis of electrical power systems, especially in countries where most of the generated energy comes from hydraulic sources. The electrical equivalent models that describe the behavior of these machines are composed of several electrical parameters, which are used in a wide range of studies. In the present work, techniques for estimating states and parameters of salient-pole synchronous machines are studied and proposed. A priori, the voltage, flux linkage, power, and motion equations are developed with the appropriate units included, both in machine variables and in variables projected on an orthogonal plane rotating in the rotor's electrical speed. In most of the literature, these units are not explained in the equation process. Among the electrical parameters, the magnetizing reactances are the ones that most influence the machine behavior under transient and steady-state conditions. In this way, a new approach to estimate the load angle of these machines and the subsequent calculation of the magnetizing reactances from specific load conditions are presented -- the performance of the proposed method is evaluated by means of simulation data and by operating data of a large synchronous generator. Some approaches to determine parameters require the machine to be taken out of operation, so that specific tests may be performed. Among them, one of the most used to determine transient and steady-state parameters is the load rejection test; thus, this test is also analyzed and refined by an automated method based on variable projection for separating the resulting sum-of-exponentials. Since the machines are highly nonlinear, multivariate, dynamic systems, different state observers seek to solve the state estimation problem in a timely manner and with satisfactory accuracy. This work presents a nonlinear and recursive approach for the estimation of flux linkages per second, amortisseur winding currents, load angle, and magnetizing reactances of salient-pole synchronous machines by means of the particle filtering. An eighth-order nonlinear model is considered, and only measurements taken at the machine terminals are necessary to estimate these quantitiesMestradoAutomaçãoMestre em Engenharia Elétrica162015/2018-6CNPq

Integrating Knowledge for River Basin Management: Progress in Thailand

Resource /Energy Economics and Policy,

Impact of Land Management Practices on Water Balance and Sediment Transport in the Morogoro Catchment, Uluguru Mountains (Tanzania)

Tanzania, like other developing countries in the tropics is severely affected by the degradation of water resources owing to improper land management practices. Such practices affect water supply through soil erosion which does not only cause sedimentation of rivers and water bodies but also leads to a reduction in the rainwater infiltration capacity of soils. This thesis seeks to demonstrate how the implementation of proper land management measures can reduce soil erosion and increase water supply in the Morogoro River catchment (Uluguru Mountains). The proper practices referred to are the soil and water conservation (SWC) approaches which include contour farming, fanya juu terracing and bench terracing. The thesis combines social science and geoscience methods in a synergetic manner to address this research problem. To understand how and to what degree SWC methods affect water fluxes and sediment yields, the hydrological model SWAT (Soil and Water Assessment Tool) was applied. Before carrying out the modelling procedures, it was necessary to examine the level of SWC adoption among farmers and factors influencing the process so as to establish the baseline. To this end, biophysical and socio-economic factors assumed to affect farmers’ adoption tendency were examined using a household questionnaire. Modelling results indicate that if correctly implemented contour farming, fanya juu terracing and bench terracing would significantly reduce sediment yield at different rates. The reduction would range approximately between 1% - 85% with the highest percentage change achieved by practicing the three SWC methods simultaneously. However, such SWC measures would not increase water flow annually owing to evapotranspiration losses. Nevertheless, according to modelling results groundwater storage would be increased by about 14% and hence contributing to water supply during the dry season. The household questionnaire survey suggests that the adoption of SWC methods in the study area is very low and complex. While age of the head of household, access to extension (professional) services, household annual income and proximity to the farm significantly influenced farmers’ decision to adopt SWC, gender of the head of household, slope characteristics of the farm, number of adults in the household and farmer’s perception on soil erosion effects had no considerable influence on adoption. Therefore, to successfully realize the SWC benefits demonstrated by the modelling results, smallholder farmers upstream of the catchment should be incentivized to implement proper land management practices. Payment for ecosystem services scheme appears to be a suitable strategy. To make this operational, the Tanzanian government should establish a national water fund which will finance watershed management activities. The methodological approach employed in this thesis is transferrable to other sites with problems comparable to the studied catchment