A Pump Monitoring Approach to Irrigation Pumping Plant Performance Testing

Traditionally, irrigation pumping plants have been tested using an instantaneous appraoch, which tests performance parameters over a very short time interval. Using this method, the tester measures the necessary work and energy use parameters to calculate the desired pumping plant performance values. The primary limitation of this approach is its inability to determine the season long efficiency of an irrigation pumping plant. A new approach to evaluating irrigation pumping plant performance is the use of pump monitoring systems which use high frequency, real-time data collection and telemetry to relay information directly from the pump to the user. This method of testing essentially conducts a continuous pumping plant performance evaluation. Throughout a typical irrigation season, a single pumping plant typically operates at a wide range of total dynamic heads as a result of changes in operational conditions due to factors such as aquifer drawdown and irrigation demand changes. When coupled with telemetry, this approach to irrigation pumping plant testing can provide real-time feedback to the irrigator on pumping plant performance, even as the operating conditions of the system changes throughout the season. Nearly 100 pumping years of diesel and electric pumping plant data was evaluated over four irrigation seasons using a network of these pump monitoring systems. Annual averages and trends in water pumping flow rate, cost of water per unit volume pumped, and efficiency as a percentage of the Nebraska Pumping Plant Performance Criteria, among other performance values were reported. These pumping performance values can be used to develop recommendations to producers in order to improve pumping plant performance and reduce operating costs as well as identifying the causes of pumping plant inefficiencies

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

Cost Optimization Modeling of Renewable Energy Sources in Smart Grid Using SCADA

In recent times, renewable energy production from renewable energy sources is an alternative way to fulfill the increased energy demands. However, the increasing energy demand rate places more pressure, leading to the termination of conventional energy resources. On the other hand, the depletion of fossil fuels like coal, petroleum, natural gas, etc., is creating an adverse effect on the environment. However, the cost of power generation from coal-fired plants is higher than the power generation\u27s price from renewable energy sources. Therefore, it has become a stumbling block balancing this increased energy demand using existing resources and new renewable resources that optimize the total power generation and the cost of power generation. However, power generation from the combined renewable energy sources confronts few complications, such as unstable power generated from the wind generator, the higher operational cost of the hydropower plant, etc. This experiment is focused on cost optimization during power generation through the pumped storage power plant and wind power plant. The entire modeling of cost optimization has been conducted in two parts. The mathematical modeling was done using MATLAB simulation while the hydro and wind power plant\u27s emulation was performed using SCADA designer implementation. The experiment was conducted using ranges of generated power from both power sources. The optimum combination of output power and cost from both generators is determined via MATLAB simulation within the assumed generated output power range. Secondly, the hydro-generator and wind generator\u27s emulation were executed individually through synchronizing the grid to determine each generator\u27s specification using SCADA designer, which provided the optimum power generation from both generators with the specific speed, aligning with results generated through MATLAB. Finally, the operational power cost (with no losses consideration) from MATLAB was compared with the local energy provider to determine the cost-efficiency. This experiment has provided the operational cost optimization of the hydro-wind combined power system with stable wind power generation using SCADA, which will ultimately assist in operations of large-scale power systems, remotely minimizing multi-area dynamic issues while maximizing the system efficiency

Modelling and Management of Irrigation System

Irrigation is becoming an activity of precision, where combining information collected from various sources is necessary to optimally manage resources. New management strategies, such as big data techniques, sensors, artificial intelligence, unmanned aerial vehicles (UAV), and new technologies in general, are becoming more relevant every day. As such, modeling techniques, both at the water distribution network and the farm levels, will be essential to gather information from various sources and offer useful recommendations for decision-making processes. In this book, 10 high quality papers were selected that cover a wide range of issues that are relevant to the different aspects related to irrigation management: water source and distribution network, plot irrigation systems, and crop water management

Groundwater research and management: integrating science into management decisions. Proceedings of IWMI-ITP-NIH International Workshop on "Creating Synergy Between Groundwater Research and Management in South and Southeast Asia," Roorkee, India, 8-9 February 2005

Groundwater management / Governance / Groundwater development / Artificial recharge / Water quality / Aquifers / Groundwater irrigation / Water balance / Simulation models / Watershed management / Water harvesting / Decision making / South East Asia / Bangladesh / China / India / Nepal / Pakistan / Syria

On-Farm Water Management Game With Heuristic Capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide reasonable scores and advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach; and (2) reinforcement learning based on a Markov Decision Processes approach, specifically, the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system on the game world. The reward function for the Q-learning method was modified to reflect the anticipated type of the WaterMan game as what is referred to as a partially competitive and partially cooperative game. Twenty-two different persons classified under three major categories (1) practicing farmers; (2) persons without an irrigation background; and (3) persons with an irrigation background, were observed while playing the game, and each of them filled out a questionnaire about the game. The technical module of the game was validated in two ways: through conducting mass balance calculations for soil water content and salt content over a period of simulation time, and through comparing the WaterMan technical module output data in calculating the irrigation requirements and the use of irrigation scheduling recommendations with those obtained from the same set of input data to the FAO CropWat 8 software. The testing results and the technical validation outcomes demonstrate the high performance of the WaterMan game as a heuristic training tool for on-farm water management

Review of Researches on Techno-Economic Analysis and Environmental Impact of Hybrid Energy Systems

Hybrid energy systems, which are combinations of two or more renewable and non-renewable energy sources, have been identified as a viable mechanism to address the limitations of a single renewable energy source, utilized for electricity generation. In view of this, several research works have been carried out to determine the optimal mix of different renewable and non-renewable energy resources used for electricity generation. This paper presents a comprehensive review of the optimization approaches proposed and adopted by various authors in the literature for optimal sizing of hybrid energy systems. It is observed that the objective functions - considered by a large percentage of researchers to optimize the sizing of hybrid energy systems - are cost minimization of the generated electricity, system reliability enhancement and environmental pollution reduction. Other factors covered in the literature are equally discussed in this article. Similarly, simulation and optimization software used for the same purpose are covered in the paper. In essence, the main aim of this paper is to provide a scope into the works that have been carried out in the field of hybrid energy systems, used for electricity generation with the view to informing researchers and members of the public alike, on trends in methods applied in optimal sizing of hybrid energy systems. It is believed that the information provided in this paper is very crucial in advancing research in the field

Optimization of environmentally friendly solar assisted absorption cooling systems

La optimización de los sistemas de conversión de energía gana cada vez más importancia debido a su impacto ambiental y los limitados recursos de combustibles fósiles. Entre estos sistemas los de refrigeración tienen una contribución creciente en el consumo total de energía y en las emisiones de CO2. Los sistemas de absorción operados con energía solar son una de las alternativas más sostenibles frente a los sistemas de refrigeración convencionales. Por lo tanto, este trabajo se centra en su mejora siguiendo los métodos de optimización termo-económica y de programación matemática. El análisis exergético y la optimización termo-económica basada en el método estructural se han realizado para distintas configuraciones de ciclos de refrigeración por absorción con las mezclas de trabajo agua-LiBr y amoniaco-agua. En la sección de programación matemática se incluye la optimización multi-objetivo (frontera de Pareto), la optimización bajo incertidumbre de los precios de la energía, el uso de varios indicadores de impacto ambiental y el efecto del impuesto sobre las emisiones de CO2. Los resultados demuestran que se pueden obtener reducciones importantes del impacto ambiental frente a los sistemas convencionales. Los sistemas de refrigeración solar no sólo son atractivos para reducir el impacto ambiental, sino también pueden ser económicamente competitivos. Su implantación dependerá, en gran medida, del impuesto sobre las emisiones de CO2 y del coste de la energía.Optimizations of energy conversion systems become more important because of their environmental impact and the limitations of the fossil fuel resources. Among these systems cooling and refrigeration machines have an increasing share in the total energy consumption and contribution to CO2 emissions. Solar assisted absorption cooling systems are sustainable alternatives compared to the conventional cooling systems. Hence, this work is focused on improving the sustainability of cooling systems following the thermoeconomic optimization and mathematical programming approaches. In the first approach the energy, exergy and structural analysis are performed for different configurations of water/LiBr and ammonia/water absorption cooling cycles. In the second approach multi-objective optimization (Pareto frontier), optimization under uncertainty of energy prices, different environmental impact indicators, and the effect of CO2 emissions tax to reduce the global warming are discussed. The results of the multi-objective optimization show that a significant environmental impact reduction can be obtained. Results indicate that these systems are attractive not only to reduce the environmental impact but also in incurring the economic benefits. However, its practical impact largely depends on the CO2 emissions tax and the increase in the energy price

Enhanced Pump Schedule Optimization For Large Water Distribution Networks To Maximize Environmental And Economic Benefits

For more than four decades researchers tried to develop optimization method and tools to reduce electricity consumption of pump stations of water distribution systems. Based on this ongoing research trend, about a decade ago, some commercial pump operation optimization software introduced to the market. Using metaheuristic and evolutionary techniques (e.g. Genetic Algorithm) make some commercial and research tools able to optimize the electricity cost of small water distribution systems (WDS). Still reducing the environmental footprint of these systems and dealing with large and complicated water distribution system is a challenge. In this study, we aimed to develop a multiobjective optimization tool (PEPSO) for reducing electricity cost and pollution emission (associated with energy consumption) of pump stations of WDSs. PEPSO designed to have a user-friendly graphical interface besides the state of art internal functions and procedures that lets users define and run customized optimization scenarios for even medium and large size WDSs. A customized version of non-dominated sorting genetic algorithm II is used as the core optimizer algorithm. EPANET toolkit is used as the hydraulic solver of PEPSO. In addition to the EPANET toolkit, a module is developed for training and using an artificial neural network instead of the high fidelity hydraulic model to speed up the optimization process. A unique measure that is called “Undesirability” is also introduced and used to help PEPSO in finding the promising path of optimization and making sure that the final results are desirable and practical. PEPSO is tested for optimizing the detailed hydraulic model of WDS of Monroe city, MI, USA and skeletonized hydraulic model of WDS of Richmond, UK. The various features of PEPSO are tested under 8 different scenarios, and its results are compared with results of Darwin Scheduler (a well-known commercial software in this field). The test results showed that in a reasonable amount of time, PEPSO is able to optimize and provide logical results for a medium size WDS model with 13 pumps and thousands of system components under different scenarios. It also is concluded that this tool in many aspects can provide better results in comparison with the famous commercial optimization tool in the market

Microgrids

Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems