Modeling and simulation of hydrokinetic composite turbine system

The utilization of kinetic energy from the river is promising as an attractive alternative to other available renewable energy resources. Hydrokinetic turbine systems are advantageous over traditional dam based hydropower systems due to zero-head and mobility. The objective of this study is to design and analyze hydrokinetic composite turbine system in operation. Fatigue study and structural optimization of composite turbine blades were conducted. System level performance of the composite hydrokinetic turbine was evaluated. A fully-coupled blade element momentum-finite element method algorithm has been developed to compute the stress response of the turbine blade subjected to hydrodynamic and buoyancy loadings during operation. Loadings on the blade were validated with commercial software simulation results. Reliability-based fatigue life of the designed composite blade was investigated. A particle swarm based structural optimization model was developed to optimize the weight and structural performance of laminated composite hydrokinetic turbine blades. The online iterative optimization process couples the three-dimensional comprehensive finite element model of the blade with real-time particle swarm optimization (PSO). The composite blade after optimization possesses much less weight and better load-carrying capability. Finally, the model developed has been extended to design and evaluate the performance of a three-blade horizontal axis hydrokinetic composite turbine system. Flow behavior around the blade and power/power efficiency of the system was characterized by simulation. Laboratory water tunnel testing was performed and simulation results were validated by experimental findings. The work performed provides a valuable procedure for the design and analysis of hydrokinetic composite turbine systems --Abstract, page iv

Integration of High Voltage AC/DC Grids into Modern Power Systems

Electric power transmission relies on AC and DC grids. The extensive integration of conventional and nonconventional energy sources and power converters into power grids has resulted in a demand for high voltage (HV), extra-high voltage (EHV), and ultra-high voltage (UHV) AC/DC transmission grids in modern power systems. To ensure the security, adequacy, and reliable operation of power systems, the practical aspects of interconnecting HV, EHV, and UHV AC/DC grids into the electric power systems, along with their economic and environmental impacts, should be considered. The stability analysis for the planning and operation of HV, EHV, and UHV AC/DC grids in power systems is regarded as another key issue in modern power systems. Moreover, interactions between power converters and other power electronics devices (e.g., FACTS devices) installed on the network are other aspects of power systems that must be addressed. This Special Issue aims to investigate the integration of HV, EHV, and UHV AC/DC grids into modern power systems by analyzing their control, operation, protection, dynamics, planning, reliability, and security, along with considering power quality improvement, market operations, power conversion, cybersecurity, supervisory and monitoring, diagnostics, and prognostics systems

Bio-inspired optimization in integrated river basin management

Water resources worldwide are facing severe challenges in terms of quality and quantity. It is essential to conserve, manage, and optimize water resources and their quality through integrated water resources management (IWRM). IWRM is an interdisciplinary field that works on multiple levels to maximize the socio-economic and ecological benefits of water resources. Since this is directly influenced by the river’s ecological health, the point of interest should start at the basin-level. The main objective of this study is to evaluate the application of bio-inspired optimization techniques in integrated river basin management (IRBM). This study demonstrates the application of versatile, flexible and yet simple metaheuristic bio-inspired algorithms in IRBM. In a novel approach, bio-inspired optimization algorithms Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are used to spatially distribute mitigation measures within a basin to reduce long-term annual mean total nitrogen (TN) concentration at the outlet of the basin. The Upper Fuhse river basin developed in the hydrological model, Hydrological Predictions for the Environment (HYPE), is used as a case study. ACO and PSO are coupled with the HYPE model to distribute a set of measures and compute the resulting TN reduction. The algorithms spatially distribute nine crop and subbasin-level mitigation measures under four categories. Both algorithms can successfully yield a discrete combination of measures to reduce long-term annual mean TN concentration. They achieved an 18.65% reduction, and their performance was on par with each other. This study has established the applicability of these bio-inspired optimization algorithms in successfully distributing the TN mitigation measures within the river basin. Stakeholder involvement is a crucial aspect of IRBM. It ensures that researchers and policymakers are aware of the ground reality through large amounts of information collected from the stakeholder. Including stakeholders in policy planning and decision-making legitimizes the decisions and eases their implementation. Therefore, a socio-hydrological framework is developed and tested in the Larqui river basin, Chile, based on a field survey to explore the conditions under which the farmers would implement or extend the width of vegetative filter strips (VFS) to prevent soil erosion. The framework consists of a behavioral, social model (extended Theory of Planned Behavior, TPB) and an agent-based model (developed in NetLogo) coupled with the results from the vegetative filter model (Vegetative Filter Strip Modeling System, VFSMOD-W). The results showed that the ABM corroborates with the survey results and the farmers are willing to extend the width of VFS as long as their utility stays positive. This framework can be used to develop tailor-made policies for river basins based on the conditions of the river basins and the stakeholders' requirements to motivate them to adopt sustainable practices. It is vital to assess whether the proposed management plans achieve the expected results for the river basin and if the stakeholders will accept and implement them. The assessment via simulation tools ensures effective implementation and realization of the target stipulated by the decision-makers. In this regard, this dissertation introduces the application of bio-inspired optimization techniques in the field of IRBM. The successful discrete combinatorial optimization in terms of the spatial distribution of mitigation measures by ACO and PSO and the novel socio-hydrological framework using ABM prove the forte and diverse applicability of bio-inspired optimization algorithms

Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems

The transition to 100% renewable energy in the future is one of the most important ways of achieving "carbon peaking and carbon neutrality" and of reducing the adverse effects of climate change. In this process, the safe, stable and economical operation of renewable energy generation systems, represented by hydro-, wind and solar power, is particularly important, and has naturally become a key concern for researchers and engineers. Therefore, this book focuses on the fundamental and applied research on the modeling, control, monitoring and diagnosis of renewable energy generation systems, especially hydropower energy systems, and aims to provide some theoretical reference for researchers, power generation departments or government agencies

Optimal operation control of hybrid renewable energy systems

Thesis (D. Tech. (Electrical Engineering)) -- Central University of Technology, Free State, 2014For a sustainable and clean electricity production in isolated rural areas, renewable energies appear to be the most suitable and usable supply options. Apart from all being renewable and sustainable, each of the renewable energy sources has its specific characteristics and advantages that make it well suited for specific applications and locations. Solar photovoltaic and wind turbines are well established and are currently the mostly used renewable energy sources for electricity generation in small-scale rural applications. However, for areas in which adequate water resources are available, micro-hydro is the best supply option compared to other renewable resources in terms of cost of energy produced. Apart from being capital-cost-intensive, the other main disadvantages of the renewable energy technologies are their resource-dependent output powers and their strong reliance on weather and climatic conditions. Therefore, they cannot continuously match the fluctuating load energy requirements each and every time. Standalone diesel generators, on the other hand, have low initial capital costs and can generate electricity on demand, but their operation and maintenance costs are very high, especially when they run at partial loads. In order for the renewable sources to respond reliably to the load energy requirements, they can be combined in a hybrid energy system with back-up diesel generator and energy storage systems. The most important feature of such a hybrid system is to generate energy at any time by optimally using all available energy sources. The fact that the renewable resources available at a given site are a function of the season of the year implies that the fraction of the energy provided to the load is not constant. This means that for hybrid systems comprising diesel generator, renewable sources and battery storage in their architecture, the renewable energy fraction and the energy storage capacity are projected to have a significant impact on the diesel generator fuel consumption, depending on the complex interaction between the daily variation of renewable resources and the non-linear load demand. V This was the context on which this research was based, aiming to develop a tool to minimize the daily operation costs of standalone hybrid systems. However, the complexity of this problem is of an extremely high mathematical degree due to the non-linearity of the load demand as well as the non-linearity of the renewable resources profiles. Unlike the algorithms already developed, the objective was to develop a tool that could minimize the diesel generator control variables while maximizing the hydro, wind, solar and battery control variables resulting in saving fuel and operation costs. An innovative and powerful optimization model was then developed capable of efficiently dealing with these types of problems. The hybrid system optimal operation control model has been simulated using fmincon interior-point in MATLAB. Using realistic and actual data for several case studies, the developed model has been successfully used to analyse the complex interaction between the daily non-linear load, the non-linear renewable resources as well as the battery dynamic, and their impact on the hybrid system’s daily operation cost minimization. The model developed, as well as the solver and algorithm used in this work, have low computational requirements for achieving results within a reasonable time, therefore this can be seen as a faster and more accurate optimization tool

Short term complex hydro thermal scheduling using integrated PSO-IBF algorithm

In this article, an integrated evolutionary technique such as particle swarm optimization (PSO) algorithm and improved bacterial foraging algorithm (IBFA) have been developed to provide an optimum solution to the scheduling problem with complex thermal and hydro generating stations. PSO algorithm is framed based on the intelligent behavior of the fish school and a flock of birds and the optimal solution in the multidimensional search region is achieved by assigning a random velocity to each potential solution (called the particle). BFA is designed by following the prey-seeking (chemotactic) nature of E. coli bacteria. This technique is followed in an improved manner to get the convergence rate in dynamic for a hyperspace problem by implementing a chemotactic step in a linearly decreased way instead of the static one. The effectiveness of this integrated algorithm is evaluated by using it in a complex thermal and hydro generating system. In this testing system, multiple numbers of cascaded reservoirs in hydro plants have a time coupling effect and thermal power units have a valve point loading effect. The simulation results indicate its merits by comparing it with other meta-heuristic techniques related to the fuel cost required to generate the thermal power.

Hybrid Generation Systems Planning Expansion Forecast: A Critical State of the Art Review

International audienceIn recent years the electric power generation has entered into a new development era, which can be described mainly by increasing concerns about climate change, through the energy transition from hydrocarbon to clean energy resources. In order to power system enhance reliability, efficiency and safety, renewable and nonrenewable resources are integrated together to configure so-called hybrid systems. Despite the experience accumulated in the power networks, designing hybrid system is a complex task. It has become more challenging as far as most renewable energy resources are random and weather/climatic conditions-dependant. In this challenging context, this paper proposes a critical state-of-the-art review of hybrid generation systems planning expansion and indexes multi-objective methods as strategies for hybrid energy systems optimal design to satisfy technical and economical constraints

SHORT TERM HYDRO THERMAL SCHEDULING PROBLEM: A REVIEW

Operation of a system having both hydro and thermal plants is far more complex and is of much more importance in a modern interconnected power system. The objective of the STHS problem is to optimize the electricity production, considering a short-term planning horizon. This paper presents an extensive review of a short term hydro thermal scheduling problem. The paper demonstrates results of various evolutionary and analytical methods applied on a short term hydro thermal scheduling problem .All the assumptions made and a brief description of the solution methods is presented in the paper. The paper provides helpful information and resources for the future studies for researchers those interested in the problem or intending to do additional research in this area

Optimal operation of dams/reservoirs emphasizing potential environmental and climate change impacts

Mahdi studied the potential ecological and climate change impacts on management of dams. He developed several new optimization frameworks in which benefits of dams are maximized, while above impacts are mitigated. Governments and consulting engineers can use the proposed frameworks for managing dams considering environmental challenges in river basins