Microgrids (MGs) are small-scale local energy grids. While dedicated to cover local power needs, their structure and operation is usually quite complex. complexity arises due to a number of factors: in the first insta...
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ISBN:
(纸本)9781467325950;9781467325967
Microgrids (MGs) are small-scale local energy grids. While dedicated to cover local power needs, their structure and operation is usually quite complex. complexity arises due to a number of factors: in the first instance, a variety of operational modes - among them, MGs can be considered to be operated autonomously whenever the main distribution grid is not available;furthermore, the heterogeneity of energy types in a MG - not exclusively electrical energy, but also thermal for instance;also, the different functions that a MG energy management system has to fulfill - like coordination and dispatching of multiple generation, transfer, transformation and storage devices;finally, the external and internal random factors that affect operations. All these aspects make control and scheduling of a MG quite a challenging task. On the other hand, this widespread complexity leaves much room for improvement on the current state of the art. An advancement on the state of the art requires the development of a realistic model of the system at hand. This work puts forward a model of a MG that is based on the framework of Stochastic Hybrid systems (SHS). SHS models can capture the interaction between probabilistic elements and discrete and continuous dynamics, and thus promise to be able to tame the complexity of the systems discussed above. This work displays the outcomes of model simulations and discusses potential development of general analysis and synthesis approaches over SHS models (e.g., based on model checking and on approximate dynamic programming) for typical challenges in MGs.
Bond Graph theory is a powerful tool in the field of dynamics and multiple-energy domains analyses of complex engineering systems. On the purpose of analyses the dynamic characters of Stirling Engine fuel supply syste...
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ISBN:
(纸本)9783037853115
Bond Graph theory is a powerful tool in the field of dynamics and multiple-energy domains analyses of complex engineering systems. On the purpose of analyses the dynamic characters of Stirling Engine fuel supply system, the author built a Stirling Engine fuel supply system model based on Bond Graph theory, derived the state equations including pump system and hydraulic system equations and built the Simulink model for simulation, finally verified the accuracy of the model through experiment.
The increasing complexity of (distributed) information systems requires new solutions for dealing with access controlproblems. In particular, information systems are based on a large number of resources, with very co...
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Discrete time series or mappings are proposed for describing the dynamics of a nonlinear system. The article considers the problems of forecasting the dynamics of the system from the time series generated by it. In pa...
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Discrete time series or mappings are proposed for describing the dynamics of a nonlinear system. The article considers the problems of forecasting the dynamics of the system from the time series generated by it. In particular, the commercial rate of drilling oil and gas wells can be considered as a series where each next value depends on the previous one. The main parameter here is the technical drilling speed. With the aim of eliminating the measurement error and presenting the commercial speed of the object to the current with a good accuracy, future or any of the elapsed time points, the use of the Kalman filter is suggested. For the transition from a deterministic model to a probabilistic one, the use of ensemble modeling is suggested. Ensemble systems can provide a wide range of visual output, which helps the user to evaluate the measure of confidence in the model. In particular, the availability of information on the estimated calendar duration of the construction of oil and gas wells will allow drilling companies to optimize production planning by rationalizing the approach to loading drilling rigs, which ultimately leads to maximization of profit and an increase of their competitiveness.
As a type of scheduling problem, the flowshop problem has been largely studied for 60 years. The total completion time is a very interesting criterion because it reflects "the total manufacturing waiting time exp...
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ISBN:
(纸本)9783319175096;9783319175089
As a type of scheduling problem, the flowshop problem has been largely studied for 60 years. The total completion time is a very interesting criterion because it reflects "the total manufacturing waiting time experienced by all customers"(Emmons and Vairaktarakis). There have been many studies in the past but they focused on a limited number of machines and/or on specific constraints. Therefore, this study presents a new approach to tackle a general permutation flowshop problem, with various additional constraints, to elaborate on lower bounds for the total completion time. These lower bounds can take into account several constraints, like delays, blocking or setup times, but they imply solving a Traveling Salesman Problem. The theory is developed first, based on a MaxPlus modeling of flowshop problems and experimental results of a branch-and-bound procedure with a lower bound selection strategy are then presented.
Recently, the intelligent Driver Assistant System (DAS) and an autonomous driving system have been widely studied. For those systems, a local route that represents the road shape is essential information for controlli...
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ISBN:
(纸本)9781538635438
Recently, the intelligent Driver Assistant System (DAS) and an autonomous driving system have been widely studied. For those systems, a local route that represents the road shape is essential information for controlling a vehicle's behavior. When the local route is recognized by the perception sensors attached to the vehicle, the discontinuous information caused by the noise and detection failure worsens the driving comfort and stability. Since filtering methods in previous studies have caused time delays, the reaction of the vehicle control may be late when the curvature of the road changes. In this paper, the local route is temporary modeled into a mathematical form with several nodes to smooth the discontinuous information without delay problems. The node location of the temporal roadway geometry model is probabilistically updated by a Bayesian filtering scheme using the recognized local route. The proposed method was evaluated with a Mobileye camera and a real road. This method not only provided road shape information without a time delay but also interpolated the road shape information during the misdetection of sensor information and updating period.
The proceedings contain 128 papers. The topics discussed include: modeling of V2G net energy injection into the grid;accuracy assessment of the long-term hydro simulation model used in Brazil based on post-operation d...
ISBN:
(纸本)9781509046829
The proceedings contain 128 papers. The topics discussed include: modeling of V2G net energy injection into the grid;accuracy assessment of the long-term hydro simulation model used in Brazil based on post-operation data;an integrated battery-charger for switched reluctance motor drives;design and calculation of a 130 kW high-speed permanent magnet synchronous machine in flywheel energy storage systems for urban railway application;flywheel energy storage systems for power systems application;using potential of domestic solar hot water systems as an alternative to reduce the electricity peak demand in Assalouyeh;a nonlinear Lyapunov-based control for an autonomous variable-speed wind turbine;use of natural sunlight incident to an internal environment with control and compensation of luminosity through an electronic system;experimental tests on a wave-to-wire pivoted system for wave energy exploitation;equilibrium approach to the single solution of longer- and shorter-term hydro-thermal scheduling problems;a linear programming approach to distribution power flow;design and sizing of short term energy storage for a PV system;hybridisation of railcars for usage in non-electrified lines;influence of power-to-gas-technology on unit commitment and power system operation;low voltage single fuel cell interface by push-pull converter: a case of study;and numerical evaluation of profitability of Estonian electricity-generating technologies.
We address the relevant problem of machine learning in a multi-agent system for distributed computing management. We propose a new approach to the agent learning in the system for managing job flows of scalable applic...
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With the increasing proportion of renewable energy generation, the grid lost strong electrical support for renewable energy generating units, which leads to a series of new grid- connected stability problems. Therefor...
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LabVIEW is a versatile tool with various inbuilt toolkits to perform various measurement and control tasks. Hence, it is used in almost every field of engineering. However, it does not provide enough contribution in t...
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ISBN:
(纸本)9789811059032;9789811059025
LabVIEW is a versatile tool with various inbuilt toolkits to perform various measurement and control tasks. Hence, it is used in almost every field of engineering. However, it does not provide enough contribution in the field of optimization which is the major concern. It has only one optimizer based on differential evolution (DE) algorithm. Even though DE is a very effective global optimization technique, but its performance highly depends on parametric settings. DE contains high number of user-defined parameters;therefore, it becomes cumbersome for user to obtain best parametric settings for a given optimization problem. Recently, several nature-inspired algorithms are developed with reduced number of parametric settings to obtain the optimum solutions while solving complex black box optimization problems. Hence, to update the LabVIEW in the field of optimization, there exists a need of continuous development of other efficient global optimizers. Multi-verse optimizer (MVO) is considered as one of the latest but effective nature-inspired optimization algorithm with only two user-defined parameters. In this paper, MVO toolkit is developed for LabVIEW platflorm and the efficiency of the proposed toolkit is validated on a test bed of five standard benchmark functions. The statistical analysis of results shows that the MVO is far better in solving optimization problems as compared to DE.
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