The increasing presence of renewable distributed generation (DG) units such as photovoltaic and wind power generation is a major challenge for the suitable operation of the electrical distribution systems (EDSs). Unce...
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The increasing presence of renewable distributed generation (DG) units such as photovoltaic and wind power generation is a major challenge for the suitable operation of the electrical distribution systems (EDSs). Uncertainties of renewable DG units and loads, related to the stochastic nature of solar irradiation, wind speed, and consumer behavior, require efficient tools that help the distribution system operator to properly define a control plan of the EDS. Within this framework, the probabilistic optimal power flow (POPF) provides statistical information(e.g. voltage profile, power flows, and power losses) according to the variation of the stochastic variables (e.g. power demand and injection of generation units). Many available POPF methods have been designed for transmission systems and/or are based on Monte Carlo simulation (MCS), which requires a high computational effort. On the other hand, other approaches adopt analytical methods, which are not applied considering the characteristics of distribution systems. This paper proposes a fast-specialized point estimate method for the POPF in EDSs with the presence of renewable DG units, based on a linearization of the Branch Flow equations and Hong's point estimate method. Due to its convex nature, the advantage of the proposed method is to use wellestablished linearprogramming commercial solvers to solve the problem. Numerical results using the IEEE 69-bus and a real EDS demonstrate the efficiency in terms of computational burden and accuracy of the proposed method compared to MCS and Cumulant approaches.
This work presents dynamic optimization strategies of batch hydrothermal liquefaction of two microalgal species, Aurantiochytrium sp. KRS101 and Nannochloropsis sp. to optimize the reactor temperature profiles. Three ...
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This work presents dynamic optimization strategies of batch hydrothermal liquefaction of two microalgal species, Aurantiochytrium sp. KRS101 and Nannochloropsis sp. to optimize the reactor temperature profiles. Three dynamic optimization problems are solved to maximize the endpoint biocrude yield, minimize the final time, and minimize the reactor thermal energy. The biocrude maximization and time minimization problems demonstrated 11% and 6.18% increment in the optimal biocrude yields and reduction of 78.2% and 61.66% in batch times compared to the base cases for the microalgae with higher lipid and protein fractions, respectively. The energy minimization problem revealed a significant reduction in the reactor thermal energies to generate the targeted biocrude yields compared to the biocrude maximization. Therefore, the identified optimal temperature trajectories outperformed the conventional fixed temperature profiles and could improve the overall economics of the batch bio-oil production from the algal-based biorefineries by significantly enhancing the reactor performance.
This paper presents a parametric optimization task of steel conic shell towers of wind-powered generators. The minimum weight of the steel tower has been considered as purpose function when produced capacity of the wi...
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This paper presents a parametric optimization task of steel conic shell towers of wind-powered generators. The minimum weight of the steel tower has been considered as purpose function when produced capacity of the wind-powered generators has been fixed at the target level. The tower's height, diameters of the middle surface of the tower's conic shell at the base level and at a height if the wind turbine installation, thicknesses of the tower's conic shell, and also the diameter of the wind wheel were considered as design variables. The wind loads applied on steel shell tower have been presented in dependence of design variables and considered as state variables. The optimization problem formulated as non-linear programming task has been solved by improved gradient method. Optimum design decisions of the steel conic shell towers for the wind-powered generators with produced capacity of wide range have been defined. An optimum tower's height and weight in dependence of produced capacity of wind-powered generators have been plotted.
We consider the planning of pulp production for large sulphate and sulfite mills. The production planning problem is formulated as a non-linear program (NLP) given a process model of the mill as constraint. The object...
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We consider the planning of pulp production for large sulphate and sulfite mills. The production planning problem is formulated as a non-linear program (NLP) given a process model of the mill as constraint. The objective is to minimize the usage of expensive chemicals and to minimize the (squared) deviation from specified set-points for selected variables, e.g. production, tank-level and chemical composition of the cooking liquor. The problem formulation also considers upper and lower limits on variables and limitations in the derivative of production related variables. The NLP, which involves several tens of thousands of variables, is solved using algorithms for large-scale optimization. To provide a correct initial state of the process model, a moving horizon estimation is done to estimate the current state of the process. A model library consisting of common process units in pulp mills have been developed. The models are described by differential algebraic equations. A software platform, which enables the user to assemble complex process models of complete mills based on the model library, has been developed. The platform also serves as data collector for the measured values from process sensors, as well as storing optimized and estimated values. The pulp mill production planning system is installed on-line at Billerud Gruvön, a large Swedish integrated pulp and paper mill, producing some 660000 tons of sulphate and sulfite pulp.
This paper deals with the thermal diagnosis on a D.C. motor working with steady or variable speed. This supervision is performed by means of parameter identification of a thermal model with parameters depending on ang...
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This paper deals with the thermal diagnosis on a D.C. motor working with steady or variable speed. This supervision is performed by means of parameter identification of a thermal model with parameters depending on angular speed. The model parameter is estimated by minimizing the output error by means of a nonlinearprogramming according to the Marquardt algorithm. The method used allows characterizing and distinguishing several thermal behaviours.
In order to improve the performance of time difference of arrival(TDOA)localization,a nonlinear least squares algorithm is proposed in this ***,based on the criterion of the minimized sum of square error of time diffe...
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In order to improve the performance of time difference of arrival(TDOA)localization,a nonlinear least squares algorithm is proposed in this ***,based on the criterion of the minimized sum of square error of time difference of arrival,the location estimation is expressed as an optimal problem of a non-linear ***,an initial point is obtained using the semi-definite *** finally,the location is extracted from the local optimal solution acquired by Newton *** results show that when the number of anchor nodes is large,the performance of the proposed algorithm will be significantly better than that of semi-definite programming approach with the increase of measurement noise.
The paper presents the method of assigning and results of simulation safe trajectory to avoid a collision at sea. There have considered meeting situations a few ships encounter. The process is described as a task non-...
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The paper presents the method of assigning and results of simulation safe trajectory to avoid a collision at sea. There have considered meeting situations a few ships encounter. The process is described as a task non-linear progranuning with using maximum principle. The paper contains examples of simulations.
A number of markets, geographically separated, with different demand characteristics for different products that share a common component, are analyzed. This common component can either be manufactured locally in each...
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A number of markets, geographically separated, with different demand characteristics for different products that share a common component, are analyzed. This common component can either be manufactured locally in each of the markets or transported between the markets to fulfill the demand. However, final assemblies are localized to the respective markets. The decision making challenge is whether to manufacture the common component centrally or locally. To formulate the underlying setting, a newsvendor modeling based approach is considered. The developed model is solved using Frank-Wolfe linearization technique along with Benders' decomposition method. Further, the propensity of decision makers in each market to make suboptimal decisions leading to bounded rationality is considered. The results obtained for both the cases are compared.
This study mainly focuses on the design of a new cantilever structure and its minimal mass optimization subject to yield and buckling constraints. Given a vertical force in a constant distance from a vertical wall, th...
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This study mainly focuses on the design of a new cantilever structure and its minimal mass optimization subject to yield and buckling constraints. Given a vertical force in a constant distance from a vertical wall, the minimal mass design of a two elements structure with and without anchorage length limitation of the wall is first studied. To further reduce the total structural mass of, a sector cantilever structure is proposed, and the advantage of choosing equal bar length and connecting strings to the center of a circle is proved. Given finite anchorage length of the wall, a tailored sector cantilever structure with finite anchorage length is proposed. Minimal mass design of the sector cantilever with and without anchorage length constraint can be obtained by processing a constrained nonlinear optimization of shape parameters. Considering the penalty of joint mass, the optimal complexity of the sector cantilever will decrease as the penalty coefficient increases. Numerical results are given to show the efficiency of the proposed cantilever structures in saving mass.
Waves and currents interact, with the resulting combination largely determining the loading on offshore structures and devices. Despite this, currents are often ignored and wave buoy data is processed without consider...
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Waves and currents interact, with the resulting combination largely determining the loading on offshore structures and devices. Despite this, currents are often ignored and wave buoy data is processed without consideration of the current or the wave-current interaction. This data is subsequently used in design, yet sea state power, steepness, and directionality may have significant errors. Here we present a novel framework for the processing of wave buoy data to account for the effect of a current. We use a mesh adaptive direct search (MADS) algorithm to solve for the current and current-modified wave parameters simultaneously. Through 125 simulated directional wave-current sea states, we demonstrate the performance of the method under a wide range of conditions;including bimodal sea states with non-colinear current. Current speed and direction are estimated accurately for all cases (mean RMSE of 0.1179ms(-1) and 0.0091 rad respectively) which enables sea state steepness and power to be estimated within +/- 3%. Ignoring this current of +/- 2(-1) when deriving these wave parameters results in errors up to 30%. This work demonstrates that it is possible to correctly process wave buoy measurement data to account for, and quantify, a current thus significantly reducing the uncertainty of the ocean conditions. After further validation work, the framework can be widely applied to historic datasets, correcting the wave data and providing an additional dataset of current velocities.
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