We consider convex Semi-Infinite programming (SIP) problems with a continuum of constraints. For these problems we introduce new concepts of immobility orders and immobile indices. These concepts are objective and imp...
详细信息
We consider convex Semi-Infinite programming (SIP) problems with a continuum of constraints. For these problems we introduce new concepts of immobility orders and immobile indices. These concepts are objective and important characteristics of the feasible sets of the convex SIP problems since they make it possible to formulate optimality conditions for these problems in terms of optimality conditions for some NLP problems (with a finite number of constraints). In the paper we describe a finite algorithm (DIO algorithm) of determination of immobile indices together with their immobility orders, study some important properties of this algorithm, and formulate the Implicit Optimality Criterion for convex SIP without any constraint qualification conditions (CQC). An example illustrating the application of the DIO algorithm is provided.
Captive power plants installed in large scale industries in many developing counties like India, are intended mainly as a stand by supply source or to cater some portion of critical load, and hence remain under utiliz...
详细信息
Captive power plants installed in large scale industries in many developing counties like India, are intended mainly as a stand by supply source or to cater some portion of critical load, and hence remain under utilized. In the context of ongoing power system deregulation, the spare capacity of captive power plants can be effectively utilized by wheeling the captive power among the deficient industries, which will in turn reduce the utility's peak demand. In this paper, an optimization model for captive power wheeling for peak demand management is proposed. The formulation utilizes nonlinearprogramming technique for minimizing the electricity cost and reducing the peak demand, by wheeling the captive power among the industries, satisfying the system constraints. The model when applied to three large scale industries of a typical industrial belt, resulted in significant reduction in peak demand (about 39%) and electricity cost (about 11%).
This paper proposes the software package SISCON, dedicated to the evaluation of optimal decisions for large scale systems. SISCON firstly evaluates mathematical models developed from experimental data using LS methods...
详细信息
This paper proposes the software package SISCON, dedicated to the evaluation of optimal decisions for large scale systems. SISCON firstly evaluates mathematical models developed from experimental data using LS methods for linear and nonlinear systems and after that computes the optimal decision problems, solving the mathematical non-linear programming problems. The large scale systems have generally a complex structure and global approach computation cannot be carried out. The authors present a decentralised decision structure having a well-defined distribution of supervisory functions. After decomposition of large – scale problems is carried out, sub problems are solved using standard optimization techniques. SISCON offers opportunities for solving non-linear mathematical programming problems and for evaluating optimal decisions in large scale systems control.
In this paper, we put forward a new hybrid methodology to generate forecasts of time series. Indeed, the proposed forecaster is a HWCF that integrates the following techniques: wavelet decomposition;ARIMA models;SVRs;...
详细信息
In this paper, we put forward a new hybrid methodology to generate forecasts of time series. Indeed, the proposed forecaster is a HWCF that integrates the following techniques: wavelet decomposition;ARIMA models;SVRs;wavelet combination of forecasts;and non-linear programming. Basically, the HWCF is able to capture, simultaneously, linear and non-linear auto-dependence structures exhibited by a time series, which are represented, at time t, by both the linear and non-linear combined forecasts: L-C,L-t and N-C,N-t, respectively. After obtaining the combined forecasts L-C,L-t and N-C,N-t, they are summed (i. e., L-C,L-t + N-C,N-t = yh,t), producing the hybrid forecast yh,t, for each instant t. The numerical results show that HWCF achieved relevant accuracy gains in forecasting process of the annual time series of sunspot, when comparing with other ten competitive forecasters.
作者：
A. GarzilloM. InnortaP. MaranninoD. SaporaEnel
Ente Nazionale per l'Energia Elettrica Automatica Research Center Via Valvassori Peroni 77-20133 Milano Italy Enel
Ente Nazionale per l'Energia Elettrica Production and Transmission Department Via G.B. Martini 3-00198 Roma Italy
The aim of the reactive power optimization is to improve as much as possible the quality of the service. The main efficiency figures taken into account are the minimum losses in the transmissio system, the warranty of...
详细信息
The aim of the reactive power optimization is to improve as much as possible the quality of the service. The main efficiency figures taken into account are the minimum losses in the transmissio system, the warranty of a determined voltage level for the consumers and the maximum reactive margin in the generating units. The latter is also an effective criterion for operating in order to cope with some contingencies in the power system. Therefore, the proposed procedure determines the minimum total MVAR generation, while observing the voltage constraints and guaranteeing that all the units operate in the feasible region delimited by the capability charts. Further constraints can be introduced in order to take into account the effects of possible regional voltage regulators. This involves the requirement of the same value in p.u. for the reactive power generation of all control units belonging to the same area. From a mathematical point of view we minimize the sum of the absolute values of the reactive powers generated with linearized constraints on the dependent variables. A linearprogramming model allows the application of our procedure to a large-size network with about 100 control units. The computational tests performed on the Italian network show some diminution in transmission losses with regard to the day time operation while useless reactive power loops are avoided at night.
The mathematical modelling of the thermal process in an intermittent kiln for ceramic product firing leads to a system of nonlinear partial derivatives equations, agreeably with the geometric and thermodynamic featur...
详细信息
The mathematical modelling of the thermal process in an intermittent kiln for ceramic product firing leads to a system of nonlinear partial derivatives equations, agreeably with the geometric and thermodynamic features of the kiln. The resolution procedure, by means of a finite difference approximation method, leads to an expensive computational time due to the nonlinearities including several etimations steps. The gas flow rate control law in the kiln, allowing the temperature at the core of the charge to reach a diven reference profile, may be iteratively determined by the Regula-Falsi algorithm, in order to minimize a quadratic criterion on the desired temperature. To avoid expensive computational time, we propose an inversion method to directly restore the control law from the reference profile, based on a finite difference algorithm extended from one built for the resolution of the nonlinear inverse heat conduction problem in the charge to be baked. The performances are satisfactory according to a lower computational cost. This paper deals with a short presentation of the simulation model, including a description of the characteristics of the iterative method and the inversion method.
Many energy control systems developed for the steel works have been concerned with on-line monitoring and logging system for energy current. However there have been very few systems developed for the optimal total ene...
详细信息
Many energy control systems developed for the steel works have been concerned with on-line monitoring and logging system for energy current. However there have been very few systems developed for the optimal total energy control of the steel works. There are two reasons for this. One is the problem of correctly forecasting the energy consumption and second is the problem of choosing a practical method for optimal control. This paper deals with both the theoretical and practical solution devised for the above two items at Sumitomo Metal Ind., Ltd. With regard to solving the forecasting problem, we forecast the 24 Hr energy generation and consumption using the Auto Regressive Moving Average model with eXogenous variable (ARMAX), with Kalman Filter. With regard to choosing a practical method for optimal energy control, we use the ”Oradient Method”. We composed the Energy factor as a 96-dimentional ( = 4 items x 24 Hr ) vector ( = X). As a function of vector X we represented the linear restriction of energy balance (∑aijXj≦bi) and the non- linear object function (income and outgo = V(X) ). This optimizes vector X so as to minimize V( X ) under the given condition (∑aijXj≦bi).
As the share of variable renewable energy increases, adequate prices on electricity spot markets become increasingly important as they set signals for scarcity, investment, or demand response. Market prices are derive...
详细信息
As the share of variable renewable energy increases, adequate prices on electricity spot markets become increasingly important as they set signals for scarcity, investment, or demand response. Market prices are derived from the underlying welfare maximization problem. On electricity spot markets, this optimization problem is based on the non-convex and non-linear Alternating Current Optimal Power Flow (ACOPF) model. Since the ACOPF is intractable, electricity markets around the world use a linear approximation, the Direct Current Optimal Power Flow (DCOPF) model. Recent research has led to better non-linear relaxations of the ACOPF. We show that these non-linear relaxations increase welfare and imply significantly lower redispatch costs and side-payments. Most importantly, we show that the price signals obtained from non-linear relaxations are much improved. The DCOPF often yields high price differences between nodes when there is no line congestion in the AC-feasible solution or vice versa. Such biased price signals pose a significant problem in practice as they lead to inefficient demand response, distorted investment signals, and incorrect congestion incomes. The use of non-linear relaxations mitigates this problem and provides an important advantage of the resulting prices over prices based on the DCOPF.
Fuzzy multi-objective programming is an important optimization method to solve many complex practical problems. In this work, the applications of fuzzy multi-objective programming modeling for solving the practical pr...
详细信息
Fuzzy multi-objective programming is an important optimization method to solve many complex practical problems. In this work, the applications of fuzzy multi-objective programming modeling for solving the practical problems in regional water resources optimal scheduling are studied. In order to strengthen the planning and management of water resources, the limited water resources are fully and effectively used scientifically. And because of the multi-objective and uncertainties of the regional water resources optimization scheduling problem, this paper adopts the fuzzy multi-objective programming method to deal with this complex practical problem. Based on the fuzzy multi-objective programming technique, the fuzzy multi-objective nonlinearprogramming model of regional water resources optimal dispatching is established. The multi-objective includes three goals: economic benefit, environmental benefit and social benefit. Then, the establishment and solving steps of the fuzzy multi-objective nonlinearprogramming model are introduced for the established model. Finally, the proposed scheme is evaluated and sorted. Finally, combined with the actual situation of a city to solve, verify the validity of the model.
暂无评论