Masakazu Kanezashi

Normal State Optimal Load Allocation in Distribution Systems

This paper addresses a subproblem related to distribution automation. It outlines an algorithm and presents computer results for minimizing the losses in a loop distribution system based on the remote operation of sectionalizing switches on feeders interconnecting different substations. The minimization is carried out subject to the voltage-drop, line-capacity and substation-capacity constraints. Computational experience with a system of realistic size indicates that the procedure proposed here is valid and effective in practical operations.

An efficient algorithm for load balancing of transformers and feeders by switch operation in large scale distribution systems

A systematic and practical algorithm for load balancing of transformers and feeders by automatic sectionalizing of switch operation in large-scale distribution systems of the radial type is discussed. The algorithm is developed by extending an approximation for load transfer of the desired two transformers. The algorithm is applicable to operations not only in the normal state, but also in the scheduled and failure outage states. Computational experience on a real large-scale system has indicated that the algorithm is valid and effective for practical operations. >

Outage State Optimal Load Allocation by Automatic Sectionalizing Switches Operation in Distribution Systems

This paper presents a systematic and practical algorithm for load transfer by automatic sectionalizing switch operation in distribution systems at a fault occurrence subject to the transformer-capacity constraints and the line-capacity constraints on condition that all the section loads are estimated. The algorithm is developed by introducing the concept of subset sum problem and network structure. Computer experience with a real system indicates that the algorithm proposed here is valid and effective for practical operations.

Optimal long-term unit commitment in large scale systems including fuel constrained thermal and pumped-storage hydro

This paper is concerned with a method for solving a long-term unit commitment problem, which is to find the commitment schedule and the operating level of all generators at each time in each day. The large scale power system treated here is composed of the following three types of units: 1) usual oil-burning thermal, 2) fuel constrained LNG/LPG-burning thermal and 3) pumped-storage hydro. In the following, these three types of units are respectively abbreviated to thermal units, LNG units and hydro units. In power systems, the peak demand occurs in the daytime and the off peak in the nighttime, and the demand on Saturday and Sunday is comparatively smaller than that on weekdays. It is therefore most economical and effective for the operation of hydro unit to pump up water during light load periods on Saturday, Sunday or in the nighttime on weekdays, and to generate power during heavy load periods on weekdays. As for LNG units, since the fuel amount decided by a long-term contract is filled up into a tank at regular intervals, the fuel consumed by LNG units is restricted over the given time horizon (usually during one week to one month). Because of the characteristics of such various power resources, it is necessary to formulate a unit commitment as a long-term problem over one week to one month. Up to this time, many approaches have been proposed to solve the unit commitment problem. These approaches can be classified into the following four types: 1) Branch and bound method, 2) Dynamic programming, 3) Priority ordering and 4) Lagrangian relaxation method. Recently, the Lagrangian relaxation method to solve the unit commitment problem have been studied by many researchers; for example, see [1]. The method makes available the dual problem to be decomposed into single generator subproblems by using Lagrange multipliers. In Ref. [2], the authors proposed the solution method for the daily unit commitment including various power resources. For solving the dual problem defined by the Lagrangian relaxation method, the variable metric method was employed instead of the traditional subgradient method. The variable metric method has a distinctive feature in that it can prevent the solution from oscillating near the dual maximum. However we cannot simply apply the method for the daily unit commitment to the long-term one. This is because the Hessian inverse, which plays a chief role in the variable metric method, becomes very large and dense. As a result, it takes a lot of memory space. Furthermore, the generated solution becomes numerically unstable as the Hessian inverse becomes large scale. For overcoming these defects, the authors developed a new method, in which a block diagonal structure of the Hessian inverse is utilized in updating the metric matrix. Since the unit commitment problem (primal problem) is formulated

Voltage crop constrained restoration of supply by switch operation in distribution systems

An algorithm is presented for power system load transfer by remotely-controllable switch operations in distribution systems when a fault occurs. In view of practical use, the authors consider both the current capacity and voltage-drop constraints of this load transfer algorithm. Taking these constraints into consideration, the loads in an out-of-service area are transferred to the transformers in an adjacent area. Since it is possible to reduce the out-of-service area monotonically by switch operation, the algorithm proposed is of practical importance. The algorithm is tested for large-scale real distribution system. The numerical results indicate that the algorithm is valid. >

A Modified Newton Method For Optimal Power Flow Using Quadratic Approximated Power Flow

In general, the Han-Powell algorithm is evaluated as the fastest and the most reliable method for small nonlinear programming problems. However, it has one serious disadvantage when applied to a large scale problem such as an optimal power flow. This disadvantage stems from its use of non-sparse approximations to certain Hessian matrices. We propose a modified Newton method to eliminate this disadvantage. Sparsity of the Hessian is maintained by this method, and it can be modified to be a non-negative definite matrix in accordance with simple procedutes. This can be implemented using quadratic approximations of power flow equations. Numerical tests on a real system show the validity of the proposed method.

Setting planned lead times for multi-operation jobs

Abstract This paper deals with the problem of how to assign planned lead times for multi-operation jobs. The standpoint of the paper is that planned lead times should be determined, based upon a management policy concerning a tradeoff between work-in-process quantities in a shop and capacity requirements variations on a bottleneck machine. A method of determining a planned lead time for a multi-operation job is proposed, through analyzing average loading times in a shop and capacity requirements variations on a bottleneck machine. The lead time is determined on the basis of the jobs total operation time in a shop. Poisson job airival to a shop and periodic loading are assumed. The method is derived with Lagranges method of indeterminate coefficients. It can minimize capacity requirements variations on a bottleneck machine under a given average loading time in a shop.

Makespan comparison between resequencing and switching in a dynamic manufacturing environment

Abstract Makespan performance capabilities, using dispatching, fixed sequencing, resequencing and switching as a scheduling approach, are compared in a general job shop setting. Switching is defined as an approach that changes fixed sequencing to dispatching, considering the manufacturing status. Two stages of simulation experiments were conducted under several intensity levels of machine breakdown occurrences and rush job arrivals. The first experiment clarifies that resequencing is superior to fixed sequencing and that switching is superior to dispatching. The second experiment, comparison between resequencing and switching, indicates that switching can dominate resequencing with no short re-sequencing intervals under high disturbance intensity levels.

Power generation scheduling by neural network

A new method for solving a power generation scheduling problem in an electric power system is presented. The objective is to determine the hourly start-up/ shut-down schedules of all generators so that forecasted hourly power demands per day may be met and total operating costs, the sum of setup and fuel costs for a given day, may be minimized. The problem may be formulated as a large-scale combinatorial optimization problem which includes 0-1 variables representing the start-up/shut-down of generators and continuous variables representing the power outputs. Determination of an optimalsolution within practical time limits is consequently difficult. Until now, the lagrangian relaxation method has been studied as it appeared to be the most practical method for obtaining an approximate solution to the problem. The efficiency of this method, however, depends on how the Lagrange multipliers are determined. Here, it is proposed that the Lagrange multipliers be estimated by utilizing the neural network and resul...