Operation Planning Of Power Systems Research Articles

The impacts of temperature forecast uncertainty on Bayesian load forecasting

This paper presents a short-term load forecast methodology that is suitable for power system operational planning studies. Bayesian estimation is use to predict multiple step ahead peak forecasts using peak and average temperature forecasts as explanatory variables. Herein, the forecast model is developed and illustrated in a case study with utility-derived power system data. Special attention is given to the practical issue of forecasting the electrical load with imperfect weather information.

Improving Lagrangian relaxation: an application to the scheduling of pressurized water reactor outages

This paper presents an improvement of Lagrangian relaxation techniques that are now widely used for optimizing the operational planning of power systems. It is a precise algorithm for maximizing the concave and nondifferentiable dual function: a proximal point algorithm. This algorithm is applied to an important operational planning problem: the scheduling of pressurized water reactor nuclear power plant outages. Compared to the more classical Uzawa algorithm, numerical examples show that the proximal algorithm significantly improves both the solutions and the indicators of their quality.

Neural network based estimation of maximum power generation from PV module using environmental information

This paper presents an application of an artificial neural network for the estimation of maximum power generation from PV module. The output power from a PV module depends on environmental factors such as irradiation and cell temperature. For the operation planning of power systems, the prediction of the power generation is inevitable for PV systems. For this purpose, irradiation, temperature and wind velocity are utilized as the input information to the proposed neural network. The output is the predicted maximum power generation under the condition given by those environmental factors. The efficiency of the proposed estimation scheme is evaluated by using actual data on daily, monthly and yearly bases. The proposed method gives highly accurate predictions compared with predictions using the conventional multiple regression model.

Improving Feeder Voltage Calculation Results with Telemetered Data

A method that uses uncertain network data, load distribution information and telemetered data for feeder voltage profile calculation is proposed in this paper. In the proposed method, data involved in the calculation are represented by using fuzzy numbers. All possible feeder voltage solutions within bounds obtained from fuzzy arithmetic are considered. The mean values of the obtained intervals are useful for power system operation planning, and lower and upper bounds can be used to alert dispatchers for possible system deterioration. Measurements are included in the calculation to reduce the uncertainty of the obtained results. The voltage calculation method is used to evaluate the measurement configuration and a meter placement scheme is proposed to select the locations of new meters from the standpoint of minimizing the uncertainties of the calculated voltage profile.

Improving feeder voltage calculation results with telemetered data

A method that uses uncertain network data, load distribution information and telemetered data for feeder voltage profile calculation is proposed in this paper. In the proposed method, data involved in the calculation are represented by using fuzzy numbers. All possible feeder voltage solutions within bounds obtained from fuzzy arithmetic are considered. The mean values of the obtained intervals are useful for power system operation planning, and lower and upper bounds can be used to alert dispatchers for possible system deterioration. Measurements are included in the calculation to reduce the uncertainty of the obtained results. The voltage calculation method is used to evaluate the measurement configuration and a meter placement scheme is proposed to select the locations of new meters from the standpoint of minimizing the uncertainties of the calculated voltage profile.

Superfast autoconfiguring artificial neural networks and their application to power systems

Abstract This paper presents the new generation of artificial neural netoworks (ANNS) for solving the task of power system operation planning. Today the error back-propagation ANNs are used most because of their simplicity and the possibility of parallel implementation on neuro-computers for high-speed execution. In spite of their popularity they have two major drawbacks: the learning process is time consuming and there is no exact rule for setting the number of neurons to avoid overfitting or underfitting and to achieve, hopefully, a converging learning phase. To avoid these difficulties, a new generation of ANNs has been developed based on the theory of radial basis functions for approximations. A comparison test on an actual problem in power system operation was performed. The results show that this new algorithm is superior to back-propagation ANNs and optimal configured back-propagation ANNs achieved with genetic algorithms.

PV-SMES システムを含む系統の最適運用計画

PV-SMES システムを含む系統の最適運用計画

Short term operation and power exchange planning of hydro-thermal power systems

This paper considers a unified problem of short-term operation planning and power exchange scheduling of large hydro-thermal power systems including: unit commitment, hydro power plant operation planning, pumped-storage hydro power plant operation planning and scheduling of power exchange with other power utilities. The criterion function is the total variable profit incurred by energy production, sales of energy to the users inside the power system, sales of energy to other power companies and purchase of energy from them, or from other sources. The overall problem is solved using the Lagrangian relaxation method. A decomposition technique is applied to solve the dual (mixed-integer) and primal (continuous programming) problem. Dynamic programming, feasible direction method and linear programming method are used for the solution of subproblems. The results of the application of the method to a numerical example are given. >

電源・運用計画の多目的性と不確定性 新環境下における計画手法

電源・運用計画の多目的性と不確定性 新環境下における計画手法

Operational Planning of Power System: An Integrated Approach

Abstract Power system operational planning to utilize the existing capacity in the best possible manner is of prime importance and is particularly relevant in a developing economy. This modeling exercise presents an integrated approach for the multiarea short-term operational planning of the power system. It considers various related activities like coal mining, transportation, generating unit maintenance and generation scheduling, demand-side management options, and unmet energy distribution among different areas in case of inadequate system capacity. The power system operations are required to meet multiple objectives, namely minimizing the total costs, minimizing the total emissions, and maximizing the generating system reliability (minimizing the loss of load expectation). A compromise programming approach is adopted to arrive at the best compromise among these noncompensatory objectives. Thus it is a systems approach to power system planning that uses a multiobjective framework to integrate all related activities in system operation. Finally, a number of potential applications of the model for policy analysis purposes have been suggested.

Power System Operation Planning for Demand and Supply

Power System Operation Planning for Demand and Supply

Improvement of electric power system load forecasting and operational planning for control automation

Methodological approaches to solving long-term and short-term electrical power system and interconnected power system load-forecasting and operational planning problems existing in the USSR are described, as well as information and system technological aspects of these problems. The present state of the art and future directions of methodological and program elaborations in this field are also considered.

Optimal preventive maintenance scheduling of thermal generating units in power systems —A survey of problem formulations and solution methods

Preventive maintenance scheduling of thermal generating units occupies a significant place in power system operation and expansion planning; at the same time it is a challenging optimization problem. The purpose of this paper is to analyse essential features of the maintenance scheduling problem, including imposed constraints and various objectives, as well as to present the results of the research work done in this field using operational research methods. Papers published during last fifteen years are discussed, with special regard for the applied optimization techniques.

Network Simplex Method Applied to AC Load-Flow Calculation

Operational research methods, and particularly flow and transportation methods have many applications in the power system field: optimization of hydroelectric power system operation, seasonal or short-time planning of a hydro-thermal system and finally power system security. The purpose of this paper is to specify the network simplex method of the load-flow calculation in a power system. This study is not limited to the DC-flow calculation but particularly presents a model for the full AC load-flow calculation. The proposed model is an imaginary and real current one. It is based on a simplifying assumption which will allow decoupling of the problem and which is the basis of the algorithm called FLF (Flow Load-Flow algorithm). Power system elements such as lines, transformers, generators and voltage control busses are represented with adapted models. Systematic tests have been performed on some existing power systems, such as the IEEE 24-bus Reliability system. The performance of this method is compared with the results of a decoupled Newton-Raphson load-flow. The accuracy of the FLF algorithm is competitive with the Newton-Raphson method, but its speed still has to be improved. However the load-flow calculation is only a part of the power system security problem, where properties and characteristics of flow and transportation algorithms will offer greater perspective.

Optimal Short Term Operation Planning of a Large Hydrothermal Power System Based on a Nonlinear Network Flow Concept

Optimal Short Term Operation Planning of a Large Hydrothermal Power System Based on a Nonlinear Network Flow Concept

Application of Decomposition Techniques to Short-Term Operation Planning of Hydrothermal Power System

Application of Decomposition Techniques to Short-Term Operation Planning of Hydrothermal Power System

Application of Decomposition Techniques to Short-Term Operation Planning of Hydrothermal Power System

This paper develops a realistic model for short-term operation planning of a large scale hydrothermal power system with a high share of hydro. This problem is a large scale mixed integer program. Benders' method is employed to decompose the problem with respect to integer and continuous variables. The master problem of this method contains only integer variables and considers the unit commitment of thermal plants. The subproblem includes only continuous variables and considers the economic dispatch problem. The special structure of master and subproblems are further exploited which results in considerable reductions in the size of the problem and computation time requirement.

Optimal Short Term Operation Planning of a Large Hydrothermal Power System Based on a Nonlinear Network Flow Concept

This paper presents a procedure for solving the short term generation scheduling problem for a large hydrothermal system that includes transmission limitations. The integrated system is divided into a hydro and a thermal subsystem. A reduced gradient algorithm is employed for the solution of the hydro subproblem. This algorithm is specialized to efficiently solve nonlinear network flow problems with additional constraints of non-netwrk type. The thermal subsystem is solved using a fast unit commitment and dispatch algorithm. A case study with the Swedish system is discussed.

A Stochastic Model for Mid-Term Operation Planning of Hydro-Thermal Systems with Random Reservoir Inflows

The operation planning of a hydro-thermal power system involves the coordination of the production schedule of various types of generation, including hydro. A good model is needed to minimize the system energy production costs over a given period in the mid-range time frame. A method is proposed to optimize the discharge of the hydro reservoirs over the period of one year. Explicit Stochastic Dynamic Programming (ESDD) [1] is employed to deal with the M-stage stochastic return function, the random inflows to the reservoirs and the bounded nature of the system constraints. Aggregation of the reservoir and hydro plant sub-systems is used to reduce the dimensionality of the problem, permitting a; realistic modeling of the hydro portion of the power system. The cost of operation for various valve loadings, the scheduled downtime for various unit maintenance activities, the predicted partial and total forced outages, and the stochastic river inflows to the reservoirs are input requirements to the program which yields the monthly hydro energy scheduling for the most economic loading over a one year period