Probabilistic electric load forecasting: A tutorial review

Optimization Techniques with FORTRAN

The authors recommend standard load models for power flow and dynamic simulation programs. The goal of this paper is to promote better load modeling and advanced load modeling, and to facilitate data exchange among users of various production-grade simulation programs. Flexibility of modeling is an important consideration. For transient stability, longer-term dynamics, and small-disturbance stability programs, the authors recommend the structure of multiple load types connected to a load bus. Load types are static including discharge lighting, induction motors, synchronous motors, and transformer saturation. For each load type, multiple models may be connected to the bus. For longer-term dynamics programs, a model for LTC transformers is also recommended.

Standard load models for power flow and dynamic performance simulation

Short-term load forecasting is an essential instrument in power system planning, operation, and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance planning for the generators. Overestimation of electricity demand will cause a conservative operation, which leads to the start-up of too many units or excessive energy purchase, thereby supplying an unnecessary level of reserve. On the other hand, underestimation may result in a risky operation, with insufficient preparation of spinning reserve, causing the system to operate in a vulnerable region to the disturbance. In this paper, semi-parametric additive models are proposed to estimate the relationships between demand and the driver variables. Specifically, the inputs for these models are calendar variables, lagged actual demand observations, and historical and forecast temperature traces for one or more sites in the target power system. In addition to point forecasts, prediction intervals are also estimated using a modified bootstrap method suitable for the complex seasonality seen in electricity demand data. The proposed methodology has been used to forecast the half-hourly electricity demand for up to seven days ahead for power systems in the Australian National Electricity Market. The performance of the methodology is validated via out-of-sample experiments with real data from the power system, as well as through on-site implementation by the system operator.

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Short-Term Load Forecasting Based on a Semi-Parametric Additive Model

In this paper, a load flow calculation method for ill-conditioned power systems is developed. The proposed method is very simple, has no mathematical approximations, and requires almost no additional storage and computation time when incorporated into the normal Newton-Raphson program. Using the method, the load flow solution never diverges, and also the existence of the solution from the initial estimate can be easily judged. To examine the effectivenesst two ill-conditioned power systems, i.e., 11 and 43 bus systems are studied by the method, and it is found that the solution does not exist for the 11 bus system though the given data are said to be operational, and also that the solution does exist for the 43 bus system but does not converge with the single precision due to the precision deficiency of the computer.

A Load Flow Calculation Method for III-Conditioned Power Systems

One of the most recognized load flow methods at present is the N-R(Newton-Raphson) method [1] with the sparsity techniques and suboptimal ordering [2]. This paper presents a new AC load flow method which is several to more than ten times faster than the N-R method and has the same memory requirement, mathematical complexity and accuracy as the N-R method. As an example, the convergence time for 118 bus system was only one eighth of the N-R method.

A Fast Load Flow Method Retaining Nonlinearity

The authors investigate the voltage stability problem based on singular perturbation theory. Possible voltage instability patterns are classified into four types (I, II-1, II-2S, and II-2D) according to the mechanism causing voltage instability. Several features of each type of instability are studied as well as their analysis methods. Voltage instability tends to begin with type I and then leads to one of the remaining types. The load flow Jacobian can be an effective index to approximately assess type I and II-2S instabilities, while types II-1 and II-2D require direct nonlinear analyses and eigenvalue analyses, respectively. The validity of the classification proposed has been verified through numerical simulations and theoretical analyses which take into account dynamic characteristics of generating units, loads, and tap-changing transformers. >

An investigation of voltage instability problems

Interval prediction of annual maximum demand using grey dynamic model

This paper describes a new computational approach to the problem of the most economical operation of hydraulic plants in electric power systems, employing L. S. Pontryagin's maximum principle. The economical operation of a simplified model system is treated and the long range operation of a multireservoir system is considered. The relaxation method is successfully applied to the solution of optimal water usage policy in a model system of two reservoir-type and three regulating pondage-type hydraulic plants, with one equivalent thermal plant. Comparison is made between the maximum principle approach and dynamic programming. It becomes evident that the maximum principle is a powerful tool not only for the treatment of engineering problems, such as time-minimal control of servomechanisms, but also as a new technique of mathematical programming for the treatment of problems in mathematical economics.

Yasuo Tamura

Papers

A Fast Load Flow Method Retaining Nonlinearity

An investigation of voltage instability problems

Interval prediction of annual maximum demand using grey dynamic model

An Application of the Maximum Principle to the Most Economical Operation of Power Systems

On the multiple solution structure, singular point and existence condition of the multiple load-flow solutions.