Autonomous system expansion planning considering renewable energysources-a computer package

The authors describe the interactive package ASP (Autonomous System Planning), which determines the optimal expansion plan of an autonomous generation system including diesel units, wind generators, and photovoltaic generators. Utilizing meteorological data, load demand data and estimated economical parameters, the package finds the optimal system expansion policy for a period of N years. The solution algorithms implemented in the package recognize planning and operational constraints and take into consideration the stochastic nature of the meteorological conditions, loads, and the availability of the diesel units     

Optimum expansion planning of an unconventional generation systemoperating in parallel with a large scale network

A package for the long-term optimal expansion planning of a generation system with renewable energy sources operating in parallel with a large-scale network is presented. The algorithm utilizes meteorological data, load demand data, and estimated economical parameters and determines the candidate plans for the expansion period. A forward dynamic programming algorithm is utilized to determine the optimal plan. Results from the application of the method to a local grid are presented     

A tool for the evaluation and selection of state estimatormeasurement schemes

This paper describes an approach for evaluating and selecting the measurement scheme for power system state estimation. The approach utilizes a computer package which has been developed for analyzing all the power system state estimation related functions. In the proposed approach the measurement configuration is selected so that the following criteria are met: measurement system observability and reliability, bad data detectability and identifiability, state estimation accuracy. The necessary algorithms to analyze the above criteria are described     

Transformer tap setting observability in state estimation

In conventional state estimation, transformer tap settings are treated as fixed network parameters. This may reduce the accuracy of state estimation algorithm, when a tap measurement is in error or an unmeasured tap is unknown. This paper presents a numerical observability analysis algorithm for a state estimation model which treats transformer tap settings as state variables and provides for turns ratio and phase-shift angle measurements. The proposed model is transformed to a conventional node frame of reference, by introducing one fictitious bus and one fictitious branch for each transformer with tap estimation enabled. For an unobservable system, observable islands are determined and additional measurements are directly provided for placement. Test results are presented.     

An Interactive Package for Risk Evaluation and Maintenance Scheduling

The calculation of the Loss of Load Probability (LOLP) is an important element in generation planning studies. LOLP is calculated either independently to evaluate the risk of a certain generation system or in conjunction with several planning application programs such as, generator maintenance scheduling, probabilistic production costing, hydrothermal scheduling, generation expansion, etc. Exact calculation of the LOLP requires the calculation of the Capacity Outage Probability Table (COPT). This table takes into consideration the capacity rating the the forced outage rates of the generating units of the system and it provides the probability values associated with various amounts of system capacity on outage. The capacity outage table is calculated by utilizing the well known recursive convolution formula. Usually the table is simplified by rounding the capacity outage table to selected discrete capacity levels. The size of the round off increment depends on the desired accuracy. The classic approach is time consuming and requires a considerable amount of computer memory. In order to reduce the computational time and computer storage several methods have been proposed, in which the capacity outage probabilities are approximated with analytic continuous probability distributions. Most of these methods utilize the Central Limit Theorem, Fourier techniques and the Gram Charlier's expansion. Closely related to the LOLP is the maintenance scheduling problem. Preventive maintenance is required for all generating units in order to reduce the probability of capacity shortage and improve the overall reliability of the power system.     

A reduced model for power system observability: analysis andrestoration

An algorithm for observability analysis and restoration in power system state estimation is presented. The problem of P-δ, Q-V and complete observability is addressed. In the proposed algorithm, groups of buses are represented by supernodes and the problem of observability analysis and restoration is examined with a reduced network. The proposed algorithm is easily implemented and it is independent of the state estimation solution algorithm. In case of unobservability, the proposed methodology identifies directly the maximal islands and determines the number and the placement of the required pseudomeasurements for observability restoration. Results from several test cases are presented     

A reduced model for bad data processing in state estimation

A reduced model theory for bad data processing is proposed which utilizes the concept of error residual spread areas. Based on the reduced model theory, statistical indices can be defined for each error residual spread area, and therefore existing detection and identification techniques can be applied separately for each error residual spread area. In this way, errors can be isolated in smaller regions of the system, making it possible to avoid the search for bad data in the global system. Results from several test cases on power systems show the effectiveness and robustness of the method     

Power system remedial action methodology

The authors address the problem of remedial-action computations for the purpose of alleviating overloads, abnormal voltages, etc. The method is based on a linear programming (LP) approach. Applications for voltage/reactive-power control, discrete capacitor/reactor switching, load transfer, and interchange control are considered. The method is optionally based on a DC or AC network model. It utilizes a number of innovations to yield an efficient computational procedure. The major innovations are: a procedure for determining coherent constraints which results in a fast identification of active constraints, fast linearization procedures for active constraints, procedures to define the region of validity of the linearized model, and a fast sparsity-coded LP algorithm. The performance of the method for large power systems is evaluated     

A decision tree method for on-line steady state security assessment

In this paper the application of an inductive inference method to online steady state security assessment of a power system is proposed. For each contingency a number of decision rules in the form of a decision tree (DT) is built offline from a preclassified learning set consisting of operating points of the system. For the real time application of the method the DTs corresponding to the foreseen contingencies are searched online to provide optimal guidelines for preventive control of the system. The algorithm developed is applied to the steady state security assessment of a realistic model of the Hellenic interconnected power system comprising 240 busbars, 270 branches, 57 transformers and 30 equivalent generators