Non-sequential Monte Carlo Simulation Research Articles

Composite Reliability Assessment Based on Monte Carlo Simulation and Artificial Neural Networks

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents a new methodology for reliability evaluation of composite generation and transmission systems, based on nonsequential Monte Carlo simulation (MCS) and artificial neural network (ANN) concepts. ANN techniques are used to classify the operating states during the Monte Carlo sampling. A polynomial network, named Group Method Data Handling (GMDH), is used, and the states analyzed during the beginning of the simulation process are adequately selected as input data for training and test sets. Based on this procedure, a great number of <emphasis emphasistype="boldital">success</emphasis> states are classified by a simple polynomial function, given by the ANN model, providing significant reductions in the computational cost. Moreover, all types of composite reliability indices (i.e., loss of load probability, frequency, duration, and energy/power not supplied) can be assessed not only for the overall system but also for areas and buses. The proposed methodology is applied to the IEEE Reliability Test System (IEEE-RTS), to the IEEE-RTS 96, and to a configuration of the Brazilian South-Southeastern System. </para>

A Framework to Implement Supply and Demand Side Contingency Management in Reliability Assessment of Restructured Power Systems

This paper presents a framework to implement supply and demand side contingency management in the reliability assessment of hybrid power markets. A model for the independent system operator (ISO) to coordinate reserve and load curtailment bids for contingency states is introduced to balance reliability worth and reliability cost. The load curtailments and generation re-dispatch for a contingency state are determined based on minimizing the market interruption cost using an optimization technique. A nonsequential Monte Carlo simulation technique based on this framework has been proposed to evaluate the customer reliability of restructured power systems with the hybrid market model. The modified IEEE Reliability Test System (RTS) is used to illustrate the proposed technique

Well-Being Analysis for Composite Generation and Transmission Systems

This paper presents a new approach to evaluating the health of composite generation and transmission systems. A well-being framework is used to classify the system states into healthy, marginal and at risk, according to a pre-defined deterministic criterion. In order to combine deterministic and probabilistic concepts, the proposed methodology uses a nonsequential Monte Carlo simulation, a multilevel nonaggregate Markov load model and new test functions to estimate the well-being indices. These test functions are based on an estimating process, designated as the one-step forward state transition, which is very flexible and efficient. Case studies on the IEEE-RTS (Reliability Test System) and on a modification of this system are presented and discussed.

A Practical Approach for Integrated Power System Vulnerability Analysis With Protection Failures

Protection system failure is one of the main causes of cascading outages. This paper proposes an integrated scheme to study power system vulnerability considering protection system failures. In this scheme, both adequacy and security based reliability analysis are conducted. A new protection system reliability model including two major failure modes is established to demonstrate their effects on power system reliability. The mechanism and scheme of protection systems have been analyzed for their contribution to cascading outages as well as system stability after a fault occurs. All contingencies and the responses in the power system are depicted in their inherent stochastic manner. The power system vulnerability is assessed by both adequacy indices, such as Bus Isolation Probability (BIP), Loss of Load Probability (LOLP) and Expected Power Loss (EPL), and the security index Probability of Stability (POS). In addition, a new vulnerability index, Integrated System Vulnerability (ISV), is introduced to give a more comprehensive description of the system vulnerability. A nonsequential Monte Carlo simulation approach is used to implement the stochastic properties of contingencies, protective response and protection system failures. The IEEE Reliability Test System is used to illustrate the methodology and present the results.

Modelagem de cargas variantes no tempo na avaliação de confiabilidade composta via simulação Monte Carlo não-seqüencial

Este artigo apresenta uma nova metodologia para avaliar a confiabilidade de sistemas compostos de geração e transmissão considerando cargas variantes no tempo. Baseado na simulação Monte Carlo não-seqüencial, o método proposto utiliza um modelo de Markov capaz de representar diferentes padrões cronológicos de carga para cada área ou barra do sistema. Um novo processo de estimação é proposto para avaliar o índice de freqüência de corte de carga (LOLF - loss of load frequency), sem a necessidade de presumir comportamento coerente para o sistema. Exemplos utilizando os sistemas MRTS (Modified IEEE Reliability Test System) e SSB (Sul-Sudeste Brasileiro) são apresentados e discutidos.

Evaluation of transfer capabilities of transmission systems in competitive environments

The main objective of this work is to propose a new methodology to determine the best points in the system to add reinforcements of the transmission network and to add new agents (sellers and buyers), in order to maximize the available transfer capability (ATC), without violating a pre-established reliability level. In the process, the ATC probability density function is determined considering uncertainties from equipment unavailabilities. The proposed algorithm uses Non-sequential Monte Carlo simulation to select system state and Linear Programming with a DC Power Flow model to analyze and optimize each selected state. The IEEE reliability test system is used to illustrate the methodology.

Probabilistic criteria for power system expansion planning

This paper presents a new methodology to power system expansion planning using probabilistic criteria. A selecting process for capturing the best expansion alternatives is proposed bearing in mind the application of different reliability evaluating models, which follow a hierarchical procedure. The state enumeration technique and the non-sequential Monte Carlo simulation are utilized basically as filters. The pseudo-chronological Monte Carlo simulation is then used to evaluate, in detail, the expansion costs of the previously selected alternatives. The major contribution is to show how traditional procedures and criteria should be adapted to the new competitive environment, where the minimum cost expansion planning has to be achieved considering the reliability worth. An expansion study of the MRTS-modified IEEE reliability system is carried out in order to demonstrate the efficiency of the proposed methodology.

Pseudo-chronological simulation for composite reliability analysis with time varying loads

This paper presents a new methodology to evaluate loss of load indices, with particular emphasis on LOLC (loss of load cost) assessment, for composite generation and transmission systems considering time varying loads for different areas or buses. The proposed approach, named pseudo-chronological simulation, retains the computational efficiency of nonsequential Monte Carlo simulation and the ability to model chronological load curves in sequential simulation. It considers the actual blocks of unsupplied energy per consumer class, per bus, and the respective duration, to accurately characterize the interruption process. Case studies on the IEEE-MRTS (Modified Reliability Test System) and the BSS (Brazilian South-Southeastern System) are presented and discussed.

Bus-based reliability indices and associated costs in the bulk power system

This paper presents a methodology to evaluate the reliability and to calculate interruption costs at the load bus level in the bulk power system (Hierarchical Level II). The method is based on a nonsequential Monte Carlo simulation combined with a linear optimization model in which the load at every bus is represented by two components, a firm and a nonfirm (curtailable) portion. Expected values of not served energy (EENS), not served demand (EPNS) and loss of load probability (LOLP) are computed for the whole system (global indices) as well as for each load bus. The paper includes a sensitivity analysis taking into consideration variations of the indices due to factors such as interruption costs and load shedding policies. In a number of countries the evaluation of bus-based reliability indices has become a key component in the negotiation of supply contracts in the open access environment. The same indices are useful to assess the reliability of the supply at the delivery point to both distribution utilities and large industrial customers.

Application of chronological load modeling in composite reliability worth evaluation

This work describes the application of pseudo-sequential Monte Carlo simulation to the composite generation—transmission reliability evaluation of the Brazilian South-Southeast system using chronological load modeling. The resulting reliability indices, in particular the loss of load cost (LOLC), were compared with those produced by a sequential Monte Carlo scheme with chronological load model and by a non-sequential Monte Carlo simulation scheme using a multistate Markov load model. It is shown that the pseudo-sequential approach produced the same indices as the sequential approach, with a substantial reduction of computational effort. Those results were in turn quite different from the non-sequential Monte Carlo scheme, thus confirming the importance of an accurate load modeling.

Frequency and duration calculations in composite generation and transmission reliability evaluation

The authors present a new methodology for frequency and duration (F&D) assessment in composite generation and transmission reliability evaluation. The F&D indices are obtained from a nonsequential Monte Carlo simulation scheme. Computational effort is reduced by using the Lagrange multipliers associated with the adequacy assessment of each state to identify the boundary wall between failure and success states. The methodology is illustrated in case studies with the IEEE test system and two utility-derived systems. The proposed approach allows the practical application of F&D indices in integrated generation/transmission planning studies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>