L.A.F. Manso

Chronological Power Flow for Planning Transmission Systems Considering Intermittent Sources

In light of the additional needs imposed by high penetration level of renewable sources on the planning of electric networks, this paper introduces new models and procedures for obtaining more robust and flexible networks. A new methodology, computational algorithm, and a new set of performance indices are presented based on the concept of chronological power flow (CPF). In view of the presence of intermittent energy resources, aspects related to the operation of the system during moments of high energy availability will be duly evaluated, since that is when there might be a waste of renewable energy, and also during low renewable production conditions, when the system may be more fragile. The results obtained for the IEEE Reliability Test System-1996 will also be presented and discussed.

Comparison of alternative methods for evaluating loss of load costs in generation and transmission systems

This paper presents a comparison among different methods to evaluate the loss of load cost (LOLC) index for composite generation and transmission systems. A new methodology is proposed and used as a reference to evaluate LOLC indices. It considers all blocks of unsupplied energy per consumer class, per bus, and the respective duration, to characterize accurately the interruption process. The proposed methodology is implemented with two composite reliability evaluation algorithms based on Monte Carlo simulation: sequential and pseudo-sequential. Also two load curtailment policies, minimum load curtailment and minimum cost, are considered and their impact on the different LOLC evaluation methods assessed. Case studies with the IEEE-MRTS (modified reliability test system) are presented and discussed.

Reliability assessment of time-dependent systems via quasi-sequential Monte Carlo simulation

This paper proposes a new methodology to assess system reliability considering time-dependent power sources and loads. Based on a non-sequential Monte Carlo simulation (MCS), the proposed method uses a multilevel non-aggregate Markov model to represent different chronological load patterns per area or bus. As a result, the fluctuation of generating capacities, a characteristic of renewable energy sources, can be duly captured by the proposed methodology. Comparisons with the chronological MCS are carried out using the IEEE-RTS-96 (Reliability Test System) and modifications of this system that include renewable sources. The results are deeply discussed.

Transmission expansion planning: A discussion on reliability and “N−1” security criteria

This paper proposes a methodology to solve the multi-stage transmission expansion planning (TEP) problem based on metaheuristic optimization techniques, as load and generation evolve. A discussion on how to consider security criteria using the well-known deterministic “N−1” approach and the probabilistic reliability-based method is presented through a case study system.

Evolution Strategies to Transmission Expansion Planning Considering Unreliability Costs

This paper presents a new methodology to solve transmission expansion planning (TEP) problems based on evolution strategies (ES), but other heuristics are also used to assist the search process. The TEP problem includes the search for the least cost solution, bearing in mind investments and interruption costs. Unreliability costs are considered through the index LOLC-loss of load cost. Moreover, the dynamic nature of the TEP is accounted for by the proposed methodology. Case studies on a small test and on a real sub-transmission network (CEMIG Company, Brazil) are presented and discussed

Optimal outage scheduling—example of application to a large power system

In this paper, we are looking at an example of an application to the Ontario system of the newly developed models for measuring the impact of maintenance strategies on the system reliability and on the associated costs. We describe a maintenance model and associated computer software that looks at the chronology of maintenance requests and captures several important aspects of a large power system behavior. Specific situations involving maintenance and repair outages are considered. In order to measure the performance of a given maintenance request, a strategy based on incremental costs has been proposed. These costs account for variations in production, revenues and reliability caused by maintenance schedules. Although, they are all random variables, the emphasis is placed on the interruption costs, and loss of potential revenue, i.e. the reliability worth. An important contribution of this paper lies in the application of sophisticated reliability concepts to a large real power system.

Generator maintenance scheduling to maximize reliability and revenue

In this paper, attention is focused on measuring the impact of generating maintenance strategies on the system reliability and on the associated costs. The paper describes a maintenance model that captures accurately the beginning and the end of all maintenance scheduling requests. Specific situations involving maintenance and repair outages are considered. In order to measure the performance of a given maintenance request, a strategy based on incremental costs has been proposed. These costs account for variations in production, revenues and reliability caused by maintenance schedules. Several numerical examples, using a modification of the IEEE Reliability Test System, are presented and the corresponding results are analyzed in detail.

Optimum load shedding strategies in distribution systems

This paper investigates the impact of load shedding strategies on distribution system reliability cost indices, due to capacity deficiency conditions caused by unscheduled outages in the bulk-generation and transmission (G&T)-system. First, an integrated adequacy evaluation, including generation, transmission and distribution, is performed in order to provide detailed information on the interruptions experienced by the distribution customers. The G&T system is represented by a fictitious equivalent network, whose parameters are obtained by Monte Carlo nonsequential simulation. The equivalent G&T network is then connected with the distribution network and analyzed using minimal cut-set theory. The next step is the assessment of the reliability performance of the distribution system considering different load shedding priorities among feeders. The best strategy should account not only for the interruption costs but also for the traditional distribution indices (e.g. SAIFI, CAIDI etc.) imposed to the companies by the regulatory legislation. The proposed methodology is applied to a hybrid system created from two standard test systems. The results and their potential applications in the new power system competitive environment are discussed.

Application of Monte Carlo Simulation to Well-Being Analysis of Large Composite Power Systems

This paper presents a new methodology to evaluating the well-being indices of large 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 non-sequential Monte Carlo simulation, a multi-level non-aggregate Markov load model and test functions to estimate the well-being indices for the system and load buses. Moreover, a network reduction is also proposed to find an equivalent well-being framework suitable to practical large power systems. Case studies on an IEEE standard system and on a configuration of the Brazilian network are presented and discussed

Transmission Expansion Planning: A Methodology to Include Security Criteria and Uncertainties Using Optimization Techniques

Transmission expansion planning (TEP) is a complex optimization task to ensure that the power system will meet the forecasted demand and the security criteria along the planning horizon, while minimizing investment, operational, and interruption costs. Optimization techniques based on metaheuristics have demonstrated the potential to find high-quality solutions. Numerous advantages can be linked to these tools: the software complexity is acceptable; they are able to mix integer and non-integer variables; and also present relatively faster computational times. Their success is related to the ability to avoid local optima by exploring the basic structure of each problem. However, owing to today’s power network dimensions, random behavior of transmission and generation equipments, load growth uncertainties, etc., the TEP problem has become combinatorial, stochastic, and highly complex. When uncertainties and chronological aspects are added to these problems, the optimal solution becomes almost inaccessible, even when using metaheuristics. This chapter proposes a methodology to solve the multi-stage TEP problem considering security criteria and the treatment of external uncertainties, as load/generation growth. In addition, a discussion about how to include security criteria using deterministic and probabilistic approaches is presented through a case study on a small test system. A real transmission network is used as an illustration of the application of the proposed methodology.