Christiano Lyra

Adaptive Hybrid Genetic Algorithm for Technical Loss Reduction in Distribution Networks Under Variable Demands

In power distribution networks the load varies within any given time frame. It may, therefore, seem that a good approach to reduce losses would be the solving of a network reconfiguration problem to suit each of the significant load variations. However, frequent changes in configuration can trigger outages or cause transient problems; they are best avoided. A recent formulation of this problem explicitly considers load variations and proposes to restrain frequent reconfigurations by assuming that network topologies will remain unchanged for a given planning period. This formulation leads to a much larger optimization problem than that traditionally used for network reconfiguration; moreover, it requires a new approach to optimization which is capable of dealing with energy flows instead of only instantaneous power flows. Such an approach is proposed in this paper, which discusses the design of an adaptive hybrid genetic algorithm that fulfills these new requirements. Key concepts in evolutionary computation and analysis of distribution systems are explored to develop this new algorithm. Application to real case studies certifies its benefits.

A multiobjective approach to the short-term scheduling of a hydroelectric power system

This paper is concerned with the short-term scheduling of the Iguacu river hydroelectric power system, in Southern Brazil. The system comprises four power plants with an unusual high coupling, held by two different utilities. Even though government regulations establishes operation guidelines, electric utilities have their own interests. A multiobjective framework is adopted to study the operation of the power system. Dynamic programming is used to find optimal solutions, with an implementation based on the concept of differential dynamic programming. A case study shows the possibility of obtaining energetic gains with the adoption of nonconventional operation rules and the need of negotiation to avoid wasting energy.

Energy Losses Estimation in Power Distribution Systems

Estimating technical losses is fundamental to the planning and economics of electric power networks. This paper surveys the evolution of the ideas behind energy loss estimation and focuses on the development of the concepts of the loss factor and equivalent hours. The paper next identifies difficulties in using maximum demands and the loss factor to estimate energy losses. Based on this analysis, this study proposes an alternative loss estimation approach that relies on the “loss coefficient” as the fundamental parameter for describing load variations in loss estimation. A large load-curve data bank from Brazilian utilities is used to characterize load-curve parameters and provide perspective on the old and new concepts. Practical applications put the proposed ideas into perspective, showing how the use of average demands and loss coefficient can help to make better cable choices, increase accuracy in loss estimation for distribution transformers, and enhance the quality of information in loss estimation analysis.

Distribution network reconfiguration for loss reduction with variable demands

This paper presents a contribution to loss reduction in distribution systems, considering variable demands. Formulations for both fixed and variable demands are presented. Simple examples illustrate significant aspects of the problem with variable demands. Two algorithms are proposed to solve the loss reduction problem with fixed configuration for the whole planning period.

Switch Allocation Problems in Power Distribution Systems

Reliability analysis of power systems has been attracting increasing attention. Regulatory agencies establish reliability standards that, if infringed, result in costly fines for the utility suppliers. A special concern pertains to the distribution networks on which most failures occur. The allocation of switches is a possible strategy to improve reliability, by allowing network reconfiguration to isolate contingencies and restore power to dark areas. This paper proposes an optimization methodology to allocate switches on radially operated distribution networks. The solution framework considers sectionalizing and tie switches of different capacities, with manual or automatic operation schemes. The approach minimizes the costs of allocation and energy not supplied, under reliability and flow capacity constraints. The solution framework is based on memetic algorithm concepts with a structured population. Case studies with a large network and real-world scenarios were used to evaluate the methodology. The results indicate that significant cost reductions can be achieved using the proposed solutions.

Modelling and Optimization of Hydrothermal Generation Scheduling

An approach is proposed to optimize the operation of energy production systems over middle term planning periods. Randomness of primary load is explicitly considered. A precise model is used to represent the hydraulic system (with individualized reservoir in cascade, water transportation delays, nonlinear generation, ...) as well as the non-hydraulic system (thermal generations, interchanges, load shedding, ...). Difficulties resulting from the large scale are overcome by decomposition techniques.

A pseudo-polynomial algorithm for optimal capacitor placement on electric power distribution networks

Allocation of shunt capacitor banks on radial electric power distribution networks allow reduction of energy losses and aggregated benefits. Four decades ago Duran proposed the use of dynamic programming to find optimal capacitor placement on these networks; however, with the restricting assumption of single-ended networks, which precluded its application to real capacitor allocation problems. Subsequently heuristic methods prevailed in the capacitor allocation literature. Here the Extended Dynamic Programming Approach (EDP) lifts Duran’s restricting assumption; a richer definition of state and the projection of multidimensional informations into equivalent one-dimensional representations are the supporting concepts. In addition to allow consideration of multi-ended networks, EDP deals with other requirements of capacitor allocation studies, including the use of both fixed and switched capacitors and representation of voltage drops along the networks. When switched capacitors are considered the optimization procedure also solves the capacitor control problem, obtaining the best tap adjustments for them. Case studies with real scale distribution networks put into perspective the benefits of the methodology; EDP has the appeal of providing global optimal solutions with pseudo-polynomial computational complexity in the worst-case, and with linear complexity for practical applications.

Minimization of energy losses in electric power distribution systems by intelligent search strategies

Energy is continuously dissipated in electric power systems due to electrical resistance in transmission and distribution lines. This paper addresses the problem of obtaining a network topology with minimum energy losses for electric power distribution systems. As distribution networks must operate radially, the problem can be formulated as a generalization of the minimum spanning tree problem. The generalization is due to variation in costs as network configuration changes. Nonlinear network flow techniques are teamed with search strategies borrowed from the field of artificial intelligence to overcome computation intractability.

UNORGANIZED MACHINES FOR SEASONAL STREAMFLOW SERIES FORECASTING

Modern unorganized machines--extreme learning machines and echo state networks--provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task.

Optimal allocation of remote controlled switches in radial distribution systems

There is an increasing interest in the analysis of power distribution systems, including demands to improve the distribution networks reliability. Regulatory agencies define reliability indices to quantify and evaluate the electric quality. In order to improve system reliability and provide a good quality service, this work proposes to install a minimum amount of switch devices at appropriate locations in the distribution network. A methodology is presented to effectively evaluate, even for large real networks the impact on reliability following contigen-cies. Firstly, are propose a constructive heuristic that allocates sectionalizers and tie switches, automatic and non-automatic, in a radial distribution system. This procedure aims to minimize the unsupplied energy caused in the network by determining a proper number, location and type of switches. A genetic algorithm is designed to further improve the switches location suggested by the constructive heuristic. The good performance of the proposed approach is confirmed by some case studies with large real energy distribution network.