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This paper deals with new power flow formulations for AC distribution networks. The power flow problem is approximated using Laurent's series expansion method over the product between voltage variables in the power balance equations, which proportionates a mathematical structure similar to the conventional Newton-Raphson method. The proposed model is developed in complex variables, which decreases the number of calculations needed and prevents the transformation of the load flow model into polar coordinates. Numerical results confirm that the proposed method is faster regarding computational time and the total number of iterations required; besides, one of the main advantages of this approach is dealing with radial or mesh grids. All simulations are conducted in the programming environment in MATLAB software.

Phase balancing is a highly complex problem that consists of minimizing power losses by swapping generation and loads along a distribution feeder. Being a discrete and nonlinear problem, its solution is usually subject to the use of heuristic methods such as Genetic Algorithms or Particle Swarm Optimization. However, the representation of the feasible space is challenging for conventional approaches. This paper proposes a heuristic algorithm which is based on group-theory, an algebraic modeling that allows a compact and efficient representation of the feasible space. The proposed representation not only allows to develop an algorithm that guarantees feasibility along the generations, but also permits its implementation in the crossover and the mutation steps. Formal definitions of groups are presented and complemented with a matrix homomorphisms that allows the implementation of the algorithm. Numerical calculations on the IEEE 13, IEEE 37 and IEEE 123 nodes test feeders complement the proposed analysis and confirm the efficiency of what is proposed.

Power systems can experience poorly damped oscillations tendency which may cause loss of synchronism and security constraints infringement. This may be caused by disturbances in power consumption, failures, and recently by the presence of delays in monitoring process. In consequence, control systems, which must deal with delayed signals in monitoring and control, need to be designed to avoid instability in the system. This paper presents the application of a proposed Sliding Prediction Block which feeds a Model Predictive Control (MPC) aiming to increase the damping of oscillations in a nonlinear model of the delayed single-machine infinite-bus system (SMIB), and in the two area test case of Kundur. The proposed scheme controls the mechanical power to track the power reference at the infinite bus, and in Kundur system the method acts over the excitation system in one of its machines. Also, the analyzed cases consider delayed signals feeding the control strategy. Results show that combining the Sliding Prediction Block with Model Predictive Control (MPC) face effectively the time-delay problem.

When a power system is exposed to a major disturbance, the system exhibits a tendency towards poorly damped oscillations which may cause loss of synchronism; in consequence, control actions, which must deal with the presence of delays in monitoring and control signals, have to be performed to avoid an instability in the system. This paper presents the application of a nonlinear control strategy for the damping of oscillations in a delayed single-machine infinite-bus system. The damping of oscillations is achieved by acting over the mechanical power and tracking the electrical power reference at the infinite bus. Also, it is addressed the issue of time-delayed signals considering the electrical power at the infinite bus as a delayed remote signal. Results show that the proposed Smith predictor based backstepping control effectively resolves the time-delay problem, and its possible application to multi machine systems is promising.