Optimization-Based Islanding of Power Networks Using Piecewise Linear AC Power Flow

In this paper, a flexible optimization-based framework for intentional islanding is presented. The decision is made of which transmission lines to switch in order to split the network while minimizing disruption, the amount of load shed, or grouping coherent generators. The approach uses a piecewise linear model of AC power flow, which allows the voltage and reactive power to be considered directly when designing the islands. Demonstrations on standard test networks show that solution of the problem provides islands that are balanced in real and reactive power, satisfy AC power flow laws, and have a healthy voltage profile

Controlling multi-reservoir systems

The paper extends the results of the form of the optimal policy for a hydroelectric reservoir problem from the one-reservoir case to multi-reservoir cases. The importance of these new results in practice is that they allow more efficient solution algorithms to be developed. Since multi-reservoir problems are extremely difficult to solve, such algorithms are of great value

Nested Benders Decomposition and Dynamic Programming for Reservoir Optimization

This paper presents a computational comparison of nested Benders decomposition and dynamic programming (DP) for stochastic optimization problems arising from the optimization of hydro-electric generation from hydraulically linked reservoirs. The following assumptions are made: the amount of electricity produced by a generator is a concave piecewise linear function of the volume taken from the feeder reservoir and is independent of the volume in the feeder reservoir; the reward for generation is a concave piecewise linear function of total generation; the final value is a separable concave piecewise linear function of residual volume. These assumptions allow the problem to be formulated as a linear programming problem. The examples considered have between 3 and 17 reservoirs, two weather states, three runoff patterns and five periods. The examples are solved exactly by the simplex method and nested Benders decomposition and solved approximately by discrete DP. A full version of DP is us..

An inexact modified subgradient algorithm for nonconvex optimization

Nonconvex optimization, Nonsmooth optimization, Sharp augmented Lagrangian, Modified subgradient method, Inexact minimization, Bang-bang control,