The optimal power flow (OPF) problem determines an optimal operating point of the power network that minimizes a certain objective function subject to physical and network constraints. There has been a great deal of attention in convex relaxation of the OPF problem in recent years, and it has been shown that a semidefinite programming (SDP) relaxation can solve different classes of the nonconve...

A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit...

This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as ...

To guide the decision making of the expert engineer specialized in power system o peration and control; the practical OPF solution should take in consideration the critical situati on due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differ...

This paper presents two new Particle swarm optimization methods to solve optimal power flow (OPF) in power system incorporating flexible AC transmission systems (FACTS). Two types of FACTS devices, thyristor-controlled series capacitor (TCSC) and thyristor controlled phase shifting (TCPS), are considered. In this paper, the problems of OPF with FACTS are solved by using particle swarm optimizat...

Modern power networks often have partitioned structures, with disjoint parts of the network being operated by competing agents. It is therefore of significant interest to be able to solve the Optimal Power Flow (OPF) problem for the entire network in a distributed manner without requiring significant exchange of sensitive operational information between rival operators. For networks whose regio...

In this paper, we propose a framework for optimal energy scheduling combined with a transaction mechanism to enable multiple microgrids to exchange their energy surplus/deficit with others while the distributed networks of microgrids remain secure. Our framework is based on two layers: a distributed network layer and a market layer. In the distributed network layer, we first solve optimal power...

This paper is concerned with market-based protocols for relieving congestion caused by transactions outside the control area in which the congestion occurred. One approach, proposed by Cadwalader et al. is based on dual decomposition in which out of area congestion is “priced-out” and added to the optimal power flow (OPF) objective function of the control area operator while the prices are dete...

As a nonlinear, non-convex and large scale optimization problem including both continuous and discrete control variables, security-constrained optimal power flow (SC-OPF) is one of the most important power system problems which need a superior optimization technique to be effectively solved. Inspired by the mating process of honey bees, honey bee mating optimization (HBMO) is a recently invente...