Future power systems are expected to have distributed energy resources (DERs). A price-based operation (PBO), where dynamic prices are used as the control signal, can be an alternative scheme to address challenging operational issues in the future power systems. In this paper, a decentralized framework for optimal PBO using a feedback control mechanism is proposed to determine the nodal prices ...

The solution of an optimal power ow (OPF) problem in rectangular form by an interior-point method (IPM) for nonlinear programming is described. When formulated in rectangular form, some OPF variants have quadratic objective and quadratic constraints. Such quadratic features allow for ease of matrix setup and inexpensive incorporation of higher-order information in a predictor-corrector procedur...

This paper presents application of a new effective metaheuristic optimization method namely, the Jaya algorithm to deal with different optimum power flow (OPF) problems. Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. In this work, three goal functions are considered for the OPF solution: generation cost minimiz...

Deregulated energy markets, demand forecasting, and the continuously increasing share of renewable energy sources call—among others—for a structured consideration of uncertainties in optimal power flow problems. The main challenge is to guarantee power balance while maintaining economic and secure operation. In the presence of Gaussian uncertainties affine feedback policies are known to be viab...

Tensor decomposition plays a key role in identifying common features across a collection of matrices in many areas of science. A fundamental need in big data research is to process data tabulated as large-scale matrices using eigenvectors. A higher-order generalized singular value decomposition technique successfully captures the common features of the same organ from multiple animals in genomi...

The optimal power flow (OPF) problem contains many constraints. However, equality constraints and a limited set of inequality encompass sufficient information to determine the feasible space. This article presents hybrid supervised regression-classification learning-based algorithm predict active inactive before solving AC OPF solely based on nodal demand information. proposed is structured usi...

This chapter presents a novel Harmony Search (HS) algorithm used to solve security constrained optimal power flow (OPF) with various generator fuel cost characteristics. HS is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This chapter analyses the evolution of the populat...

The penetration of distributed generation and wind power in particular is expected to increase significantly over the coming years, and a huge shift in control, operation and planning of distribution networks is going to be necessary if this generation is to be connected in a cost effective manner. Traditionally, distribution networks have been operated as passive networks with uni-directional ...

Nonconvex optimization problems can be approximately solved via relaxation or local algorithms. For many practical such as optimal power flow (OPF) problems, both approaches tend to succeed in the sense that is usually exact and algorithms converge a global optimum. In this article, we study conditions are sufficient necessary for nonconvex simultaneously have no spurious optima. These help exp...

This paper proposes three strong second order cone programming (SOCP) relaxations for the AC optimal power flow (OPF) problem. These three relaxations are incomparable to each other and two of them are incomparable to the standard SDP relaxation of OPF. Extensive computational experiments show that these relaxations have numerous advantages over existing convex relaxations in the literature: (i...