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This paper presents the application of binary firefly algorithm (BFA) in obtaining the optimal location of battery energy storage systems (BESS) in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. The optimization process aims to obtain the optimal location by minimizing the voltage deviation of the PVDG bus. A BESS placement (BP) vector...
This paper deals with energy management in smart districts using distributed model predictive control (DMPC). We investigate two decomposition methods, primal and dual decomposition, for problems where a shared resource has to be distributed optimally amongst sub systems. The objective is to compare these two decomposition methods with a focus on how well they are suited in the context of smart district...
Placing appropriate numbers of PMUs is critical to collect phase angle data for best identifying multiple line outages in wide-area transmission system, because of high deployment costs. This work focuses on exploring the global optimal strategy of PMU deployment for maximizing the average identification capability of multiple line outages. Inspired by Kullback-Leibler (KL) distance, this paper proposes...
In this paper, a variant of quantum particle swarm optimizer called Guiding Quantum Particle Swarm Optimizer incorporating Immune algorithm (GQPSOI) is proposed. The algorithm employs quantum infusion to train the effectiveness of learning as particle swarm optimization with Quantum Infusion (PSO-QI). Differing from PSO-QI, GQPSOI replaces particles by means of neighborhood-based immune algorithm...
The paper shows that the manifestation of Hamilton principle in electric power system is tending of its states to self-optimization. Characteristic feature of these states is minimum dissipation of electric energy during its transmission. The possibility and expedience of this principle usage for optimal control of normal modes of electric power system is shown.
In this work, several techniques for the optimization of expressions in a novel quaternary algebra are discussed thoroughly. This quaternary algebra, which can be used to implement any quaternary logic function, is closely related to Boolean algebra. A set of quaternary operators are defined and two ways to express any quaternary function mathematically are described. Finally, we have discussed several...
This paper considers a problem where multiple users make repeated decisions based on their own observed events. The events and decisions at each time step determine the values of a utility function and a collection of penalty functions. The goal is to make distributed decisions over time to maximize time average utility subject to time average constraints on the penalties. An example is a collection...
A robust transmit beamforming scheme is proposed for green cognitive radio networks in presence of incorrect steering vector estimations. The beamformer is designed using a stochastic optimization approach. The proposed beamforming scheme achieves three objectives: a) Probability for large-than-a-threshold for secondary user's received power in the steering direction is maximized; b) Probabilities...
In this paper, we investigate a new design technique that adopts a modern optimization scheme called the second-order-cone-programming (SOCP) for designing an all-pass (AP) phase-correction-network (PCN). The PCN is required in the digital communications through non-linear phase channel such that the non-linear phase characteristic can be corrected to nearly linear phase. As a consequence, applying...
In SON enabled LTE networks many different SON functions may operate simultaneously in order to optimize the network performance. With the increasing number of SON functions the probability of conflicts and dependencies between them increases and become more challenging to handle. In this paper an integrated approach for two SON functions, namely handover optimization and load balancing combined with...
This paper proposes a method for the construction of approximate feasible primal solutions from infeasible ones for large-scale optimization problems possessing certain separability properties. Whereas the infeasible primal estimates can typically be produced from (sub-) gradients of the dual function, it is often not easy to project them to the primal feasible set, since the projection itself has...
A multi-way relaying scenario is considered. Each node has to transmit an individual message and has to receive the messages of all other nodes. These multi-way communications between the multi-antenna nodes are performed via an intermediate non-regenerative multi-antenna relay station. An iterative MMSE approach is proposed to jointly design the transceive filter at the relay station and the receive...
This work is concerned with solving non-convex power optimization problems by introducing the concept of “nonlinear optimization over graph”. To this end, the structure of a given nonlinear real/complex optimization with quadratic arguments is mapped into a generalized weighted graph, where each edge is associated with a weight set constructed from the known parameters of the optimization (e.g., the...
In the diffusion strategies for distributed estimation over adaptive networks, each node calculates a weighted average of the intermediate parameter estimates of its neighboring nodes. Thus, all the nodes should continuously share their intermediate estimates with their neighbors. In this paper, we consider exchanging a predetermined number of elements of each intermediate estimate vector at each...
Linear precoding for cooperative multi-cell transmission can provide substantial gains in user throughput, while channel state information (CSI) need to be available at the transmitter. Performance degradation due to imperfect CSI can be partially compensated by robust precoding techniques. For distributed precoding the pre-processing of the user data is performed locally at each base station (BS),...
Exposure fusion is a technique to fuse several differently exposed low dynamic range (LDR) images to an LDR image. The output image has more information than each of the input images, but it could suffer from loss of fine details. In this paper, we propose a detail-enhanced exposure fusion algorithm by introducing an L0 norm based optimization in gradient domain. The proposed algorithm extracts fine...
This paper solves Unit commitment (UC) problem using Priority List (PL) method based on maximum power rating of the generating unit while satisfying all the constraints over a period of time. Two novel optimization techniques, namely Particle Swarm Optimization (PSO) and Differential Evolution (DE) are implemented to deal with UC problem and to attain minimum operating cost by proper scheduling of...
The Internet of things has reached a stage that allows ubiquitous data access. Still, practical limitations remain in networks with scarce bandwidth. Here, we examine the Bloom filter data structure and its use in distributed protocols. We discuss how to minimize the bandwidth and energy usage consumed when distributed protocols exchange Bloom filters, through dynamic Bloom filter resizing. We propose...
The sparse representation problem of recovering an N dimensional sparse vector x from M < N linear observations y = Dx given dictionary D is considered. The standard approach is to let the elements of the dictionary be independent and identically distributed (IID) zero-mean Gaussian and minimize the l1-norm of x under the constraint y = Dx. In this paper, the performance of l1-reconstruction...
This paper proposes a new method of inter prediction based on low-rank matrix completion. By collection and rearrangement, image regions with high correlations can be used to generate a low-rank or approximately low-rank matrix. We view prediction values as the missing part in an incomplete low-rank matrix, and obtain the prediction by recovering the generated low-rank matrix. Taking advantage of...
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