11,481 research outputs found
Minimization of Losses on Electric Power Transmission Lines
Availability of electric power has been the most powerful vehicle for facilitating economic, industrial and social developments of any nation. Electric power is transmitted by means of transmission lines which deliver bulk power from generating stations to load centres and consumers. For electric power to get to the final consumers in proper form and quality, losses along the lines must be reduced to the barest minimum. In this paper, a mathematical model of losses along electric power transmission lines was developed using a combination of ohmic and corona losses. The resulting model, which is a nonlinear multivariable unconstrained optimization problem, was minimized using the classical optimization technique. From the results, we were able to see that power losses on transmission lines will be minimized if we transmit electric power at a very low current and at an operating voltage that is very close to the critical disruptive voltage. Also the spacing between the conductors should be large in comparison to their diameters. These results, gotten by the use of an analytical method, conform to the existing results for power transmission. Keywords: Power Losses, Minimization, Transmission, Classical Optimization, Mathematical Model
Smart Grid for the Smart City
Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users
Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid
Recently there has been increasing interest in improving smart grids
efficiency using computational intelligence. A key challenge in future smart
grid is designing Optimal Power Flow tool to solve important planning problems
including optimal DG capacities. Although, a number of OPF tools exists for
balanced networks there is a lack of research for unbalanced multi-phase
distribution networks. In this paper, a new OPF technique has been proposed for
the DG capacity planning of a smart grid. During the formulation of the
proposed algorithm, multi-phase power distribution system is considered which
has unbalanced loadings, voltage control and reactive power compensation
devices. The proposed algorithm is built upon a co-simulation framework that
optimizes the objective by adapting a constriction factor Particle Swarm
optimization. The proposed multi-phase OPF technique is validated using IEEE
8500-node benchmark distribution system.Comment: IEEE PES GM 2014, Washington DC, US
Optimized Solar Photovoltaic Generation in a Real Local Distribution Network
Remarkable penetration of renewable energy in electric networks, despite its
valuable opportunities, such as power loss reduction and loadability
improvements, has raised concerns for system operators. Such huge penetration
can lead to a violation of the grid requirements, such as voltage and current
limits and reverse power flow. Optimal placement and sizing of Distributed
Generation (DG) are one of the best ways to strengthen the efficiency of the
power systems. This paper builds a simulation model for the local distribution
network based on obtained load profiles, GIS information, solar insolation,
feeder and voltage settings, and define the optimization problem of solar PVDG
installation to determine the optimal siting and sizing for different
penetration levels with different objective functions. The objective functions
include voltage profile improvement and energy loss minimization and the
considered constraints include the physical distribution network constraints
(AC power flow), the PV capacity constraint, and the voltage and reverse power
flow constraints.Comment: To be published (Accepted) in: Proceedings of the IEEE PES Innovative
Smart Grid Technologies Conference (ISGT), Washington D.C., USA, 201
A goal programming methodology for multiobjective optimization of distributed energy hubs operation
This paper addresses the problem of optimal energy flow management in multicarrier energy networks
in the presence of interconnected energy hubs. The overall problem is here formalized by a nonlinear
constrained multiobjective optimization problem and solved by a goal attainment based methodology.
The application of this solution approach allows the analyst to identify the optimal operation state of the
distributed energy hubs which ensures an effective and reliable operation of the multicarrier energy
network in spite of large variations of load demands and energy prices. Simulation results obtained on
the 30 bus IEEE test network are presented and discussed in order to demonstrate the significance and
the validity of the proposed method
RNA Interference (RNAi) for plants
As we are facing global population
development, strategies are required to improve
agricultural production in the battle against
hunger and poverty. Agricultural biotechnology
provides a powerful method in combination of
conventional breeding, new innovations and
enhanced management of resources which
improves the productivity of livestock,
aquaculture, and crops. After the finding of RNA
interference (RNAi), researchers have made
considerable growth in improving this
remarkable crop especially in defence
technology. RNA interference is a vital plant
growth, development and reaction regulator to
various types of stresses. This technology
leads to higher efficiency and potency of gene
silencing, thus becoming the highly promising
technology for crop improvements at a rapid
rate with some advantages. Nowadays, RNAi
has been widely used for the improvement in
agricultural biotechnology and seems to be
applicable and commercialized in other fields
too
Efficient and Risk-Aware Control of Electricity Distribution Grids
This article presents an economic model predictive control (EMPC) algorithm for reducing losses and increasing the resilience of medium-voltage electricity distribution grids characterized by high penetration of renewable energy sources and possibly subject to natural or malicious adverse events. The proposed control system optimizes grid operations through network reconfiguration, control of distributed energy storage systems (ESSs), and on-load tap changers. The core of the EMPC algorithm is a nonconvex optimization problem integrating the ESSs dynamics, the topological and power technical constraints of the grid, and the modeling of the cascading effects of potential adverse events. An equivalent (i.e., having the same optimal solution) proxy of the nonconvex problem is proposed to make the solution more tractable. Simulations performed on a 16-bus test distribution network validate the proposed control strategy
Application of Grey Wolf Optimizer Algorithm for Optimal Power Flow of Two-Terminal HVDC Transmission System
This paper applies a relatively new optimization method, the Grey Wolf Optimizer (GWO) algorithm for Optimal Power Flow (OPF) of twoterminal High Voltage Direct Current (HVDC) electrical power system. The OPF problem of pure AC power systems considers the minimization of total costs under equality and inequality constraints. Hence, the OPF problem of integrated AC-DC power systems is
extended to incorporate HVDC links, while taking into consideration the power transfer control characteristics using a GWO algorithm. This algorithm is inspired by the hunting behavior and social leadership of grey wolves in nature. The proposed algorithm is applied to two different case-studies: the modified 5-bus and WSCC 9-bus test systems. The validity of the proposed algorithm is demonstrated by comparing the obtained results with those reported in literature using other optimization techniques. Analysis of the obtained results show that the proposed GWO algorithm is able to achieve shorter CPU time, as well as minimized total cost when compared with already existing optimization techniques. This conclusion proves the efficiency of the GWO algorithm
Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review
YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000
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