46,282 research outputs found
Review of trends and targets of complex systems for power system optimization
Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107
Electrical power grid network optimisation by evolutionary computing
A major factor in the consideration of an electrical power network of the scale of a national grid is the calculation of power flow and in particular, optimal power flow. This paper considers such a network, in which distributed generation is used, and examines how the network can be optimized, in terms of transmission line capacity, in order to obtain optimal or at least high-performing configurations, using multi-objective optimisation by evolutionary computing methods
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
A Multiperiod OPF Model Under Renewable Generation Uncertainty and Demand Side Flexibility
Renewable energy sources such as wind and solar have received much attention
in recent years and large amount of renewable generation is being integrated to
the electricity networks. A fundamental challenge in power system operation is
to handle the intermittent nature of the renewable generation. In this paper we
present a stochastic programming approach to solve a multiperiod optimal power
flow problem under renewable generation uncertainty. The proposed approach
consists of two stages. In the first stage operating points for conventional
power plants are determined. Second stage realizes the generation from
renewable resources and optimally accommodates it by relying on demand-side
flexibility. The benefits from its application are demonstrated and discussed
on a 4-bus and a 39-bus systems. Numerical results show that with limited
flexibility on the demand-side substantial benefits in terms of potential
additional re-dispatch costs can be achieved. The scaling properties of the
approach are finally analysed based on standard IEEE test cases upto 300 buses,
allowing to underlined its computational efficiency.Comment: 8 pages, 10 figure
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
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