A review of optimal power flow studies applied to smart grids and microgrids

Abdi, Hamdi; Beigvand, Soheil Derafshi; Scala, Massimo La

doi:10.1016/j.rser.2016.12.102

Cited by 188 publications

(91 citation statements)

References 222 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The other elements of the array are the identities of ''from'' and ''to'' buses of the branch impedances, stored in RR½ ½0 and RR½ ½1 respectively, and the resistance and reactance of the branch impedances, stored in RR½ ½2 and RR½ ½3 respectively, with ohms as their units. The conductance (real part) YG½n þ 1½n þ 1 and susceptance (imaginary part) YB½n þ 1½n þ 1 of the admittance matrix can be calculated according to (2) and (3) after getting array RR½ ½ . YG½ ½ and YB½ ½ are both RDDs arrays.…”

Section: Parallel Power Flow Calculation Methodsmentioning

confidence: 99%

“…4 below in terms of diagonal elements and off-diagonal elements separately. Off-diagonal elements can be computed directly from branch resistance and impedance using (2). Then the diagonal elements can be calculated according to (3).…”

Section: Parallel Power Flow Calculation Methodsmentioning

confidence: 99%

“…Moreover, the construction of cross-regional interconnection and long-distance transmission systems make the scale of power systems expand and their structure tends to be complicated. There is an urgent need to propose new power flow calculation approaches [2,3] to cope with these changes and consequent issues they bring to power flow calculation, such as the addition of a temporal dimension, insufficient memory, and slow computational speed and convergence [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Wang

Zhou

2018

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex. They require faster computing speed and better scalability for power flow calculations to support unit dispatch. Based on the analysis of a variety of parallelization methods, this paper deploys the large-scale power flow calculation task on a cloud computing platform using resilient distributed datasets (RDDs). It optimizes a directed acyclic graph that is stored in the RDDs to solve the low performance problem of the MapReduce model. This paper constructs and simulates a power flow calculation on a large-scale power system based on standard IEEE test data. Experiments are conducted on Spark cluster which is deployed as a cloud computing platform. They show that the advantages of this method are not obvious at small scale, but the performance is superior to the stand-alone model and the MapReduce model for large-scale calculations. In addition, running time will be reduced when adding cluster nodes. Although not tested under practical conditions, this paper provides a new way of thinking about parallel power flow calculations in large-scale power systems.

show abstract

Section: Parallel Power Flow Calculation Methodsmentioning

confidence: 99%

Section: Parallel Power Flow Calculation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Wang

Zhou

2018

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

show abstract

“…Equipment such as smart meters and phasor measurement units will contribute to an increase in observability and improvement in decision-making and situational awareness. Ultimately, the goal of smart grid is to provide a safe, reliable, and flexible grid operation, which is able to accommodate large number of renewables and other resources without sacrificing the reliability and cost of grid operation [15,16]. On the other hand, microgrid represents a group of interconnected loads and generation resources with defined grid boundaries that can be controlled as a single entity.…”

Section: Preliminariesmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

View full text Add to dashboard Cite

This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

show abstract

“…Optimization models have been widely used for the derivation of the optimal solution in microgrids; the interested reader may refer to [16] for a review of the most significant optimal power flow approaches in smart grids…”

Section: Related Workmentioning

confidence: 99%

Cooperation in microgrids through power exchange: An optimal sizing and operation approach

Zenginis

Vardakas

Echave³

et al. 2017

Applied Energy

View full text Add to dashboard Cite

This paper proposes a novel model for the optimal design and power management of a microgrid. The key objective of the proposed model is to indicate the benefits of cooperation in terms of energy cost savings, carbon emission reduction and provision of energy self-sufficiency. The proposed cooperative configuration considers that buildings with different load patterns exchange power through a common DC bus , so that that an optimum utilization of the energy generated by local renewables is achieved. The problem of selecting the optimal capacities of photovoltaic arrays, energy storage systems and inverters, as well as of determining the optimal daily power operation plan is formulated as a mixed integer linear programming problem, where the objective function is optimized based on the Nash bargain method.. The impact of the daily scheduling of the energy storage systems and electric vehicles, as well as the impact of power exchanges on the equipment * Corresponding author Keywords: smart cities, microgrid, cooperative system, renewable energy sources, optimization.

show abstract

A review of optimal power flow studies applied to smart grids and microgrids

Cited by 188 publications

References 222 publications

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Cooperation in microgrids through power exchange: An optimal sizing and operation approach

Contact Info

Product

Resources

About