A study on optimal power sharing in interconnected microgrids under uncertainty

Nikmehr, Nima; Ravadanegh, Sajad Najafi

doi:10.1002/etep.2081

Cited by 39 publications

(32 citation statements)

References 29 publications

(63 reference statements)

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“…For this purpose, different heuristic optimization algorithms such as GA [36], PSO [37], modified particle swarm optimization [38], differential evolution (DE) [39], and imperialist competitive algorithm (ICA) [40] are implemented in this paper, and the performance comparison and the results are presented. The parameters used in different algorithms are given in the Appendix A.…”

Section: Controllers' Coefficients Selectionmentioning

confidence: 99%

Integration of the wind power plants through a novel, multi-objective control scheme under the normal and emergency conditions

Ansari

Jamei

Kazemi

2016

Int. Trans. Electr. Energ. Syst.

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SUMMARYIn this paper, a two-part (i.e., normal part and reserve part) control scheme is presented for a single wind turbine generator and then extended to a set of them called wind power plant. The proposed method can be applied under the normal operation of the system or emergency condition in which the generating power drops, suddenly. In this work, initially, a novel control scheme is proposed for both single wind turbine generator and wind power plant under the normal condition. Then, the reserve part of the scheme is presented with the aim of injecting huge amount of energy to the network, and therefore improving the frequency, after an outage of a generating unit. The proposed scheme is applied to two case studies to validate the performance. Finally, a comprehensive analysis is performed, and the effects of different parameters on the system's frequency behavior are evaluated for different wind speed profiles.

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Section: Controllers' Coefficients Selectionmentioning

confidence: 99%

Integration of the wind power plants through a novel, multi-objective control scheme under the normal and emergency conditions

Ansari

Jamei

Kazemi

2016

Int. Trans. Electr. Energ. Syst.

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“…Numerous researchers have assessed the technical impacts of electric vehicles (EVs) on radial distribution systems (RDSs) . In a parallel way, other researchers have investigated the technical impacts of PV systems on RDSs . The assessment of technical impact of PV systems and EVs has recently emerged in literature .…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, probabilistic techniques are the key to a more accurate assessment of the combined impact of uncertainties regarding RDS output variables. Of these techniques, the ones that are most frequently used are the following: probabilistic load flow methods based on Monte Carlo simulation (MCS), analytical techniques, and approximation methods …”

Section: Introductionmentioning

confidence: 99%

“…From the literature review about the impact of PV systems, EVs or the combined interaction on RDSs, major identified shortcomings in studies include: (1) the simulation step is not adjusted to 10 minutess (usually 0.5 or 1 hour is planned); (2) the technical impact is assessed without considering its probability of occurrence. This means that the probability distribution of the RDS output variable is not calculated; the averaged values are usually given and the probability of voltage threshold violation is not computed; (3) the correlation of the input variables is rarely considered.…”

Section: Introductionmentioning

confidence: 99%

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Voltage behaviour in radial distribution systems under the uncertainties of photovoltaic systems and electric vehicle charging loads

Ruíz-Rodríguez

Hernández

Jurado

2017

Int Trans Electr Energ Syst

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Summary This paper presents a probabilistic method that accurately verifies the fulfilment of voltage constraints in radial distribution systems (RDSs) with photovoltaic (PV) systems and electric vehicle (EV) charging loads. This problem has not been comprehensively discussed. The proposed probabilistic method (PPM) involves the calculation of input variable cumulants, the linearization of load‐flow equations, and the application of the cumulant method and the Cornish‐Fisher expansion. Obviously, it is first necessary to model the PV systems and EV charging loads as random variables. In addition, the correlation of the input variables is suitably handled. As part of this research, a Monte Carlo simulation was performed, which confirmed the accuracy of the results obtained with the PPM. As an added value, when compared to the Monte Carlo simulation, there was a significant reduction in computational cost. The results obtained by the PPM demonstrate that the connection of PV systems in the IEEE 33‐node RDS with EVs clearly contributes to keeping voltages within regulatory limits, once the distributions of the RDS output variables are inspected. Nonetheless, the greater dispersion in the distributions in combined PV and EV scenarios means that voltage constraint fulfilment cannot be absolutely guaranteed. This probabilistic approach provides a more accurate assessment than one based on a simple deterministic vision. Thus, the PPM is extremely useful because it provides a better understanding of the combined technical impact under different correlated and uncorrelated scenarios.

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“…Mount Carlo simulation (MCS), Latin hypercube sampling (LHS), PSO, and the imperialist competitive algorithm (ICA) are widely used as numerical methods to model uncertainties [34,35]. Approximate methods such as the point estimate method (PEM) and two-point estimate method (2PEM) were used in [36,37].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

2017

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Abstract:A microgrid (MG) is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM) utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP) and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.

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A study on optimal power sharing in interconnected microgrids under uncertainty

Cited by 39 publications

References 29 publications

Integration of the wind power plants through a novel, multi-objective control scheme under the normal and emergency conditions

Integration of the wind power plants through a novel, multi-objective control scheme under the normal and emergency conditions

Voltage behaviour in radial distribution systems under the uncertainties of photovoltaic systems and electric vehicle charging loads

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

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