Probabilistic optimal power flow

Madrigal, M.; Ponnambalam, K.; Quintana, V.H.

doi:10.1109/ccece.1998.682765

Cited by 93 publications

(63 citation statements)

References 7 publications

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“…Jabr and Pal suggested an OPF WPPs-TUs coordination model for networks operating with the consideration of overestimation and underestimation of WPPs [15]. Madrigal et al employed a first-order second-moment method (FOSMM) to investigate the statistical characteristics of the POPF problem for only a specific solution [16]. Verbic and Canizares proposed a 2m point estimated method (2m PEM) for the POPF problem in [17].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Steady state security conditions These are the set of discrete and continuous constraints that provide the power system security and operational limits. The changes in active power generations of TUs (15), reactive power generations of TUs (16), active power of CHP units (17), heat power generation of CHP and heat-only units (18) and (19), output power of WPPs and PVs (20) and (21), branch flows (22), bus voltage magnitudes (23), reactive power of shunt compensators (24) and transformer tap settings (25) …”

Section: Heat Balance Constraintmentioning

confidence: 99%

“…Probabilistic OPF (POPF) is an important probabilistic solver to analytically assess the random nature of the power grid variables. It plays an efficient role in maintaining the security and economy of the power network [1].…”

Section: Problem Description and Motivationmentioning

confidence: 99%

“…Although, there is a vast body of literature on proposing a solution methodology for DOPF including [6][7][8][9][10][11][12], and on modeling the uncertainties and correlations between IRVs of the POPF problem which comprise [13][14][15][16][17][18][19][20][21][22][23], little attention has been paid to accomplish the goal of contributing all these essential issues in a well-organized POPF considering both the technical and economical restrictions.…”

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

Azizipanah‐Abarghooee

Niknam

Malekpour

et al. 2015

Energy Conversion and Management

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Section: Literature Reviewmentioning

confidence: 99%

Section: Heat Balance Constraintmentioning

confidence: 99%

Section: Problem Description and Motivationmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

Azizipanah‐Abarghooee

Niknam

Malekpour

et al. 2015

Energy Conversion and Management

View full text Add to dashboard Cite

“…These methods provide a satisfactory balance between speed and precision. Among these techniques, the first-order second-moment [18] and point estimate methods stand out. The point estimate method [19] can be used to calculate the statistical moments of a random quantity that is a function of one or several random variables and has been used in the transfer capability uncertainty computation [20].…”

Section: Introductionmentioning

confidence: 99%

Optimal operation management of microgrids using the point estimate method and firefly algorithm while considering uncertainty

Mohammadi¹,

Mozafari²,

Soleymani³

2014

Turk J Elec Eng & Comp Sci

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Abstract:This paper analyzes the behavior of Hong's point estimate method to account for uncertainties in probabilistic energy management systems to optimize the operation of a microgrid (MG). These uncertainties may arise from different sources, such as the market prices, load demands, and electric power generation of wind farms and photovoltaic systems.Point estimate methods constitute a remarkable tool to handle stochastic power system problems because good results can be achieved using the same routines as those corresponding to deterministic problems, while keeping the computational burden low. The problem is formulated as a nonlinear constraint optimization problem to minimize the total operating cost. Weibull, beta, and normal distributions are used to model the uncertain input variables in this study. Moreover, the firefly algorithm is applied to achieve optimal operational planning with regard to cost minimization. The efficiency of Hong's point estimate method is validated on a typical MG. Results for the case study are presented and compared against those obtained from the Monte Carlo simulation. Specifically, this paper shows that the use of the 2m+1 scheme provides the best performance when a high number of random variables, both continuous and discrete, are considered.

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Probabilistic multi-objective transmission investment and expansion planning

Arabali

Hosseini

Moeini‐Aghtaie

2014

Int. Trans. Electr. Energ. Syst.

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Summary In market‐based planning studies, the financial aspects of transmission grids have been posed as a major challenge since these are important keys to provide a non‐discriminative and competitive environment for energy market participants. In this respect, this paper proposes a probabilistic multi‐objective transmission expansion planning algorithm considering private investors' preferences, technical concerns, and random nature of power system uncertainties. The combination of Non‐Dominated Sorting Genetic Algorithm II, as a widely‐used robust multi‐objective optimization technique, and point estimation method is employed to handle non‐commensurable probabilistic objective functions. The IEEE Reliability Test System is taken into consideration as the test system to verify and address the different aspects of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.

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Probabilistic optimal power flow

Cited by 93 publications

References 7 publications

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

Optimal operation management of microgrids using the point estimate method and firefly algorithm while considering uncertainty

Probabilistic multi-objective transmission investment and expansion planning

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