Uncertainty handling in power system expansion planning under a robust multi‐objective framework

Alizadeh, Behnam; Jadid, Shahram

doi:10.1049/iet-gtd.2013.0674

Cited by 11 publications

(8 citation statements)

References 31 publications

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“…MCS is the most straightforward, promising and accurate one having computational procedure and cumbersome efforts are its shortcoming that limits its range of practical applicability for large-scale plants. Analytical methods use convolution techniques which result in some simplifications such as independency or linear dependency of different random variables, linearization of the power system equations and losing accuracy [27], [28]. Approximate techniques have an intermittent characteristic and can provide a balance between speed and precision.…”

Section: A Primary-levelmentioning

confidence: 99%

“…TOAT ensures that the testing scenarios providing good statistical information with a minimum number in the uncertain operating space, which significantly reduces the testing burden. TOAT has been proven to have the ability to select optimally representative scenarios for testing from all possible combinations [28]. Compared with MCS, TOAT provides much smaller testing scenarios and leads to shorter computing time.…”

Section: A Primary-levelmentioning

confidence: 99%

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Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture

Marzband

Parhizi

Savaghebi

et al. 2016

IEEE Trans. Energy Convers.

135

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In this paper, a comprehensive real-time interactive EMS framework for the utility and multiple electrically-coupled MGs is proposed. A hierarchical bi-level control scheme-BLCS with primary and secondary level controllers is applied in this regard. The proposed hierarchical architecture consists of sub-components of load demand prediction, renewable generation resource integration, electrical power-load balancing and responsive load demand-RLD. In the primary-level, EMSs are operating separately for each MG by considering the problem constraints, power set-points of generation resources and possible shortage or surplus of power generation in the MGs. In the proposed framework, minimum information exchange is required among MGs and the distribution system operator. It is a highly desirable feature in future distributed EMS. Various parameters such as load demand and renewable power generation are treated as uncertainties in the proposed structure. In order to handle the uncertainties, Taguchi s orthogonal array testing-TOAT approach is utilized. Then, the shortage or surplus of the MGs power should be submitted to a central EMS-CEMS in the secondary-level. In order to validate the proposed control structure, a test system is simulated and optimized based on multi-period imperialist competition algorithm-MICA. The obtained results clearly show that the proposed BLCS is effective in achieving optimal dispatch of generation resources in systems with multiple MGs. Index Terms-bi-level stochastic programming, Imperialist competition algorithm, demand response, multiple Microgrid, optimal energy management system, optimal scheduling, responsive load demand, Tagochi algorithm. NOMENCLATURE Acronyms CEMS central energy management system DER distributed energy resources DGU dispatchable generation unit BLCS bi-level control scheme DR demand response EMS energy management system This work was supported by the Energy Technology Development and Demonstration Program (EUDP) through the Sino-Danish Project "Microgrid Technology Research and Demonstration" (meter.et.aau.dk).

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Section: A Primary-levelmentioning

confidence: 99%

Section: A Primary-levelmentioning

confidence: 99%

Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture

Marzband

Parhizi

Savaghebi

et al. 2016

IEEE Trans. Energy Convers.

135

View full text Add to dashboard Cite

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“…Among these sectors, transmission and generation expansion planning have captured the attention of the scientific community, and they have been widely investigated as two nondetachable parts of long‐term power‐system planning. In most of these studies, generation or transmission expansion plans are selected based on a presumed expansion plan for the other. However, in practice, planners should find transmission expansion plans for various generation expansion futures, in order to find adequate investment decisions .…”

Section: Introductionmentioning

confidence: 99%

Transmission and energy storage–expansion planning in the presence of correlated wind farms

Mahmoudi

Moghaddam

Alizadeh

2019

Int Trans Electr Energ Syst

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Summary With the increasing penetration level of renewable energies and the related problems to the stochastic nature of their output power, reliable decision making in power system expansion has faced new challenges. This paper presents a new stochastic structure for coordinating expansion planning of transmission and integrated wind farms along with energy storage systems in the electricity market environment. Thereupon, uncertainties pertained to the power output of wind farms, locational marginal prices (LMPs), and load demands have been taken into consideration. Neglecting the correlation between the wind speeds in multiple wind farms may lead to an increase in investment risk of the power system. Hence, this correlation is modeled through both Weibull probability distribution and Copula functions. The given results of the proposed structure applied to Garver 6‐bus test system and Guilan province 230, and 132‐kV transmission systems indicate the effectiveness of the Copula function.

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“…Taguchi method (TM) is another optimisation technique which is capable of providing near-optimal solution in less number of experiments [22][23][24][25][26][27]. It is successfully employed in manufacturing process to save millions of dollar by avoiding the revenue loss due to manufacturing defect in products at early stage of the process.…”

Section: Introductionmentioning

confidence: 99%

“…It is proved to be an efficient optimisation technique when number of input parameters is small but too large to allow for exhaustive search of every possible input value. In the literature, a very few power system problems are solved using TM such as economic dispatch [23], transmission expansion planning [24,26], optimum design of proportional integral controllers [25], power system state estimation [27] etc. However, in these studies, Taguchi factors, i.e.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective Taguchi approach for optimal DG integration in distribution systems

Meena

Swarnkar

Gupta

et al. 2017

IET Generation, Transmission & Distribution

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Uncertainty handling in power system expansion planning under a robust multi‐objective framework

Cited by 11 publications

References 31 publications

Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture

Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture

Transmission and energy storage–expansion planning in the presence of correlated wind farms

Multi‐objective Taguchi approach for optimal DG integration in distribution systems

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