Network Planning in Unbundled Power Systems

Buygi, Majid Oloomi; Shanechi, H.M.; Balzer, Gerd; Shahidehpour, Mohammad; Pariz, Naser

doi:10.1109/tpwrs.2006.873016

Cited by 97 publications

(55 citation statements)

References 11 publications

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“…where ,tech,g,c, it PG is the generated power of unit in bus i with technology tech and capacity g during contingency c in year t. The amount of ,tech,g,c, it PG is limited to its capacity in (5). The capacity can be changed due to new generation units installation during planning horizon.…”

Section: A the Model Without Consideration Of Robustnessmentioning

confidence: 99%

Reliability‐based model for generation and transmission expansion planning

Ahmadi

Mavalizadeh

Zobaa

et al. 2017

IET Generation, Transmission & Distribution

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This paper presents a mixed integer linear multi-objective model based on information gap decision theory (IGDT), which is used to solve coordinated multiyear generation and transmission expansion planning (G&TEP) problems. The model maximizes the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission, and fuel availability are considered. A multi-objective method called the ε-constraint method is used here to maximize the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24 bus IEEE test system. The numerical results show the good performance of the model.

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Section: A the Model Without Consideration Of Robustnessmentioning

confidence: 99%

Reliability‐based model for generation and transmission expansion planning

Ahmadi

Mavalizadeh

Zobaa

et al. 2017

IET Generation, Transmission & Distribution

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“…Uncertainty derived from load and generation is usually tackled by scenario technique [17]. Scenarios of DG production as well as load are divided into summer and winter, weekday and weekend, and 24 hours a day in [11].…”

Section: A Including Load and Pv Uncertaintiesmentioning

confidence: 99%

Distribution network planning with a large amount of small scale photovoltaic power

Martínez

Huang

Söder

2013

2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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Abstract-This paper presents a new method to assist distribution system operators assessing the capacity of each bus for connecting more photovoltaic power in a low voltage distribution network. The developed method takes the uncertainties from load and generation into account. Moreover, it applies probabilistic voltage limits in the assessment process. An improved linear power flow analysis is used in the process. Furthermore, a case study in a Swedish low voltage network is discussed to apply the proposed method on assessing the maximum photovoltaic peak power that can be installed into a distribution network without violating probabilistic voltage limits. A comparison between deterministic approach and probabilistic approach is also performed.

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“…For this purpose, the uncertainties can be represented by scenario techniques, decision trees, and/or fuzzy sets [23,24].…”

Section: External Uncertaintiesmentioning

confidence: 99%