Transmission Network Expansion Planning Considering Uncertainty in Demand

Silva, Id.J.; Rider, Marcos J.; Romero, Rubén; Murari, Carlos Alberto Favarin

doi:10.1109/tpwrs.2006.881159

Cited by 98 publications

(13 citation statements)

References 11 publications

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“…The constraint in Equation (15) (17) and (18), respectively. Equation (19) limits the phase angle between two nodes. Equation (20) means that x l is 1 for existing transmission lines and Equation (21) states that x l is a binary variable for investment candidates.…”

Section: Model Formulationmentioning

confidence: 99%

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Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times

et al. 2018

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Investment options of transmission expansion planning (TEP) involve different lead times according to their length, technology, and environmental and social impacts. TEP planners can utilize the various lead times to deal with the risk of uncertainty. This paper proposes a novel framework for TEP under an uncertain environment, which includes investment options with various lead times. A multi-stage model is developed to reflect the different lead times in the planning method. The level of demand uncertainty is represented using a relative standard deviation. Demand uncertainty in the presented multi-stage model and its influence on the optimal decision are studied. The problem is formulated as a mixed integer linear problem to which stochastic programming is applied, and the proposed framework is illustrated from case studies on a modified Garver's six-bus system. The case studies verify the effectiveness of the framework for TEP problems with a mathematically tractable model and demonstrates that the proposed method achieves better performance than other methods when the problems involve investment candidates with various lead times under uncertain conditions. Transmission planning activities are divided into several steps according to reliability criteria, while evaluating long-term reliability of transmission networks requires statistical approaches. The amount of load shedding is one of the reliability criteria. An objective function minimizes the sum of the investment cost and expected load-shedding cost [5]. Another reliability criterion is loss of load expectation [6], in which two probabilistic reliability criteria were applied to transmission planning activity: the transmission system and its bus/nodal framework. Deterministic reliability criteria are usually used to evaluate the operating reliability of a transmission network, and the (N-α) contingency criterion is the most widely used method to evaluate the security of transmission networks [7]. To circumvent investigating the whole contingency set, an adjustable robust optimization approach was proposed in Reference [8]. Recent changes in power generation mix require that operating reliability criteria incorporate the characteristics of renewable energy sources. Uncertainty regarding wind power generation was considered in transmission network expansion planning [9], where a combined Monte Carlo and probabilistic power flow analysis method was used with a chance-constrained approach. The interactions of wind power generation and dynamic thermal ratings of transmission lines were investigated in Reference [10], and the authors suggested that constructing new transmission corridors may not be the optimal transmission network reinforcement strategy when wind power generation is connected. Fault analysis and stability analysis are usually the final steps of transmission planning activities [11]. The technical analysis requires a pre-optimized network configuration and different types of parameters for generation and transmission. In this step, the engine...

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Section: Model Formulationmentioning

confidence: 99%

“…the worst case in a given interval of possible demand values. In Reference [19], long-term demand uncertainty was modeled by a generalized version of a deterministic peak demand.…”

Section: Introductionmentioning

confidence: 99%

Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times

et al. 2018

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“…Uncertainties of load prediction [1], wind power generation [2], and availability of power system facilities [3] are common types of these uncertainties. Many approaches have been proposed to deal with uncertainties in TEP problem.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Robust dynamic network expansion planning considering load uncertainty

Sarhadi

Amraee

2015

International Journal of Electrical Power & Energy Systems

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“…Versions of this algorithm are applied by Jalilzadeh et al [37,38] and Escobar et al [19,20]. We refer the interested reader to the papers [18,28,57,59,60] for further applications and modifications of genetic algorithms for TEP problem not discussed in this chapter.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Algorithms and Models for Transmission Expansion Planning

2011

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This chapter presents an overview of algorithms and optimization models used for solving Transmission Expansion Planning (TEP) problem. Being a very complex problem TEP attracts much attention from both researchers and practitioners. A great number of publications in the technical literature address this problem by providing various optimization models and applying different algorithms to solve the TEP problem. Besides literature review and brief classification of the proposed algorithms and models this survey covers examples for most of the methods.

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Transmission Network Expansion Planning Considering Uncertainty in Demand

Cited by 98 publications

References 11 publications

Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times

Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times

Robust dynamic network expansion planning considering load uncertainty

Algorithms and Models for Transmission Expansion Planning

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