Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model

Abstract-One of the major functions of a smart substation (SS) is to restore power supply to interrupted customers as quickly as possible after an outage. The high cost of a smart substation limits its widespread utilization. In this paper, a smart substation allocation model (SSAM) to determine the optimal number and allocation of smart substations in a given distribution system is presented, with the upgrade costs of substations and the interruption costs of customers taken into account. Besides, the reliability criterion is also properly considered in the model. By linearization strategies, the SSAM is simplified into a mixed integer linear programming problem which could be solved efficiently with commercial solvers. Finally, the performance of the proposed methodology is demonstrated by the standard RBTS-BUS 4 test system and a medium voltage power distribution system in Denmark.

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“…The load demand employed in the study cases is the average value in each of the 15 years with an annual load growth rate 5% [24].…”

Section: Case Studymentioning

confidence: 99%

Optimal Allocation of Smart Substations in a Distribution System Considering Interruption Costs of Customers

Sun

You

et al. 2018

IEEE Trans. Smart Grid

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“…To make it manageable, the robust counterpart is formulated based on the framework of robust linear optimization to derive the optimal solution immunized against uncertainty. The single-stage robust optimization [23,24] provides an efficient means to deal with uncertainty sets that occur in the objective function or inequality constraints, as shown in [25]. The symmetry of uncertainty sets is required, but it does not always apply to reality.…”

Section: Robust Counterpart Of the Proposed Modelmentioning

confidence: 99%

Determining the Minimal Power Capacity of Energy Storage to Accommodate Renewable Generation

Han

Liao

et al. 2017

Energies

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Abstract:The increasing penetration of renewable generation increases the need for flexibility to accommodate for growing uncertainties. The level of flexibility is measured by the available power that can be provided by flexible resources, such as dispatachable generators, in a certain time period under the constraint of transmission capacity. In addition to conventional flexible resources, energy storage is also expected as a supplementary flexible resource for variability accommodation. To aid the cost-effective planning of energy storage in power grids with intensive renewable generation, this study proposed an approach to determine the minimal requirement of power capacity and the appropriate location for the energy storage. In the proposed approach, the variation of renewable generation is limited within uncertainty sets, then a linear model is proposed for dispatchable generators and candidate energy storage to accommodate the variation in renewable generation under the power balance and transmission network constraints. The target of the proposed approach is to minimize the total power capacity of candidate energy storage facilities when the availability of existing flexible resources is maximized. After that, the robust linear optimization method is employed to convert and solve the proposed model with uncertainties. Case studies are carried out in a modified Garver 6-bus system and the Liaoning provincial power system in China. Simulation results well demonstrate the proposed optimization can provide the optimal location of energy storage with small power capacities. The minimal power capacity of allocated energy storage obtained from the proposed approach only accounts for 1/30 of the capacity of the particular transmission line that is required for network expansion. Besides being adopted for energy storage planning, the proposed approach can also be a potential tool for identifying the sufficiency of flexibility when a priority is given to renewable generation.

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“…In this study, it is used the LODF definition [5] in order to compute the postcontingency transmission constraints (9): Using the PTDF-based formulation and equation (9), it is possible to compute the N − 1 (m = 1) linear factor (10):…”

Section: ) Post-contingency Transmission Limitsmentioning

confidence: 99%

Stochastic security-constrained generation expansion planning methodology based on a generalized line outage distribution factors

Hinojosa

González-Longatt

2017

2017 IEEE Manchester PowerTech

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Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model

Cited by 142 publications

References 38 publications

Optimal Allocation of Smart Substations in a Distribution System Considering Interruption Costs of Customers

Optimal Allocation of Smart Substations in a Distribution System Considering Interruption Costs of Customers

Determining the Minimal Power Capacity of Energy Storage to Accommodate Renewable Generation

Stochastic security-constrained generation expansion planning methodology based on a generalized line outage distribution factors

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