Reliability-Security Constrained Unit Commitment based on benders decomposition and Mixed Integer Non-Linear Programming

Gupta, Pranda Prasanta; Jain, Prerna; Sharma, Sunil; Bhakar, Rohit

doi:10.1109/comptelix.2017.8003988

Cited by 19 publications

(6 citation statements)

References 10 publications

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“…The optimal size of an ESS is calculated using one of the optimization techniques. Some of those techniques are mixed-integer linear programming (MILP) [8], mixedinteger non-linear programming (MINLP) [14], dynamic programming (DP) [15], [16], particle swarm optimization (PSO) [17], two-stage stochastic programming [18], distributionally robust optimization [19], model predictive control (MPC) [20]. The parameters of optimization problems could be either certain or uncertain.…”

Section: Index Termsmentioning

confidence: 99%

Optimizing a Distributed Wind-Storage System Under Critical Uncertainties Using Benders Decomposition

2019

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Section: Index Termsmentioning

confidence: 99%

Optimizing a Distributed Wind-Storage System Under Critical Uncertainties Using Benders Decomposition

2019

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“…One of the optimization techniques is used to calculate the ideal size of an ESS. Some of these methods are mixed-integer linear programming (MILP) [8], mixed-integer non-linear programming (MINLP) [16], dynamic programming (DP) [17,18], particle swarm optimization (PSO) [19], two-stage stochastic programming [20], distributionally robust optimization [21], model predictive control (MPC) [22]. The optimization problems parameters may be either certain or uncertain.…”

Section: Literature Reviewmentioning

confidence: 99%

“…where E ESS t is the energy stored in the ESS at hour t. The equation for calculating the charging status at a particular hour is formulated in (16). Charging status is the stored energy and techniques are established to optimize it [78].…”

Section: Energy Storage System Constraintsmentioning

confidence: 99%

Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

2019

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In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize total investment and operation expenses. A constrained optimization problem is solved using an optimization technique to optimize a storage system. This problem of optimization may be deterministic or probabilistic. In case of optimizing the size of a BESS connected to a system containing renewable energy sources, solving a probabilistic optimization problem is more effective because it is not possible to accurately determine the forecast of their output power. In this paper, using the stochastic programming technique to discover the optimum size of a BESS to connect to a grid-connected microgrid comprising wind power generation, a probabilistic optimization problem is solved. A comparison is then produced to demonstrate that solving the problem using stochastic programming provides better outcomes and to demonstrate that the reliability of the microgrid improves after it is connected to a storage system. The simulation findings demonstrate the efficacy of the optimum sizing methodology proposed.

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“…Optimal sizing of an ESS is done through one of the optimisation methods. It can be sized using the mixed‐integer linear programming (MILP) [6], mixed‐integer non‐LP (MINLP) [10], dynamic programming [11], particle swarm optimisation [12], two‐stage stochastic programming [13], distributionally robust optimisation [14], and model predictive control [15]. Optimisation problems are either deterministic or probabilistic.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the reliability of a microgrid through optimal size of battery ESS

Abdulgalil

Khalid

2019

IET Generation, Transmission & Distribution

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Reliability-Security Constrained Unit Commitment based on benders decomposition and Mixed Integer Non-Linear Programming

Cited by 19 publications

References 10 publications

Optimizing a Distributed Wind-Storage System Under Critical Uncertainties Using Benders Decomposition

Optimizing a Distributed Wind-Storage System Under Critical Uncertainties Using Benders Decomposition

Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

Enhancing the reliability of a microgrid through optimal size of battery ESS

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