Security-constrained unit commitment in AC microgrids considering stochastic price-based demand response and renewable generation

Vahedipour-Dahraei, Mostafa; Najafi, Hamidreza; Anvari‐Moghaddam, Amjad

doi:10.1002/etep.2596

Cited by 36 publications

(24 citation statements)

References 41 publications

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“…The problem explained above is a nonlinear one due to the bilinear product of terms E D t;ω ρ D r 0 ;t , E Ch t;ω ρ Ch r 0 ;t , and E Dis t;ω ρ Dis r 0 ;t in (4). To derive the single-level formulation, the KKT optimality conditions of the lower-level problem (5) and (13) to (22) are obtained and incorporated in the upper-level problem. Then the bilinear terms are also replaced with their equivalent expressions using the strong duality theorem 21,25 as below: By using KKT conditions and strong duality theorem, the lower-level problem is obtained and is solved as a single-level MILP problem.…”

Section: Equivalent Linear Single-level Problemmentioning

confidence: 99%

Stochastic risk-constrained decision-making approach for a retailer in a competitive environment with flexible demand side resources

Rashidizadeh‐Kermani

Vahedipour‐Dahraie

Anvari‐Moghaddam

et al. 2018

Int Trans Electr Energ Syst

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Summary This paper presents a risk‐averse stochastic bi‐level programming approach to solve decision‐making of a retailer in a competitive market under uncertainties. The retailer decides the level of involvement in day‐ahead (DA) and regulation markets by making an optimal bidding strategy with the goal of expected profit maximization. Uncertainties associated with DA prices, up/down regulation market prices, customers' demand, and rival retailers' behaviors are tackled through a stochastic programming model. In the proposed model, responsive loads and electric vehicles (EVs) track the real‐time prices and choose the proper retailer to minimize their payments in the competitive trading floor. The obtained nonlinear stochastic model is transformed into an equivalent linear single‐level program by replacing the lower‐level problem with its Karush‐Kuhn‐Tucker optimality conditions and using duality theory. Finally, the proposed methodology is evaluated by applying to a realistic case study, and the results demonstrate the effectiveness of the proposed framework.

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Section: Equivalent Linear Single-level Problemmentioning

confidence: 99%

Stochastic risk-constrained decision-making approach for a retailer in a competitive environment with flexible demand side resources

Rashidizadeh‐Kermani

Vahedipour‐Dahraie

Anvari‐Moghaddam

et al. 2018

Int Trans Electr Energ Syst

Self Cite

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“…Finally, the price elasticity of loads is extracted from Vahedipour‐Dahraie et al The forecasted errors are generated based on 1000 scenarios by using MCS and RWM. After generation of 1000 initial scenarios, K ‐means algorithm is used to reduce the number of scenarios into 45 . Afterwards, the selected scenarios are used in the proposed problem and the optimization is executed by CPLEX solver using GAMS software on a PC with 4 GB of RAM and Intel Core i7 @ 2.60 GHz processor.…”

Section: Simulations and Numerical Resultsmentioning

confidence: 99%

“…After generation of 1000 initial scenarios, K-means algorithm is used to reduce the number of scenarios into 45. 32 Afterwards, the selected scenarios are used in the proposed problem and the optimization is executed by CPLEX solver using GAMS software 33 on a PC with 4 GB of RAM and Intel Core i7 @ 2.60 GHz processor.…”

Section: Case Studymentioning

confidence: 99%

A stochastic bi‐level decision‐making framework for a load‐serving entity in day‐ahead and balancing markets

Rashidizadeh‐Kermani

Vahedipour‐Dahraie

Anvari‐Moghaddam

2019

Int Trans Electr Energ Syst

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Summary This paper investigates a stochastic bi‐level scheduling model for decision‐making of a load‐serving entity (LSE) in competitive day‐ahead (DA) and regulating markets with uncertainties. In this model, LSE as the main interacting player of the market sells electricity to end‐use customers and plug‐in electric vehicles (PEVs) to maximize its expected profit. Therefore, a two‐level decision‐making process with different objectives is considered to solve the problem. In one level, the objective is to maximize the LSE's profit by optimally scheduling of responsive loads and PEVs charging/discharging process, while in the other level, the payments of the customers and PEV owners should be minimized in a competitive market. In the proposed decision‐making process, to model the uncertainties, market prices, required energy of customers and PEVs, and the rival LSEs' prices are considered as random variables. The bi‐level stochastic problem is then converted into a linear single‐level stochastic model with equilibrium constraints by using Karush‐Kuhn‐Tucker (KKT) optimality conditions as well as duality theory. A case study is implemented to indicate the applicability of the intended model. The applicability of the proposed model is tested on Nordic market and the results show that in a competitive market, the LSE can increase its revenue and attract more demand loads and PEV owners by offering more moderate prices.

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“…This happens when bus j is the parent of bus i (β ij = 1), or bus i is the parent of bus j (β ji = 1). Equation (6) indicates that every bus other than substation bus should have one parent, where Equation (7) states that the substation bus has no parents.…”

Section: Hourly Reconfiguration Of Distribution Systemmentioning

confidence: 99%

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

et al. 2018

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Due to the recent developments in the practical implementation of remotely controlled switches (RCSs) in the smart distribution system infrastructure, distribution system operators face operational challenges in the hourly reconfigurable environment. This paper develops a stochastic Model Predictive Control (MPC) framework for operational scheduling of distribution systems with dynamic and adaptive hourly reconfiguration. The effect of coordinated integration of energy storage systems and demand response programs through hourly reconfiguration on the total costs (including cost of total loss, switching cost, cost of bilateral contract with power generation owners and responsive loads, and cost of exchanging power with the wholesale market) is investigated. A novel Switching Index (SI) based on the RCS ages and critical points in the network along with the maximum number of switching actions is introduced. Due to nonlinear nature of the problem and several existing binary variables, it is basically considered as a Mixed Integer Non-Linear Programming (MINLP) problem, which is transformed into a Mixed Integer Linear Programming (MILP) problem. The satisfactory performance of the proposed model is demonstrated through its application on a modified IEEE 33-bus distribution system.

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Security-constrained unit commitment in AC microgrids considering stochastic price-based demand response and renewable generation

Cited by 36 publications

References 41 publications

Stochastic risk-constrained decision-making approach for a retailer in a competitive environment with flexible demand side resources

Stochastic risk-constrained decision-making approach for a retailer in a competitive environment with flexible demand side resources

A stochastic bi‐level decision‐making framework for a load‐serving entity in day‐ahead and balancing markets

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

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