Moving beyond the optimal transmission switching: stochastic linearised SCUC for the integration of wind power generation and equipment failures uncertainties

Nikoobakht, Ahmad; Aghaei, Jamshid; Mardaneh, Mohammad; Niknam, Taher; Vahidinasab, Vahid

doi:10.1049/iet-gtd.2017.0617

Cited by 25 publications

(29 citation statements)

References 30 publications

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“…Constraints (24), (25) and (26) indicate limits on charging and discharging power of bes. Equation (27) calculates the energy stored E bes, t, sp in storage unit bes at hour t for wind scenario sp.…”

Section: Bes Modelmentioning

confidence: 99%

“…System operator uses DC power flow to change SCUC into MILP problem for simplicity and speed. [23][24][25] Injection shift factor (ISF)is used for the DC power flow, 18,26 because it minimizes the variables. Its main drawback, however, lies in the line contingency state in SCUC that requires a large number of coefficients in line flow calculations resulting into huge models with heavy computation requirement.…”

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confidence: 99%

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Stochasticsecurity constrained unit commitmentwith battery energy storage and wind power integration

Gupta

Jain

Kalkhambkar

et al. 2020

Int Trans Electr Energ Syst

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Large penetration of intermittent wind power creates reliability and system security issues in power system operation which can be alleviated by providing energy storage systems (ESS). In this view, this paper proposes stochastic security constrained unit commitment (SCUC) framework with battery energy storage (BES) considering wind power uncertainty and N-1-line contingency criteria. The uncertain wind power is modeled through probable scenarios. In addition, use of N-1 security criteria for pre and post line contingency is modeled using DC power flow. Conventionally, injection shift factor (ISF) are used in power flow equations however, N-1 security formulation is computationally heavy and takes huge time. This work proposes the use of line outage distribution factor (LODF) to reduce the number of non-zero coefficients of post contingency DC security constraints for improving computational requirement. Mathematical model is complex mixed integer linear programming (MILP) problem and solved using benders decomposition for modified IEEE reliability test system and 118-bus system. The results analyze the impact of BES, total operating costs with LODF and ISF, locational marginal price (LMP), wind curtailment, BES scheduling and computation time. The proposed model is economically beneficial for power system operations under large wind penetration. K E Y W O R D S battery energy storage, line outage distribution factor, security constrained unit commitment and wind integration 1 | INTRODUCTION Renewable integration is increasing at a faster rate owing to its environmental benefits and negligible operational cost. However, large plants like wind farms are located at the remote geographical area with limited network capability and low nearby loads. High wind penetration in such regions may produce transmission congestion. Also, large uncertainty

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Section: Bes Modelmentioning

confidence: 99%

mentioning

confidence: 99%

Stochasticsecurity constrained unit commitmentwith battery energy storage and wind power integration

Gupta

Jain

Kalkhambkar

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

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“…In this regard, a model for AC power flow (ACPF) using the piecewise linear (PWL) method is presented in [10] for applying to demand response studies. Moreover, in [9], a model for security-constrained unit commitment and optimal transmission switching is proposed based on the ACOPF constraints for managing RESs uncertainties and particular outage events. Furthermore, in distribution level, a linear model for ACPF is developed in [11], which can be implemented only in radial networks without any distributed generation.…”

Section: Nomenclaturementioning

confidence: 99%

Robust linear model for multi‐period AC optimal power flow

Heidarabadi

Pourahmadi

Hossieni

2020

IET Generation Trans & Dist

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In the near future power systems, efficient management of uncertainties with considering the system constraints without any simplification will be a challenge for system operators. Considering AC constraints leads to providing more accurate schedule of generating units, which can have a significant impact on the reduction of operating costs. Although numerous studies have been done to convexify AC optimal power flow constraints, most of the models are non-linear, which can be intractable for large-scale systems. In this study, a novel linear robust AC model is introduced using a combination of the quadratic convex relaxation (QCR) and the Frank-Wolfe algorithm for linearising the AC constraints. The uncertainties are modelled by applying the robust optimisation with recourse to obtain an optimal schedule for the conventional units in multiperiod real-time markets. The Benders-dual algorithm is implemented to solve the optimisation problem. The proposed model was applied to the IEEE 3-bus, 118-bus, and 300-bus systems. The results indicate that the proposed algorithm obtains more precise approximation than the QCR method. In addition, the costs and losses of the proposed model are less than those of the conventional robust DC and stochastic models. Furthermore, because the proposed model is linear, its runtime is rational. NomenclatureIndices i, j index of buses, 1 to N b t index of time intervals, 1 to T k index of generating units, 1 to N g w index of wind power plants, 1 to N w Decision variablest active/reactive power outputs of generating unit k in time interval t V i, t voltage magnitude of bus i in time interval t θ i, t the voltage phase angle of bus i in time interval t κ i, j, t auxiliary complex variable replacing the product of V i, t ∠θ i, t and V j, t ∠ − θ j, t ϑ i, t auxiliary variable replacing V i, t 2 cs i, j, t /sn i, j, t auxiliary variable replacing cos θ i, t − θ j, t /sin θ i, t − θ j, t . σ i, j, t /ψ i, j, t auxiliary variable replacing the real/imaginary parts of κ i, j, t Λ i, j, t auxiliary variable replacing the product of V i, t

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“…In [5], the authors designed a developed energy hub and presented a mathematical formulation for deterministic and stochastic situations of renewable resources, power demand, and price. Papers such as [6,7] have deployed transmission switching in a UC problem to improve wind power utilisation and grid flexibility. However, they have neglected demand-side activities.…”

Section: Introductionmentioning

confidence: 99%

Power system flexibility improvement with a focus on demand response and wind power variability

Dadkhah¹,

Vahidi²,

Shafie‐khah³

et al. 2020

IET Renewable Power Generation

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Unpredictable system component contingencies have imposed vulnerability on power systems, which are under high renewables penetration nowadays. Intermittent nature of renewable energy sources has made this unpredictability even worse than before and calls for excellent adaptability. This study proposes a flexible security-constrained structure to meet the superior flexibility by coordination of generation and demand sides. In the suggested model, demand-side flexibility is enabled via an optimum real-time (RT) pricing program, while the commitment of conventional units through providing up and down operational reserves improves the flexibility of supply-side. The behaviour of two types of customers is characterised to define an accurate model of demand response and the effect of customers' preferences on the optimal operation of power networks. Conclusively, the proposed model optimises RT prices in the face of contingency events as well as wind power penetration. System operators together with customers could benefit from the proposed method to schedule generation and consumption units reliably.

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Moving beyond the optimal transmission switching: stochastic linearised SCUC for the integration of wind power generation and equipment failures uncertainties

Cited by 25 publications

References 30 publications

Stochasticsecurity constrained unit commitmentwith battery energy storage and wind power integration

Stochasticsecurity constrained unit commitmentwith battery energy storage and wind power integration

Robust linear model for multi‐period AC optimal power flow

Power system flexibility improvement with a focus on demand response and wind power variability

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