A Dynamic Piecewise Linear Model for DC Transmission Losses in Optimal Scheduling Problems

Santos, T.N.; Diniz, André Luiz

doi:10.1109/tpwrs.2010.2057263

Cited by 88 publications

(42 citation statements)

References 19 publications

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“…The cost function can be estimated with a linear method [28], a piece-wise linear method [29] or second order polynomials, such as 2 0 (Re( )) Re( ) Re( )…”

Section: B Comparison With the Normal Dt Methodsmentioning

confidence: 99%

Distributed Optimization-Based Dynamic Tariff for Congestion Management in Distribution Networks

Huang

Zhao

et al. 2019

IEEE Trans. Smart Grid

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“…The cost function can be estimated with a linear method [28], a piece-wise linear method [29] or second order polynomials, such as 2 0 (Re( )) Re( ) Re( )…”

Section: B Comparison With the Normal Dt Methodsmentioning

confidence: 99%

Distributed Optimization-Based Dynamic Tariff for Congestion Management in Distribution Networks

Huang

Zhao

et al. 2019

IEEE Trans. Smart Grid

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“…Each bus also considers half of the losses associated with the branches connected to it [5], [18], [27], such that the system branch energy losses can be included in the formulation.…”

Section: B Nodal Power Balance Considering Branch Lossesmentioning

confidence: 99%

Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration

Zhang

Rahbari-Asr

Duan

et al. 2016

IEEE Trans. Sustain. Energy

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Day-ahead scheduling of generation units and storage devices is essential for the economic and efficient operation of a power system. Conventionally, a control center calculates the dispatch schedule by gathering information from all of the devices. However, this centralized control structure makes the system vulnerable to single point of failure and communication failures, and raises privacy concerns. In this paper, a fully distributed algorithm is proposed to find the optimal dispatch schedule for a smart grid with renewable and energy storage integration. The algorithm considers modified DC power flow constraints, branch energy losses, and energy storage charging and discharging efficiencies. In this algorithm, each bus of the system is modeled as an agent. By solely exchanging information with its neighbors, the optimal dispatch schedule of the conventional generators and energy storage can be achieved in an iterative manner. The effectiveness of the algorithm is demonstrated through several representative case studies.

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“…Linear losses are always greater than quadratic losses because the linear approximation uses only 1 line segment in our formulation. The loss estimation may improve by escalating the number of line segments used in the formulation …”

Section: Numerical Examplesmentioning

confidence: 99%

A computational comparison of 2 mathematical formulations to handle transmission network constraints in the unit commitment problem

Hinojosa

Gutiérrez-Alcaraz

2017

Int. Trans. Electr. Energ. Syst.

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Summary Until recently, transmission network constraints have been incorporated into the unit commitment (UC) problem (security‐constrained UC [SCUC]) using the classical direct current (DC)–based equation. This paper proposes a new formulation to model network constraints in the UC problem by using the power transfer distribution factor (PTDF). The classical formulation uses the binary commitment status, the power generation, and the voltage‐phase angles as decision variables. For the proposed formulation, the nodal balance equality constraints are modeled using one equality constraint, and the transmission network constraints have been modeled using the PTDF and the active power generation (decision variables). The main advantage of this formulation is the reduction of decision variables in the operation problem in comparison with the classical DC formulation. Transmission losses, using a piecewise linear approximation, are included in the SCUC problem as well. Both formulations are validated and tested on the Institute of Electrical and Electronics Engineers (IEEE) 14‐bus, the IEEE 30‐bus, the IEEE 57‐bus, and the IEEE 118‐bus. The IEEE 14‐bus and IEEE 57‐bus systems are used to compare the loss and the lossless models. The results show that the PTDF‐based formulation, which requires fewer continuous variables and equality constraints than the classical DC formulation, reduces the simulation time without sacrificing optimality. The results also demonstrate the feasibility of the proposed formulation to address the SCUC problem and its potential applicability to medium‐scale and large‐scale power systems.

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A Dynamic Piecewise Linear Model for DC Transmission Losses in Optimal Scheduling Problems

Cited by 88 publications

References 19 publications

Distributed Optimization-Based Dynamic Tariff for Congestion Management in Distribution Networks

Distributed Optimization-Based Dynamic Tariff for Congestion Management in Distribution Networks

Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration

A computational comparison of 2 mathematical formulations to handle transmission network constraints in the unit commitment problem

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