A Chance Constrained Transmission Network Expansion Planning Method With Consideration of Load and Wind Farm Uncertainties

Yu, Hoi-Lai; Chung, C.Y.; Wong, Kit Po; Zhang, J.H.

doi:10.1109/tpwrs.2009.2021202

Cited by 302 publications

(178 citation statements)

References 33 publications

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“…The operation costs contain the cost of power purchases from the grid (C grid ), cost of power purchases from DGs (C DG ), cost of compensation DGs (C payDG ) and cost of compensation ILs (C RL ). Chance constrained programming [26] is adopted to deal with the multi-state models of WT-PV outputs. CCP can be used to solve the optimization problem with uncertain factors under the given confidence level, which is suitable for solving the scheduling problem in this paper that takes the uncertain outputs of REGs into consideration.…”

Section: Initial Optimizationmentioning

confidence: 99%

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Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

et al. 2017

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Abstract:With large-scale integration of distributed energy resources (DERs), distribution networks have turned into active distribution networks (ADNs). However, management risks and obstacles are caused by this in due to renewable energy generation (REG) forecasting errors. In this paper, a day-ahead active power scheduling method considering REG forecast errors is proposed to eliminate the risks, minimize the costs of distribution companies and achieve optimal power flow. A hierarchical coordination optimization model based on chance constrained programming is established to realize day-ahead optimal scheduling of active power in ADNs coordinated with network reconfiguration, achieving an optimal solution of network topologies and DER outputs. The hierarchical method includes three levels: the first level provides initial values, and multiple iterations between the second and third level are used to solve the multi-period mixed integer nonlinear optimization problem. The randomness due to REG forecast errors is tackled with chance constrained programming in the scheduling procedure. The hybrid particle swarm optimization algorithm is employed to solve the proposed model. Simulation results verify the validity of the proposed method with an improved 33 nodes distribution network.

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Section: Initial Optimizationmentioning

confidence: 99%

“…The outputs of controllable DGs and the exploitation of ILs in each period are optimized with an optimization objective of the operation costs of DISCOs, and CCP is employed to solve the multi-state models of WT-PV outputs. minF t 3 (26) The constraints are as follows: Probability constraint of the objective:…”

Section: Der Optimizationmentioning

confidence: 99%

Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

et al. 2017

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“…Equation (14) expresses the amount of power to be exchanged between zones as a function of both price and voltage magnitudes. This is not economically desired or interpretable and is not consistent with the existing pricing mechanisms [17].…”

Section: B Static Transmission Planning Problem (Step)mentioning

confidence: 99%

A Market-Based Transmission Planning for HVDC Grid—Case Study of the North Sea

Torbaghan

Gibescu

Rawn

et al. 2015

IEEE Trans. Power Syst.

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Abstract-There is significant interest in building HVDC transmission to carry out transnational power exchange and deliver cheaper electricity from renewable energy sources which are located far from the load centers. This paper presents an approach to solve a long-term transmission planning problem for meshed VSC-HVDC grids that connect regional markets. This is in general a nonlinear non-convex large-scale optimization problem with high computational burden, partly due to the many combinations of wind and load that become possible. We developed a two-step iterative algorithm that first selects a subset of operating hours using a clustering technique, and then seeks to maximize the social welfare of all regions and minimize the investment capital of transmission infrastructure subject to technical and economic constraints. The outcome of the optimization is an optimal grid design with a topology and transmission capacities that results in congestion revenue paying off investment by the end the project's economic lifetime. Approximations are made to allow an analytical solution to the problem and demonstrate that an HVDC pricing mechanism can be consistent with an AC counterpart existing onshore. The model is used to investigate development of the offshore grid in the North Sea. Simulation results are interpreted in economic terms and show the effectiveness of our proposed two-step approach.

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“…The impacts of regulatory interventions on wind power expansion generation planning are investigated in [3]. The reliability of composite generation and transmission system with large-scale WG integration can be found in [4], and the effect of wind and load forecast errors on the power system expansion planning is presented in [5]. A simple approach using the annual load duration curve to evaluate the potential base and peak load savings by the installation of wind power has been presented by [6].…”

Section: Introductionmentioning

confidence: 99%

Generation expansion planning considering integrating large-scale wind generation

Zhang

Ding

Østergaard

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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Abstract-Generation expansion planning (GEP) is the problem of finding the optimal strategy to plan the construction of new generation while satisfying technical and economical constraints. In the deregulated and competitive environment, large-scale integration of wind generation (WG) in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. A bi-level generation expansion planning approach considering large-scale wind generation was proposed in this paper. The first phase is investment decision, while the second phase is production optimization decision. A multi-objective PSO (MOPSO) algorithm was introduced to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of the proposed bi-level planning approach and the MOPSO algorithm have been verified by a numerical test system.

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A Chance Constrained Transmission Network Expansion Planning Method With Consideration of Load and Wind Farm Uncertainties

Cited by 302 publications

References 33 publications

Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

A Market-Based Transmission Planning for HVDC Grid—Case Study of the North Sea

Generation expansion planning considering integrating large-scale wind generation

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