Distributed adaptive expansion approach for transmission and distribution networks incorporating source-contingency-load uncertainties

Liu, Jia; Tang, Zao; Zeng, Peter Pingliang; Li, Yalou; Wu, Qiuwei

doi:10.1016/j.ijepes.2021.107711

Cited by 14 publications

(8 citation statements)

References 34 publications

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“…To avoid any scaling, ( 29) is replaced by (30) as the strict inequality constraint. Eventually, the final objective function can be defined by (31), where epsilon is a small value between 10 À3 and 10 À6 ,…”

Section: Augmented Epsilon-constraint Methodsmentioning

confidence: 99%

“…29 In a similar research, a distributed decision-making framework is used under the uncertainties of sources, loads and transmission lines. 30 A mixed-integer tri-level model is formulated for simultaneous expansion of transmission and distribution systems to provide higher operation flexibility and reduce the total cost. 31 Reference [032] proposes a robust model for expansion planning of multi-microgrid and active distribution networks with the considerationof responsive loads and the generation contingency.…”

Section: Literature Reviewmentioning

confidence: 99%

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Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Azari

Tabar

Tohidi

2022

Intl J of Energy Research

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Summary Due to the increase in global warming and environmental pollution, heavy penalties have been imposed on pollution producers such as electrical energy networks. Hence, the role of renewable resources expansion in power systems is unavoidable. However, their high penetration increases the uncertainties and decreases the reliability. This paper investigates the expansion of renewable resources in distribution systems based on the zero energy concept. In this regard, different scenarios are designed to determine the optimal location and sizing of wind turbines and photovoltaics as the most matured technologies. To achieve such a goal, a multiobjective linear programming consisting of investment cost and environmental pollution is suggested, which is solved by the augmented epsilon constraint method. Moreover, an incentive‐based demand response program is implemented using shiftable and curtailable responsive loads. Eventually, the uncertainties of renewable resources are modeled by a scenario generation and reduction approach to simulate realistic conditions. The results show that the system that includes only wind turbines or only photovoltaics cannot completely overcome the pollution problem due to the uncertainties. By contrast, a zero energy structure is achievable by their combination, where the investment cost is increased by 73.17% and 48.13% compared to the separate expansion of photovoltaics and wind turbines, respectively. The participation of responsive loads decreases the investment cost by 49.29% as well. Furthermore, the uncertainties of renewable resources increase the total cost by only about 5.95% in the presence of responsive loads; however, the system will be robust against at least 6% of wind turbines and photovoltaics fluctuations.

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Section: Augmented Epsilon-constraint Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Azari

Tabar

Tohidi

2022

Intl J of Energy Research

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“…The advantage of facilitating TSO-DSO interactions in a distributed way is that the number of constraints and variables of the transmission-distribution coordination is reduced. It is then available for the solver to handle large-scale co-optimization problems [7]. Another advantage of the distributed optimization is that, by taking the substations between transmission and distribution networks as the boundaries, the data privacy of each subnetwork can be protected and all the subnetworks' information required by the substations is communicated at the boundary buses [8].…”

Section: Index Terms-distributed Optimization Distribution Expansion ...mentioning

confidence: 99%

“…Note that the left side of ( 5) limits P loss ij,s , which equivalently limits the capacity of line ij. The branch flow equations are enforced in (7) and (8). Equations ( 9)-( 21) relate the convex hulls of the nonconvex ac power flow constraint v i,s v j,s sinθ ij,s = 22) constrains the bus voltage.…”

Section: Socp-based Expansion Modelmentioning

confidence: 99%

Fully Distributed Second-Order Cone Programming Model for Expansion in Transmission and Distribution Networks

Liu

Tang

Zeng

et al. 2022

IEEE Systems Journal

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Active (MW) and reactive (MVar) power outputs of generations at bus i in scenario s P ij,s , Q ij,s Active (MW) and reactive (MVar) power flows of line ij in scenario s P loss ij,s , Q loss ij,s Active (MW) and reactive (MVar) power losses of line ij in scenario s u ij Binary variable representing whether line ij is constructed or not V i,s Voltage magnitude square at bus i in scenario s (p.u. 2 ) v i,s Voltage magnitude at bus i in scenario s (p.u.) θ i,s Voltage phase angle at bus i in scenario s (rad) θ ij,s Voltage phase angle difference of line ij in scenario s (rad) I. INTRODUCTION

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“…In Ref. (Liu et al, 2020;Liu et al, 2022), two effective expansion planning methods for transmission and active distribution networks were proposed, where the uncertainties associated with supply (PV and WT generation) and demand (electric load) factors were fully analyzed and discussed so that a better economic efficiency and reliability can be achieved.…”

Section: Introductionmentioning

confidence: 99%

Low-Carbon Strategic Planning of Integrated Energy Systems

Guo

Xiang

2022

Front. Energy Res.

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With the rapid promotion of renewable energy technologies and the trend to a low-carbon society, the positive impacts of an integrated energy system that realizes various forms of energy-utilizing improvement and carbon reduction have fully emerged. Hydrogen with a decarbonized characteristic being integrated into the integrated energy system has become a viable option to offset the intermittency of renewables and decline the fossil fuel usage. An optimal planning model of a wind–photovoltaic–hydrogen storage-integrated energy system with the objective of total economic and environmental cost minimization by considering various energy technology investments is proposed. Case studies are developed to compare the economic and environmental benefits of different energy investment scenarios, especially hydrogen applications. The cost–benefit analysis was carried out to prove that hydrogen investment is not a cost-competitive option but can alleviate the burden of carbon emissions somehow. Finally, sensitivity analysis of key parameters of sale capacity, carbon tax, and renewable penetration level was performed to indicate the rational investment for a wind–photovoltaic–hydrogen storage-integrated energy system.

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Distributed adaptive expansion approach for transmission and distribution networks incorporating source-contingency-load uncertainties

Cited by 14 publications

References 34 publications

Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Stochastic multi‐objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Fully Distributed Second-Order Cone Programming Model for Expansion in Transmission and Distribution Networks

Low-Carbon Strategic Planning of Integrated Energy Systems

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