Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties

Zhou, Zhi-Ang; He, Chuan; Liu, Tianqi; Dong, Xiaojing; Zhang, Kun; Dang, Dongsheng; Chen, Baorui

doi:10.1109/access.2020.3032560

Cited by 17 publications

(14 citation statements)

References 36 publications

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“…It should be noted that interest rate and lifetime of planning problem are defined to annualize the scale of long-term investment sub-problem with operational sub-problem. The total investment cost (23) includes the invest-ment cost of newly installed transmission lines (25) and BESS modules (26). The total operational cost is presented in (24), which includes the operational cost of the generating units (27), the BESS modules (28) with the fixed as well as variable maintenance costs, and wind curtailment cost (29).…”

Section: Objective Functionmentioning

confidence: 99%

“…Authors in [24] suggest an adaptive robust optimization system flexibility model under a unit commitment time‐scale framework considering wind uncertainty. In [25], a long‐term stochastic co‐optimization planning model is presented to minimize total cost and maintain power system flexibility under RESs uncertainties. A flexibility evaluation method in distribution networks has been presented in [26] based on the feasibility analysis of uncertain regions of solar photovoltaic generations and demands.…”

Section: Introductionmentioning

confidence: 99%

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Harnessing power system flexibility under multiple uncertainties

Mazaheri

Saber

Fattaheian‐Dehkordi

et al. 2022

IET Generation Trans & Dist

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Increasing the intermittent outputs of renewable energy sources (RESs) has forced planners to define a new concept named flexibility. In this regard, some short‐ and long‐term solutions, such as transmission expansion planning (TEP) and energy storage systems (ESSs) have been suggested to improve the flexibility amount. A proper optimization procedure is required to choose an optimal solution to improve flexibility. Therefore, a mixed‐integer linear programming (MILP) direct‐optimization TEP versus ESSs co‐planning model is presented in this paper to enhance power system flexibility. In doing so, a novel RES‐BESS‐based grid‐scale system flexibility metric is proposed to investigate the improvement of flexibility amount via ESSs modules in the numerical structure. In this paper, a novel repetitive fast offline method has been proposed to quickly reach the desired amount of flexibility by defining an engineering price/benefit trade‐off to finally find the best investment plan. Also, multiple uncertainties associated with wind farms and demanded loads and a practical module‐type battery energy storage system (BESS) structure for each node are defined. The proposed model is applied to the modified IEEE 73‐bus test system including wind farms, where the numerical results prove the model efficiency as BESS impacts on flexibility, investment plans and power system economics.

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Section: Objective Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Harnessing power system flexibility under multiple uncertainties

Mazaheri

Saber

Fattaheian‐Dehkordi

et al. 2022

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…Still, it is essential to use various RSs available in a power system. Various power systems indices like operation, economic, reliability, and resiliency are introduced in different papers. But it is worth mentioning that the improvement of indices is separate and independent from their consideration [20, 21]. For instance, low‐cost sources are adopted to enhance the economic side [21], but they may not have good resiliency in power systems.…”

Section: Introductionmentioning

confidence: 99%

Co‐planning of generation and transmission expansion planning for network resiliency improvement against extreme weather conditions and uncertainty of resiliency sources

Seyyedi

Rashid

Akbari

et al. 2022

IET Generation Trans & Dist

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Generation and transmission expansion increase the flexibility of power systems and hence their ability to deal with contingency. This paper presents a resilient‐constrained generation and transmission expansion planning (RCGTEP) model considering the occurrence of earthquakes and floods. The proposed model minimizes the investment and operation costs of resiliency sources (RSs) and resiliency (blackout) costs arising from the outage of the network against the occurrence of extreme conditions. For further consideration, uncertainties of load and RSs availability are included as a Stochastic programming model. A hybrid solver of teaching‐learning‐based optimization (TLBO) and krill herd optimization (KHO) is used to solve the proposed problem and achieve the optimal solution, including a low standard deviation in the final optimal response. The model is tested using a modified version of the IEEE 6‐Bus and IEEE 89‐Bus transmission networks. Numerical results show the potential of the mentioned approach to improve indices of operation, economics, and resiliency in the transmission network.

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“…e model is subject to technical and economic constraints on uncertainty parameters. In an attempt to reduce the capital and operating cost, a stochastic co-optimization planning strategy is used [9], in which a linearized model-based AC power flow maintains the bus voltages, reactive power, and active power loss of the system. To compensate for reactive power, some equipment, including power generation sources, transmission lines, static var compensators (SVCs), and capacitor banks, was used in the same study.…”

Section: Introductionmentioning

confidence: 99%

Robust Allocation of FACTS Devices in Coordinated Transmission and Generation Expansion Planning considering Renewable Resources and Demand Response Programs

Rashid

Akbari

Khalafian

et al. 2022

International Transactions on Electrical Energy Systems

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Nowadays, the use of demand response programs (DRPs) in a variety of long-term and short-term planning problems has been explored. In this paper, a generation and transmission expansion planning (GTEP) model along with FACTS device allocation is presented. Furthermore, demand response programs are taken into account for more load flexibility. The proposed model is presented as a multi-objective minimizing problem considering emission, cost, and voltage security index. Furthermore, the conventional Pareto optimization is adopted using fuzzy weighted sum method (FWSM) to achieve a single-objective model. The final problem is constrained by equations of alternative current power flow, operation and voltage security limits, planning model of shunt FACTS devices, and operation of the DRP. Adaptive robust optimization (ARO) is used to reach suitable models for the active power of renewable resources and power consumption. As a main search algorithm, a hybrid combination of water cycle algorithm (WCA) and ant lion optimization (ALO) is proposed to find the optimum solution with a small standard deviation. The problem is tested on different standard IEEE systems, and the results validate the operation and network security improvement due to optimal location of FACTS devices. According to the results, the economic and environmental status of the network has also improved.

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Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties

Cited by 17 publications

References 36 publications

Harnessing power system flexibility under multiple uncertainties

Harnessing power system flexibility under multiple uncertainties

Co‐planning of generation and transmission expansion planning for network resiliency improvement against extreme weather conditions and uncertainty of resiliency sources

Robust Allocation of FACTS Devices in Coordinated Transmission and Generation Expansion Planning considering Renewable Resources and Demand Response Programs

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