A Wasserstein Distributionally Robust Planning Model for Renewable Sources and Energy Storage Systems Under Multiple Uncertainties

Li, Junkai; Xu, Zhao‐Dong; Liu, Hong; Wang, Chengshan; Wang, Liyong; Gu, Chenghong

doi:10.1109/tste.2022.3173078

Cited by 21 publications

(8 citation statements)

References 32 publications

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“…Furthermore, the importance of "flexibility" in the establishment of net-zero systems has been demonstrated [1]. Flexibility is the capability of a system in mitigating the intermittency and volatility of renewable energy generation (REG) [11], thus ensuring secure and low-carbon system operation [12]. BESSs facilitate energy temporal transfer, substantially enhancing the PV hosting capability in DSs [5], and providing flexibility for net-zero DS construction.…”

Section: Index Of Variables Inmentioning

confidence: 99%

“…Currently, two main types of distributionally robust ambiguity sets are adopted: moment-and statistical-distance-based sets [20]. However, using two moments (the first and second moments) can capture only part of the true distribution information, sometimes leading to over-conservative decisions [12], [21]. To construct statistical-distance-based sets, the Kullback-Leibler (KL) divergence or the Wasserstein metric can be applied.…”

Section: Index Of Variables Inmentioning

confidence: 99%

“…Constraint (11) limits the charging and discharging power of the BESS. Constraint (12) ensures that the residual energy of BESS meets the SOC constraints at every period throughout the day. Constraint (13) ensures that the initial residual energy of BESS for a day is equal to its ending residual energy, thereby ensuring the feasibility of BESS utilization in the following day.…”

Section: Operation Constraints Of Besssmentioning

confidence: 99%

“…1) For BESSs: (11). However, the bounds of ( 11) may be temporally coupled during different time periods, due to constraints (12) and (13). The treatment of this will be elaborated in Section V-B.…”

Section: A Obtaining Affine Relations For Pvics Using Basic Feasible ...mentioning

confidence: 99%

“…The seasonal characteristics of PV outputs are from [34]. The intraday carbon emission intensity profile is from [12], assuming that it does not change in different seasons.…”

Section: A 4-bus Systemmentioning

confidence: 99%

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An Analytical Method for Delineating Feasible Region for PV Integration Capacities in Net-zero Distribution Systems Considering Battery Energy Storage System Flexibility

Zhang,

Ge,

Liu

et al. 2024

Journal of Modern Power Systems and Clean Energy

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To provide guidance for photovoltaic (PV) system integration in net-zero distribution systems (DSs), this paper proposes an analytical method for delineating the feasible region for PV integration capacities (PVICs), where the impact of battery energy storage system (BESS) flexibility is considered. First, we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements, which form the upper and lower bounds of the feasible region. Then, the formulation and solution of the feasible region is proposed. The resulting analytical expression is a set of linear inequalities, illustrating that the feasible region is a polyhedron in a high-dimensional space. A procedure is designed to verify and adjust the feasible region, ensuring that it satisfies network loss constraints under alternating current (AC) power flow. Case studies on the 4-bus system, the IEEE 33-bus system, and the IEEE 123-bus system verify the effectiveness of the proposed method. It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs, loads, and BESSs, while also quantifying the impact of this relationship on the boundaries of the feasible region.

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Section: Index Of Variables Inmentioning

confidence: 99%

Section: Index Of Variables Inmentioning

confidence: 99%

Section: Operation Constraints Of Besssmentioning

confidence: 99%

Section: A Obtaining Affine Relations For Pvics Using Basic Feasible ...mentioning

confidence: 99%

“…The seasonal characteristics of PV outputs are from [34]. The intraday carbon emission intensity profile is from [12], assuming that it does not change in different seasons.…”

Section: A 4-bus Systemmentioning

confidence: 99%

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