Cost-Benefit Analysis of Phase Balancing Solution for Data-Scarce LV Networks by Cluster-Wise Gaussian Process Regression

Kong, Wangwei; Ma, Kang; Fang, Lurui; Wei, Renjie; Li, Furong

doi:10.1109/tpwrs.2020.2966601

Cited by 11 publications

(6 citation statements)

References 27 publications

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“…For example, an 11kV distribution network has near-overload cables and transformers and suffers from significant phase unbalance, in which case the unbalance-induced network investment cost should be considered. Previous cost-benefit analysis of phase balancing solutions focused on LV networks only [67], resulting in an underestimation of the phase balancing benefits and thus a conservative cost-benefit analysis. A cross-voltage-level analysis would reveal a more accurate cost of phase unbalance (also the potential benefit from phase rebalancing) than the analysis solely focusing on the LV level, thus enabling a more accurate cost-benefit analysis of phase rebalancing solutions.…”

Section: Costly and Not Scalable To Millions Of LV Networkmentioning

confidence: 99%

Review of Distribution Network Phase Unbalance: Scale, Causes, Consequences, Solutions, and Future Research Direction

Ma¹,

Fang²,

Kong³

2020

Preprint

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Phase unbalance is widespread in the distribution networks in the UK, continental Europe, US, China, and other countries. First, this paper reviews the mass scale of phase unbalance and its causes and consequences. Three challenges arise from phase rebalancing: the scalability, data scarcity, and adaptability (towards changing unbalance over time) challenges. Solutions to address the challenges are: 1) using retrofit-able, maintenance-free, automatic solutions to overcome the scalability challenge; 2) using data analytics to overcome the data-scarcity challenge; and 3) using phase balancers or other online phase rebalancing solutions to overcome the adaptability challenge. This paper categorizes existing phase rebalancing solutions into three classes: 1) load/lateral re-phasing; 2) using phase balancers; 3) controlling energy storage, electric vehicles, distributed generation, and micro-grids for phase rebalancing. Their advantages and limitations are analyzed and ways to overcome the limitations are recommended. Finally, this paper suggests future research topics: 1) long-term forecast of phase unbalance; 2) whole-system analysis of the unbalance-induced costs; 3) phase unbalance diagnosis for data-scarce LV networks; 4) technocommercial solutions to exploit the flexibility from large threephase customers for phase balancing; 5) the optimal placement of phase balancers; 6) the transition from single-phase customers to three-phase customers.

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Section: Costly and Not Scalable To Millions Of LV Networkmentioning

confidence: 99%

Review of Distribution Network Phase Unbalance: Scale, Causes, Consequences, Solutions, and Future Research Direction

Ma¹,

Fang²,

Kong³

2020

Preprint

Self Cite

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show abstract

“…Reference [23] presented a way to estimate the additional reinforcement cost (ARC) for both LV transformers and main feeders using the degree of power imbalance. Our previous work [24] proposed a method to estimate the ARC and the additional energy loss cost (AELC) for data-scarce LV networks. The AELC includes the transformer copper loss cost and the costs caused by the phase residual current [24].…”

Section: Introductionmentioning

confidence: 99%

“…Our previous work [24] proposed a method to estimate the ARC and the additional energy loss cost (AELC) for data-scarce LV networks. The AELC includes the transformer copper loss cost and the costs caused by the phase residual current [24]. Nonetheless, these research works only focus on the LV networks with traditional passive loads, rather considering the increasing penetrations of LCTs.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic impact assessment of phase power imbalance in the LV networks with increasing penetrations of low carbon technologies

Kong

2022

Electric Power Systems Research

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“…The first two of these methodologies imply higher investment costs, as they require the acquisition of new equipment (i.e., capacitors, static compensators, and distributed generators), including the associated installation and maintenance costs [13]. On the other hand, the phase-balancing approach can be considered the most inexpensive method to reduce power losses because this method obviates the necessity for new devices [4], and the unique cost related to the phase-balancing plan is associated with working groups entrusted with traveling around to implement the required changes in the phases of the nodes of the grid [14]. In this study we solve the phase-balancing problem in an attempt to reduce the annual operating cost of three-phase distribution networks with asymmetric loads.…”

Section: Introductionmentioning

confidence: 99%

Operating Cost Reduction in Distribution Networks Based on the Optimal Phase-Swapping including the Costs of the Working Groups and Energy Losses

2021

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The problem of optimal phase-balancing in three-phase asymmetric distribution networks is addressed in this research from the point of view of combinatorial optimization using a master–slave optimization approach. The master stage employs an improved sine cosine algorithm (ISCA), which is entrusted with determining the load reconfiguration at each node. The slave stage evaluates the energy losses for each set of load connections provided by the master stage by implementing the triangular-based power flow method. The mathematical model that was solved using the ISCA is designed to minimize the annual operating costs of the three-phase network. These costs include the annual costs of the energy losses, considering daily active and reactive power curves, as well as the costs of the working groups tasked with the implementation of the phase-balancing plan at each node. The peak load scenario was evaluated for a 15-bus test system to demonstrate the effectiveness of the proposed ISCA in reducing the power loss (18.66%) compared with optimization methods such as genetic algorithm (18.64%), the classical sine cosine algorithm (18.42%), black-hole optimizer (18.38%), and vortex search algorithm (18.59%). The IEEE 37-bus system was employed to determine the annual total costs of the network before and after implementing the phase-balancing plan provided by the proposed ISCA. The annual operative costs were reduced by about 13% with respect to the benchmark case, with investments between USD 2100 and USD 2200 in phase-balancing activities developed by the working groups. In addition, the positive effects of implementing the phase-balancing plan were evidenced in the voltage performance of the IEEE 37-bus system by improving the voltage regulation with a maximum of 4% in the whole network from an initial regulation of 6.30%. All numerical validations were performed in the MATLAB programming environment.

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Cost-Benefit Analysis of Phase Balancing Solution for Data-Scarce LV Networks by Cluster-Wise Gaussian Process Regression

Cited by 11 publications

References 27 publications

Review of Distribution Network Phase Unbalance: Scale, Causes, Consequences, Solutions, and Future Research Direction

Review of Distribution Network Phase Unbalance: Scale, Causes, Consequences, Solutions, and Future Research Direction

Probabilistic impact assessment of phase power imbalance in the LV networks with increasing penetrations of low carbon technologies

Operating Cost Reduction in Distribution Networks Based on the Optimal Phase-Swapping including the Costs of the Working Groups and Energy Losses

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