Dr Kang Ma

Selected Journal Publications

According to IEEE and the IET copyright policies, only accepted versions of the papers are made available. Any citation should be made to the published version, which is accessible by clicking the DOI link.

"A Statistical Methodology to Identify Imbalance-Induced Capacity Waste for LV Networks"

Electric Power System Research, 2021. Link: DOI

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

CSEE Journal of Power and Energy Systems, 2020. Link: DOI Download full text

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

IEEE Transactions on Power Systems, 2020. Link: DOI Download full text

"A Statistical Approach to Guide Phase Swapping for Data-Scarce Low Voltage Networks"

IEEE Transactions on Power Systems, 2019. Link: DOI Download full text

"Assessment of Additional Phase Energy Losses Caused by Phase Imbalance for Data-Scarce LV Networks"

IET Generation, Transmission & Distribution, 2019. Link: DOI Download full text

"A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks"

IEEE Transactions on Power Systems, 2019. Link: DOI Download full text

"Three Phase Power Imbalance Decomposition into Systematic Imbalance and Random Imbalance"

IEEE Transactions on Power Systems, 2018. Link: DOI Download full text

"Utility-Scale Estimation of Additional Reinforcement Cost from 3-Phase Imbalance Considering Thermal Constraints"

IEEE Transactions on Power Systems, 2017. Link: DOI Download full text

"Quantification of Additional Reinforcement Cost from Severe 3-Phase Imbalance"

IEEE Transactions on Power Systems, 2017. Link: DOI Download full text

"Quantification of Additional Reinforcement Cost Driven by Voltage Constraint under Three-Phase Imbalance"

IEEE Transactions on Power Systems, 2016. Link: DOI Download full text

"Quantification of Additional Asset Reinforcement Cost from Three Phase Imbalance"

IEEE Transactions on Power Systems, 2015. Link: DOI Download full text

"Estimation of Voltage-Driven Reinforcement Cost for LV Feeders under 3-Phase Imbalance"

IEEE Access, 2016. Link: DOI Download full text

Research Area: Phase Imbalance in Electrical Distribution Networks

Phase imbalance is a widespread problem in the UK's three-phase four-wire and five-wire low voltage (LV, 415V) distribution networks. More than 70% of these networks suffer from moderate or severe degrees of phase imbalance. For instance, it is not uncommon to see that one phase has a peak current of 300 A and another phase only has 150 A. This problem is also prevalent in European LV distribution networks as well as the medium-voltage distribution networks in the US, China, and other countries in the world. This problem will be aggravated by the increase of photovoltaic generation, wind generation, and electric vehicles, if they are not properly controlled.

Causes

In practice, the major causes for phase imbalance are: (1) an uneven allocation of customers across the three phases (I will refer to the phases as a, b and c) and (2) random customer behavior.

Consequences

Phase imbalance has three main consequences:

1) Phase imbalance wastes network capacity. For instance, consider the common situation where phase a carries, say 72 kW with no spare capacity and the other two phases (b and c) carry 36 kW with 50% spare capacity. Customers on phase a cannot connect any additional appliances without overloading the system, yet the large margins on phases b and c cannot be transferred to phase a – they are effectively wasted by phase imbalance.

2) Energy losses are increased by more than 20% (equivalent to 4 ~ 5 TWh, or worth more than £4 bn by 2050 throughout the UK, compared to the ideal phase balanced case).

3) It causes “a current of imbalance”, also known as the zero-sequence current. An additional conductor, the neutral wire, is required to carry this neutral current. This incurs an additional investment cost compared to the ideal phase balanced case.

Challenges

In attempting to cure the problem, researchers are confronted by three main challenges: (i) too little data available in LV networks, which I refer to as blindness, (ii) scalability (millions of LV networks need to be phase balanced), and (iii) adaptability (the imbalance condition changes over time because of random customer behavior and the connections of electric vehicles).

Research tasks

My research involves understanding the characteristics and consequences of phase imbalance and developing data-efficient (requiring a minimal amount of data), scalable, adaptive solutions to rebalance the three phases.