Assessment of flexible interconnection strategies for the integration of electric vehicles and renewable energy in load-centric distribution networks

0 Introduction

0.1 Research background

The distribution network (DN) is a crucial infrastructure for electric power distribution and delivery, which plays an essential role in the urban electricity-energyphysical network.As net-zero carbon initiatives progress and power systems evolve,the DN becomes vital for maintaining the security and stability of system operations,enhancing system resilience, and facilitating capacity expansion[1,2].The increasing integration of electric vehicles (EVs) and distributed generators (DGs) from renewable energy sources (RESs) in load-centric environments is pivotal for sustainable urban development.However,this rising demand necessitates decentralized interconnection structures, which pose significant challenges to the advancement of modern urban distribution systems[3].

Conventional flexible interconnection devices (FIDs),which primarily utilize mechanical switches, are fraught with operational risks due to their slow response times and limited capacity for continuous regulation amidst fluctuating renewable power generation.In contrast, FIDs dominated by power electronic devices, specifically those comprising voltage source converters (VSCs), offer enhanced power system flexibility.These devices allow for dynamic power flow adjustments and an increase in system capacity[3].VSC-based FIDs serve as replacement for mechanical switches and addresses the limitations of slow response and related safety concerns.According to[5], VSC-based FIDs are differentiated into back-to-back(B-T-B)and multiport configurations based on the number of VSCs used for feeder connections.Notably,B-T-B twoport FIDs are especially well-suited for simple and radially distributed feeder configurations, as depicted in Fig.1.

Multi-port FIDs provide significantly greater potential compared to B-T-B two-port FIDs for accommodating complex distribution network and feeder arrangements.These include multi-feeder interconnections, loop-to-loop interconnections, and dual-mode ‘‘master and backup”management systems, which are expected to become prevalent in future urban distribution networks [3,4].From an engineering and power systems perspective, configurations involving four-feeder interconnections demonstrate high scalability and are well-suited to reliably meet the demands of more complex operational scenarios, such as dual-circuit feeders and 4-1 ‘‘master-standby” modes[6,7].This configuration holds considerable research value and potential for replication, and is thus a primary focus of this study, especially in new power systems and loadcentered environments.

0.2 Problem proposing

Conducting quantitative research and evaluations using advanced techniques is crucial for a comprehensive assessment of improvements and for effectively analyzing the performance and practical application value of flexible interconnection distribution networks.

Fig.1.Back-to-back two-port FID-based interconnection.

In [7], a methodology was introduced to evaluate the power-supply capacity and reliability of active distribution networks that incorporate FIDs.Similarly, [8] developed an evaluation framework for the carrying capacity of distribution networks integrated with reactive power compensation equipment and distributed generators,considering metrics such as high power quality, economic efficiency, and flexibility.Reference [9] proposed a probabilistic framework based on an accurate hosting capacity(HC) model to assess the ability of a distribution network to support various renewable sources.This approach highlighted the HC limitations and operational risks associated with integrating distributed generators into distribution networks.Despite considerable efforts to evaluate various power system configurations, most metrics and indicators focus on single dimensions such as system efficiency, load transfer capability, and security, leading to fragmented assessments.Additionally,for FID-based distribution networks, existing research predominantly evaluates single characteristics like load transfer capability, sustainability,or carrying capacity.Comprehensive evaluations comparing flexible interconnection options for multi-feeders in urban areas remain limited.

Regarding evaluation methodologies, current research predominantly focuses on applying weights to various indicators to derive conclusions.Common techniques include the fuzzy comprehensive evaluation(FCE)[10],the analytic hierarchy process (AHP), the entropy weighting method[11], and the technique for order preference by similarity to an ideal solution [12].Reference [13] introduced a novel comprehensive evaluation method for assessing power system development levels through indicator-level grading.In[14], an advanced hierarchical attribute model and conflict correlation method were proposed to balance subjective and objective weighting assignments.Additionally,the work described in[15]developed a multilevel comprehensive evaluation index system for modern distribution networks, utilizing the AHP and FCE methods for practical implications, which proved to be particularly inspiring.While these studies have introduced various evaluation frameworks, none have specifically addressed flexible interconnections within new urban distribution networks.Furthermore, these approaches have not adequately tackled the challenges posed by the dynamic characteristics of contemporary power systems.

The evolving environmental scenarios in urban power distribution systems differ significantly from conventional setups, characterized by complex, diverse, flexible, and fluctuating power resources and loads.New evaluation systems designed for flexible interconnected distribution networks should be more inclusive, covering a broader spectrum of evaluation factors, especially in loadcentered urban contexts.This necessitates the integration of existing evaluation frameworks with the unique demands of flexible interconnected distribution networks.Moreover, a more thorough analysis of crucial evaluation metrics is essential, taking into account the distinctive characteristics of specific application scenarios.

0.3 Research work and main contribution

This study introduces a multidimensional evaluation framework designed to meet the evolving needs of urban distribution networks in load-centered cities.It further explores flexible interconnection configurations designed to optimize the efficiency and adaptability of power distribution networks.We propose a comprehensive evaluation system and its corresponding model, which encompasses metrics of system efficiency, economic considerations,sustainability, power supply reliability, and the specific demands of urban flexible interconnection scenarios.Utilizing the AHP and FCE methods, we developed an evaluation tool that has been applied to assess four distinct flexible distribution network interconnection configurations.The contributions are outlined as follows:

We present four unique flexible interconnected configurations for distribution feeders:a conventional configuration using mechanical switches, a power-electronicsdriven B-T-B FID-based configuration, a three-port FID-based honeycomb configuration, and a four-port FID-based configuration.Each configuration is analyzed to highlight its distinctive features.

A comprehensive evaluation framework has been developed, incorporating five key metrics: system efficiency,economic feasibility, environmental sustainability,power supply reliability, and the specialized requirements of urban flexible interconnection application scenarios.

An evaluation tool, combining the AHP and FCE methods, was created and employed to analyze various flexible interconnection configurations,identifying their specific advantages and most suitable scenarios.

The structure of this article is organized as follows:Section 1 describes the four targeted flexible interconnected distribution networks and their respective characteristics.Section 2 details the comprehensive evaluation framework,model, and methodology.Section 3 gives the calculations,accompanied by an analysis and discussion.Section 5 concludes with a summary of our findings.

1 Configurations and characteristics of flexible distribution network interconnections

The integration of a substantial number of EVs, DGs,operational response functions, and other elements into new urban distribution networks significantly increases the complexity and variability of operations, necessitating a more adaptable power system architecture [3].In this context, flexible interconnections are essential in new urban distribution networks, especially in load-centered cities that need to expand their power system capacity while managing spatial constraints.Therefore,four configurations based on different FIDs are proposed for analysis,as depicted in Fig.2.

1.1 Common flexible interconnection configuration

The conventional configuration employs mechanical constructs to establish an interconnected network and enables power flow adjustments across multiple feeders.As shown in Fig.2(a), this setup supports step regulation for up to four feeders (F1-F4) through a combination of mechanical ties and sectionalizing switches.However, this configuration exhibits significant limitations.Continuous regulation is significantly constrained by the operational frequency of these mechanical switches and the number of interconnections, leading to constrained regulation capabilities and potential reliability risks.Consequently, this setup operates under a ‘‘closed-loop design, open-loop operation”mode.

Fig.2.Diagram of typical flexible interconnected distribution networks.

1.2 B-T-B two-port FID-based flexible interconnection

To address the restricted regulation range inherent in closed-loop interconnections among different regional feeders, FIDs are connected at the ends of feeders in separate single-loop networks to form a flexible structure [16].By substituting some mechanical switches with power-electronic devices, as illustrated in Fig.2(b), a feeder-to-feeder flexible interconnection configuration is reconstructed to enable ‘‘closed-loop” operation [17].This approach significantly extends the regulation range of the FIDs,addressing the constraints of fixed-step regulation.However, as the requirements for broader distribution network regulation increase,the number of VSCs within the FID may need to be substantially increased, leading to higher investment costs and potentially reducing the overall efficiency of the system.

1.3 Three-port FID-based honeycomb interconnection

Reference [18]advances the concept of a meshed distribution network utilizing a honeycomb interconnection structure to enhance ‘‘closed-loop” operation, based on the work reported in [5].The configuration depicted in Fig.2(c) connects four distribution feeders via three-port FIDs as central components, enabling flexible regulation of power flow.This setup addresses the limitations of conventional closed-loop interconnections by offering a comprehensive time-series power flow regulation across the entire power system, which was previously unachievable due to limited regulation range.It ensures precise and rapid response capabilities within the interconnected feeder and distribution network, thus enhancing adaptability to variable energy resources.

1.4 Four-port FID-based interconnection

In contrast to the honeycomb configuration depicted in Fig.2(c), the structure shown in Fig.2(d) employs four VSCs within the FID to facilitate a flexible interconnection of the four distribution feeders.This arrangement reduces the number of VSCs and simplifies the system architecture compared to the honeycomb setup, while the FIDs continue to function as their original open switches.This configuration allows for flexible management of power among multiple feeders and provides reactive power and voltage support at the feeder terminals,thereby improving voltage stability [19].

2 Comprehensive evaluation framework and process for flexible distribution network interconnections in loadcentered environments

2.1 Comprehensive evaluation framework

The evaluation framework established in this study provides a structured approach for selecting and developing appropriate indicators and models.Reflecting the unique characteristics of flexible interconnections in new distribution networks and the increasing demand for high-quality power supply and net-zero carbon emissions,this research introduces a comprehensive evaluation system spanning five dimensions: system efficiency, economic factors, sustainability, power supply reliability, and the specific requirements of load-centered application scenarios.This framework is detailed in Fig.3, with the indicators elaborated in the subsequent subsections.

2.1.1 System efficiency

System efficiency (η) primarily quantifies the energy losses during power conversion and delivery, represented by the formula:

where Pout denotes the total output power, Pin represents the total input power,and t is the operating time.A higher efficiency coefficient indicates reduced power losses,denoting a more efficient power system.

System efficiency is intricately linked to the overall losses within the interconnected distribution network.The annual power consumption can be calculated by taking into account the electric load demand, providing insights into the system’s efficiency and operational performance over time.As formulated in (2), this calculation facilitates a comprehensive evaluation of the system effi-ciency of an interconnected distribution network in meeting its power delivery requirements:

where PL is the rated power of the electric load demand,k is the electric load rate, and tL represents the operating time in hours per year for the electric loads.

2.1.2 Economy

(1) Initial investment

The investment primarily covers the costs associated with VSC equipment and distribution infrastructure,which typically includes transformers, distribution cabinets,switchgears,and feeder cabinets for a 10 kV distribution network.Additional investments might involve renewable energy systems and energy storage systems (if applicable), along with auxiliary expenses such as cables and project management costs.It is important to note that costs related to civil work, air-conditioning systems, IT equipment, and other ancillary equipment are excluded for simplicity.

Fig.3.Structure of the comprehensive evaluation.

(2) Operating cost

The operating costs predominantly comprise the depreciation of fixed assets, electricity consumption, labor, and maintenance expenses(excluding taxes and other charges).In calculating annual cash outflows using the net present value (NPV) method, depreciation of fixed assets is not considered; only the costs of electricity consumption,labor,and maintenance are included.Electricity consumption costs pertain to the expenses incurred from electricity use and power losses within the distribution network,while labor and maintenance costs are estimated to be 8 percent of the initial investment.

(3) Annual revenue

Annual revenue primarily stems from interactions with various distribution feeders, differentiated peak and off-peak tariffs, and benefits generated through demand response mechanisms.Utilizing the NPV for a comprehensive economic cost-benefit assessment, the economic viability of the proposed scheme was evaluated based on the magnitude of the NPV.This approach provides a more accurate depiction of the economic value of the scheme by accounting for the time value of costs.

2.1.3 Sustainability

Environmental sustainability was determined by evaluating the reductions in carbon emissions.In this study,the emission coefficient was employed to quantify the carbon emissions from the flexible interconnection network.Carbon reduction is achieved primarily through two approaches: energy savings from enhanced power source efficiency, and the utilization of clean, renewable power sources alongside EV discharges.

Using the average efficiency (η0) as the reference value,the annual carbon emission value is calculated as:

The annual carbon emission value under the actual effi-ciency (η1) is determined using the following formula:

The formula for determining the annual reduction in carbon emissions is given by:

where μ is the baseline carbon emission coefficient of the regional power grid, published annually by the National Energy Administration and varies by region.Ps represents the power sourced from renewable energy and EV discharges, measured in kW.ts denotes the annual operating time of the power source, measured in h.

2.1.4 Power supply reliability

(1) Voltage profile index (VPI)

While the FID connected at the end of the distribution feeder enhances system stability and improves the voltage level within the distribution network[19],the VPI serves as a metric to quantify the deviation of feeder voltage from its designated reference value.The VPI is calculated using the following formula:

where Vi is the actual voltage on feeder i,Vi0 is the reference voltage value,and n is the total number of interconnected feeders.

(2) Power flow transfer capability

The power flow transfer function of the FID is crucial in balancing power flows and reducing feeder overload conditions.In the event of feeder failure, real-time power regulation through the FID enables the redistribution of power loads or generation to other feeders within the broader distribution network.

To evaluate the impact of the power flow transfer capability of interconnected distribution networks, this study employs the flow transfer entropy metric, as defined in[20], to quantitatively characterize the effectiveness of power flow transfer.The relevant formula can be written as:

where Pji0 denotes the initial active power flow of feeder j,and Pji represents the active power flow of feeder j following the disconnection of feeder i owing to faults.Δεji quantifies the active power flow redirected to feeder j as a consequence of the fault in feeder i, while γji corresponds to the power flow transfer rate.Yzi signifies the entropy associated with the power flow transfer of feeder i.Higher values of Yzi represent a greater potential impact on the system, resulting from the power flow redistribution triggered by feeder i’s failure.Yt is defined as the powerflow transfer entropy threshold, which represents the capacity of the system to endure the power-flow transfer.

(3) Short-circuit current

The short-circuit current is a crucial parameter for evaluating the security and stability of a power system.It assists in determining whether the short-circuit current of each feeder exceeds the permissible threshold,ensuring optimal network reconfiguration.An FID within an interconnected distribution network offers current-limiting capabilities,thus reducing short-circuit current levels.The mathematical expression for short-circuit current is given by:

where Iscc denotes the short-circuit current of feeder i and Iscc_b represents the short-circuit current breaking capacity of the circuit breaker.

2.1.5 Scenario-specific requirements

(1) Hosting capacity

The hosting capacity is defined as the maximum level of DG and EV that can be integrated into the distribution network without surpassing operational constraints such as voltage, thermal limits, and stability.In interconnected distribution networks within load-centered cities, the HC for DG and EV can be significantly enhanced by using FIDs, which offer robust control functions.FIDs effectively coordinate the power flow across each feeder and provide reactive power compensation, thereby reducing voltage fluctuations and ensuring the integration of DG and EV.The formula used to calculate the HC is as follows:

(2) EV/renewable accommodation

Alongside the HC metric, the penetration level (PL) of DG and EV serves as a quantitative measure for assessing the interconnected distribution network.In load-centered cities utilizing FIDs, the PL is defined as:

where Pmax-load represents the maximum loading value of the interconnected distribution network.

2.2 Comprehensive evaluation process

2.2.1 Analytic hierarchy process

The AHP is a multi- objective decision-making method that effectively integrates both qualitative and quantitative factors to evaluate a limited set of alternatives [21].It is particularly suited to complex decision-making challenges involving multiple diverse factors where precise quantification is challenging, as demonstrated in this study.

The AHP decomposes the evaluation problem into multiple levels and factors, conducts pairwise comparisons to establish their relative importance,and calculates the overall weight of each solution by systematically analyzing the factors from the most basic to the most complex level.The solution with the highest weight is considered optimal.The process of determining the weight coefficients for various factors using AHP involves four key steps.

a) Establishment of Hierarchical Model: The initial step involves defining the decision-making objective and identifying the factors that influence this objective.This process leads to the creation of a hierarchical structural model comprising three primary levels:the objective, criteria, and indicator layers.

b) Construction of Pairwise Judgment Matrix: At each level of the hierarchy, elements undergo pairwise comparisons, resulting in the construction of a judgment matrix.The importance weight Wi of each element is represented within a matrix C, where each factor is compared against another in terms of relative importance, is known as the judgment matrix and is expressed as:

Relative scales Wi/Wj were employed to measure the relative importance of the two factors, typically using a scale ranging from 1 to 9,as detailed in Table 1.This scale effectively quantifies the comparative significance of each factor, where the values of Cij and Cji exhibit an inverse relationship, that is, Cij = 1/Cji.

c) Calculation of weight coefficients: The maximum eigenvalue λmax of the judgment matrix is calculated,along with its corresponding eigenvector.These eigenvectors were then normalized to define the weight coefficients of the lower-level elements relative to the upper level.

d) Consistency check: To ensure the reliability of the conclusions derived from the AHP, it is necessary to compute the Consistency Index (CI) and Consistency Ratio (CR) for the judgment matrix.The CI is calculated as:

where n is the order of the judgment matrix C.The random consistency index (RI) can be referenced from [22].When n of judgment matrix C exceeds 2, the CR is calculated as the ratio of CI to RI.A CR value less than 0.1 indicates acceptable consistency; otherwise, the matrix may require adjustments.

2.2.2 Fuzzy comprehensive evaluation

The FCE method, based on the theory of ‘affiliation degree’ and ‘affiliation function’ from fuzzy mathematics[23], is a quantitative approach for analysis and assessment.The evaluation process flowchart (depicted in Fig.4) consists of seven main steps.

Table 1 Scaling methods used in the analytic hierarchy process (AHP).

ScaleDefinition 1 Two factors are equally important 3 One factor is slightly more important than the other 5 One factor is significantly more important than the other 7 One factor is strongly more important than the other 9 One factor is extremely more important than the other 2, 4, 6, 8Intermediate values between two adjacent judgments

a) Subject Identification of the Evaluation System: In this study,four distinct configurations of feeder flexible interconnected distribution networks,as detailed in Section 2,were chosen as the primary subjects for evaluation.

b) Determination of Comprehensive Evaluation Metrics:The evaluation metrics selected include system effi-ciency, power supply reliability, economic viability,sustainability, and scenario-specific requirements pertinent to load-centered cities.

c) Determination of the Weights of the Evaluation Indicators: In environments centered around load management, indicators such as power supply reliability and the accommodation of EVs and RESs are considered critical; hence, appropriate weights are assigned to these indicators.

d) Weight Calculation: Using the AHP method, as outlined in Subsection 3.2.1, comparisons were made between rows and columns to establish the relative importance of each factor.A scale from 1 to 9,ranging from’slightly important’to’very important,’was used to denote levels of importance, with less significant indicators receiving inverse values.This approach enabled the generation of an evaluation matrix.The eigenvectors derived from this matrix were then transposed to produce a weight matrix W for each evaluation indicator.

e) Single-Factor Fuzzy Evaluation: Define This step involves defining the value ranges for each evaluation level associated with each indicator.The actual values of each evaluation index are calculated and compared against these ranges, simulating expert assessments.If the actual value falls within a specified range, an affiliation degree of 1 is assigned to that evaluation level, while other levels receive an affiliation degree of 0.These degrees for each index collectively form the comprehensive evaluation matrix R.

f) Establishment of the Evaluation Model: With the weight matrix W from step (d) and the evaluation matrix R from step(e),the comprehensive evaluation model can be constructed.This is achieved by selecting an appropriate weighted synthesis operator:

where b1,b2,b3,b4,b5 represent the degrees of affiliation of the evaluation results with the evaluation levels {worst,poor, general, better, and good}, respectively.Normalize vector B to align with the 5-point evaluation scale, and compute the weighted product summation to derive the comprehensive evaluation value, which ranges from 1 to 5.A higher value indicates a more favorable overall evaluation of the system.

Fig.4.Fuzzy comprehensive evaluation workflow.

g) Evaluation Result Output and Analysis: The final evaluation results are computed and output for further analysis based on comprehensive evaluation model E derived in step (g).

3 Result and discussion

3.1 Model setting

Along with Fig.2,this subsection compares the performances of the four-feeder flexible interconnected configurations illustrated in Fig.5.Feeders F2 and F4 serve urban areas with requirements for EV integration,whereas feeders F1 and F3 are situated in regions prioritizing renewable energy generation.The key parameters for these configurations are detailed in Table 2, incorporating data from[24]and a real-world interconnected distribution network project in Guangdong Dongguan, China [25].This comparison reveals the strengths and weaknesses of each configuration, providing a solid foundation for selecting the most suitable option for various scenarios.

3.2 Result and analysis

The indicators for each flexible interconnection configuration were calculated using the developed comprehensive evaluation tool.This analysis yields final results that distinctly highlight the strengths and weaknesses of the configurations across the five key dimensions, along with their respective evaluation scores.The specific values for each indicator are detailed in Table 3, and the judgment matrix C, derived using the AHP, is presented in Table 4.

Fig.5.Comparison of four flexible interconnected configurations.

The weight matrices for the five relevant dimensions are represented as W = [0.11988, 0.06794, 0.06974, 0.53868,0.20555].This matrix was validated through a consistency check, yielding a CR of 0.08.The weight matrix indicates that power supply reliability is assigned the highest weight,accounting for 53.9 % of the total, highlighting its critical importance in the functionality of the distribution network.System efficiency and scenario-specific requirements follow, with respective weights of 12 % and 20.5 %, highlighting their significance in the evolution of new power systems.In terms of sustainability, Configurations 3 and 4 achieve the highest carbon reduction, at 55.4 %.Configuration 2 results in a carbon reduction of 45.0 %, while Configuration 1 achieves the lowest, at 36.0 %, primarily due to its lesser utilization of clean power sources.The overall evaluation scores for each configuration, as presented in Table 5 and Fig.6, provide a clear depiction of the metrics and offer a comprehensive comparison across the various criteria.

According to the data in Tables 2 and 4, the capacities for renewable and EV accommodation in power electronic FID-based flexible interconnected distribution networks are significantly enhanced, each achieving a perfect score of five points.This enhancement not only effectively addresses the limitations associated with power flow transfer in conventional radial distribution networks but also enables voltage regulation through the integration of FIDs, thereby improving consumption efficiency.Compared with VSC-based solutions, where the investment for a typical 10 kV distribution network with an 8 MVA capacity is approximately 5,000,000 CNY, the investment and operational maintenance costs for mechanical switches are considerably lower, leading to a higher economic score.Flexible configurations that rely less on the VSC achieve greater economic benefits (scoring 5 and 4 points for Configurations 1 and 2, respectively), but at the cost of reduced supply reliability (scoring 2 and 3 points for Configurations 1 and 2,respectively),consistent with established reasoning.

From the analysis presented,it is evident that(1)power electronic FID-based interconnection configurations(with overall scores of 3.14,3.18,and 4.21,respectively)offer significant advantages over mechanical switch-based configurations across several critical dimensions: systemefficiency, environmental sustainability,power supply reliability, and requirements of load-centered environmental scenarios.The integration of FIDs significantly enhances system efficiency, leading to reduced power losses.Furthermore,improvements in sustainability and environmental performance are achieved not only through decreased power generation consumption and carbon emissions due to enhanced system efficiency but also through the more effective utilization of renewable energy and the discharge energy from electric vehicles.(2) A quantitative analysis reveals that,despite their advantages,interconnection configurations utilizing VSC-FID underperform economically.This shortfall is attributable to the higher initial investments and operational costs associated with DCtype equipment, such as VSCs and DC circuit breakers(though circuit breakers were not considered in this study),which are considerably more expensive than their AC-type counterparts.However,as the technology matures,there is significant potential for reducing costs.Power electronically driven interconnection configurations yield substantial savings in electricity costs due to improved efficiency,reduced operational losses, and optimal power flow regulation.Moreover, integrating the DC-side system with an energy storage system provides considerable benefits, particularly by utilizing regional peak-valley electricity price differentials and demand-side response subsidies.

Table 2 Main parameters.

ItemValue Distribution feeder line(0.22 + j0.3662)*3 Ohm Rated voltage10 kV Active power capacity of power source6 MW Power capacity of VSC8 MW Converter operating efficiency99.70 %Annual operating hours4000 h Single station equipment investment500,000 CNY Single distribution line investment200,000 CNY Single converter investment5,000,000 CNY Electricity cost0.3 CNY/kWh Electricity revenue0.2 CNY/kWh Baseline carbon emission factor for the regional power grid0.839 kg/kWh

Table 3 Actual values used in evaluations.

ItemConfiguration 1Configuration 2Configuration 3Configuration 4 System efficiency η 98.84 %98.85 %98.89 %98.88 %ΔW607917.1369 kWh603335.1946 kWh583806.4104 kWh587679.3635 kWh Economy (ten thousand and ten thousand/year)Investment640162036402660 Operation and maintenance cost (equipment overhaul cost)18.2375141118.1000558417.5141923117.63038091 Operation and maintenance cost51.2129.6291.2212.8 Electricity Sales Revenue1040104010401040 Annual earning23624.0621520687.498614642.1451917579.24048 Sustainability C052358.7528952354.1952334.7563652338.61097 C133509.6018528794.8123349.3528423351.07259 ΔC18849.1510423559.3866928985.4035228987.53838 Power supply reliability VPI1.106 kV0.971 kV1.27 kV0.889 kV Yt0.6829081050.6931471811.0986122891.098612289 Yscc54.99 %54.99 %69.65 %69.65 %Scenario-specific requirements HC4.68 MW5.85 MW7.2 MW7.2 MW PV/EV PL13.26 MW16.575 MW20.4 MW20.4 MW

Table 4 Judgment matrix for comprehensive evaluation.

DimensionSystem efficiencyEconomySustainabilityPower supply reliabilityScenario specific requirements System efficiency1220.20.5 Economy0.5110.1428570.333333 Sustainability0.5110.1428570.333333 Power supply reliability57713 Scenario specific requirements2330.3333331

Table 5 Calculation results and comparisons from the comprehensive evaluation.

DimensionConfiguration 1Configuration 2Configuration 3Configuration 4 System efficiency2354 Economy5423 Sustainability2455 Power supply reliability2324 Scenario specific requirements2355 Overall evaluation score2.2038323.1358883.18011314.2055508

Fig.6.Radar chart illustrating the comprehensive evaluation results.

3.3 Application scenario classification

Four distribution network flexible interconnection configurations are discussed and analyzed in Subsection 4.2,with a comparative analysis presented in Table 6.Each configuration is designed for distinct application scenarios,with specific analyses detailed in this subsection.

(1) Common flexible configuration with mechanical switches: While this configuration is more economically viable due to lower initial investment and maintenance costs, it encounters significant limitations in flexibility and responsiveness.These limitations can lead to issues such as overvoltage and degraded power quality, which may compromise system reliability.The stepwise regulation is constrained by the operational limitations of mechanical switches,making it less effective in environments with high levels of renewable energy integration or electric vehicle adoption.Therefore, this configuration is primarily recommended for networks experiencing minimal fluctuations in power sources.

(2) B-T-B two-port FID-based configuration:This setup offers a balance between flexibility and cost, providing effective regulation for feeder networks with moderate levels of renewable power or electric vehicle penetration.However, the limited adjustment range, geographical constraints, and scalability issues can diminish its effectiveness in more complex urban power distribution systems.Consequently,this configuration is best suited for scenarios that require only moderate flexibility.

(3) Three-port FID-based honeycomb configuration:This configuration significantly enhances system effi-ciency and power supply reliability due to its multiple interconnected FID-based designs.However,the high implementation costs associated with the use of multiple VSCs present financial challenges.The honeycomb configuration is particularly wellsuited for scenarios demanding very high reliability and efficiency, assuming budgetary constraints allow for substantial investment.

(4) Four-port FID-based configuration: This scheme provides excellent flexibility and is capable of managing complex power flows, making it suitable for applications involving high levels of renewable sources and electric vehicles.Its superior performance in terms of system efficiency, reliability, and adaptability makes it ideal for meeting the dynamic demands of modern urban power systems, particularly in high-load urban environments.Despite its relatively high cost, the configuration’s advantages in system efficiency, reliability, and adaptability render it an excellent choice for new urban distribution systems, earning a strong overall evaluation score.It offers comprehensive flexibility for load-centered environments, accommodating both DG-equipped suburban areas and areas with high electricity and EV demands.This option is actively being promoted.

4 Conclusion

This study conducted a comprehensive evaluation of four distribution network interconnection configurations,encompassing both mechanical switches and advanced power electronics-driven, VSC-based FIDs.The performance of each configuration was meticulously evaluated across multiple dimensions to reveal their advantages and identify specific application scenarios.Mechanical switching-driven configurations, while economically advantageous,lack flexibility and are therefore best suited for power systems with limited fluctuations in sources orloads.Conversely, the B-T-B two-port VSC FID-based configurations strike a cost-effective balance between flexibility and reliability,making them ideal for medium-sized power systems or applications with moderate penetration of renewable sources and EVs.The three-port VSC FIDbased honeycomb configuration is customized for highpower-demand scenarios, significantly enhancing both power reliability and system efficiency, thereby necessitating substantial investment.The four-port VSC FID-based configuration, with its exceptional flexibility and power flow management capabilities,is established as the optimal choice for contemporary load-centric environments with high integration of renewable sources and EVs,and is thus highly recommended.In this study, four distinct configurations were evaluated, taking into consideration current converter technology and characteristics of power distribution systems.

Table 6 Comparative analysis of the four configurations.

DimensionConfiguration 1Configuration 2Configuration 3Configuration 4 System efficiencyPoorLowHighMedium EconomyHighMediumPoorLow SustainabilityPoorMediumHighHigh Power supply reliabilityPoorLowPoorMedium DG/EV accommodation and hosting capacity PoorLowHighHigh

With the advent of emerging technologies such as new power-switching devices, high-voltage, high-current reverse-blocking IGCTs (RB-IGCTs), and wide-bandgap(WBG) devices, AC-DC and DC-DC power converters are becoming increasingly diversified.Multiport converter devices are anticipated to reduce costs,expand the number of interconnected ports, and minimize power conversion losses.For interconnected distribution networks utilizing these new technologies, the proposed comprehensive evaluation process remains applicable; however, it requires adaptation to accommodate new parameters.

This study provides valuable insights that guide realworld decision-making and future implementations,aiding in the selection of the most suitable configuration for loadcentric environments.These findings demonstrate the potential of advanced power electronic FID-based configurations to enhance the resilience and adaptability of modern power systems.

Permission to reproduce materials from other sources

None.

CRediT authorship contribution statement

Guowei Liu: Writing - original draft, Investigation,Formal analysis, Data curation.Liming Wang: Supervision, Project administration.Kangsheng Cui: Validation,Formal analysis,Data curation.Peiqian Guo:Supervision,Resources,Methodology,Investigation.Hao Dai: Writing- review & editing, Funding acquisition.Min Guo: Software, Project administration, Investigation.Lisheng Xin:Writing - review & editing, Funding acquisition.

Funding information

Science and Technology Project of China Southern Power Grid Co.Ltd.(SZKJXM20230085).

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Guowei LIU, Hao Dai, Lisheng Xin are currently employed by Shenzhen Power Supply Co., Ltd.

Acknowledgments

This work was supported by the Science and Technology Project of the China Southern Power Grid Co., Ltd.(Project number: SZKJXM20230085).

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.