Integrated Distribution System Research Articles

Unit commitment in solar‐based integrated energy distribution systems with electrical, thermal and natural gas flexibilities: Application of information gap decision theory

AbstractThe depleting oil reserves, air pollution and increasing energy demand, have overturned the focus of the scientific community to renewable energy sources. Among which the photovoltaic (PV) systems occupy more than half of the market share and are generally installed at the distribution level. The volatile and uncertain nature of these PV productions necessitates flexible resources in energy systems. To this end, the district heating systems have an outstanding flexibility on account of their high thermal inertia. This study investigates the optimal unit commitment scheduling for gas‐fired and non‐gas‐fired distributed generation units (NGU) in an integrated energy distribution system (IEDS) within the physical constraints of the electrical, natural gas and thermal energy distribution networks. Moreover, a planning‐based optimization framework is proposed to investigate the investment of battery storage systems in the electric distribution network under the high penetration of PV systems with the aim of enhancing flexibility and reducing the operating costs of the IEDS. In this framework, the information gap decision theory is deployed under risk‐averse and risk‐seeker strategies to deal with uncertain PV energy production. Additionally, the environmental emissions are considered in a multi‐objective approach. The IEDS is embodied through IEEE 33‐bus EDS, 20‐node natural gas network and an 8‐node district heating systems. Eventually, The proposed approach makes a noteworthy contribution to the advancement of solar energy systems in IEDS.

Stochastic‐gradient‐based control algorithms for power quality enhancement in solar photovoltaic interfaced three‐phase distribution system

AbstractHere, stochastic‐gradient‐based adaptive control algorithms have been discussed and employed for power quality enhancement in a Photovoltaics (PV) integrated distribution system. Least mean square (LMS), least mean fourth (LMF), sign‐error LMS, and ‐normalised LMS (‐NLMS) have been implemented as control algorithms for the estimation of fundamental load current. The performances of these adaptive algorithms are compared under steady‐state and dynamic conditions under the non‐linear load conditions in a closed‐loop three‐phase system. The main aim of implementing these algorithms is reactive power compensation, power quality enhancement, and load balancing in a single‐stage three‐phase grid‐tied PV system. The hysteresis current control (HCC) technique is used to generate switching pulses for the three‐phase Distribution Static Power Compensator (DSTATCOM). An MPPT is also employed to ensure maximum power delivery from the solar PV array. PV integrated three‐phase single‐stage distribution system with adaptive control algorithms is implemented in MATLAB/Simulink environment as well as in experimental environment to achieve the goals per standard IEEE‐519.

A Novel Approach for Power Quality Improvement Using D-STATCOM in Wind Integrated Distribution System

Objectives: The major goal of the proposed article is to enhance the power quality of a wind-integrated radial distribution network utilizing D-STATCOM. It is done by the appropriate allocation of wind turbine-based DGs and D-STATCOM. Methods: The multi-objective optimization problem is implemented using a novel and effective Prairie Dog Optimization (PDO) to attain the best-compromised solutions. This optimization tool is well suited for solving complex, non-linear voltage stability problems. The proposed approach is validated for the modified IEEE-13 bus highly unbalanced system using MATLAB. Findings: The findings indicate enhancements in the voltage profile, system losses, and total harmonic distortion (THD). The THD for the load current is 18%, while the THD for the source current is 2.54% for nonlinear loads using the proposed methodology. The voltage profile of 3.25% is enhanced as compared with the existing method, which is 2.15% better than the other obtainable method. Novelty: Prairie Dog Optimization (PDO) was chosen over traditional algorithms for its nature-inspired approach, simplicity, and efficacy in exploring complicated search fields. Its robust exploration and exploitation skills make it excellent for multi-modal optimization challenges. Keywords: Radial distribution system (RDS), D-STATCOM, Power quality, Prairie Dog Optimization, THD

Forced carrier perturbation opens a loophole for chip-based continuous variable quantum key distribution system

The integration of the continous-variable quantum key distribution(CVQKD) system is an important technical route with great potential value for constructing high-performance and low-cost CVQKD system. In all previous CVQKD studies, the quantum efficiency of the detector can be calibrated in advance and is considered to remain unchanged. But when the size of the system shrinks to the on-chip level, especially in the premise of non-uniform waveguide, heavy doping and other factors, effects such as free carrier absorption and scattering loss will become prominent, which will directly cause carriers undergo violent migration due to the tiny jitter of the local oscillator and further lead to dynamical variation of quantum efficiency of detection. In this paper, we propose a practical chip-based detector model, and numerous simulation results based on this model show that the practical system will face potential security threats due to the variable quantum efficiency. Moreover, two defense strategies are proposed to solve these practical security problems commonly exist in general chip-based CVQKD systems. This work breaks the inherent viewpoint that the quantum efficiency in the chip-based CVQKD system can still be calibrated in advance, and suggests a more rigorous consideration of practical security for development of chip-based CVQKD.

Optimal planning of integrated electricity-natural gas distribution systems with hydrogen enriched compressed natural gas operation

In future integrated electricity-natural gas distribution systems (IEGDS), hydrogen and methane converted from excessive renewable generation will be mixed with natural gas to form hydrogen enriched compressed natural gas (HCNG) for fewer carbon emissions. Consequently, optimal planning of the HCNG-integrated IEGDS plays an essential role in increasing the economy and technical benefits. However, integrating HCNG operation into the planning of IEGDS still has many challenges, such as unrealistic modeling, nonlinear constraints, and the potential risk of voltage violations. The purpose of this paper is to develop a tractable optimization model for planning and operation of the HCNG-integrated IEGDS, aiming to minimize the investment and operating cost, reduce the voltage violation, and improve the renewable power penetration rate. To achieve this, a bilevel optimization model is developed for optimal planning of wind turbines and soft open points (SOPs) in the IEGDS considering comprehensive HCNG operation, in which both hydrogen and methane injection are considered and optimized for different system operation scenarios. Furthermore, the proposed nonlinear model is reformulated to a tractable bilevel mixed-integer second-order cone model using several reformulation techniques and solved by the reformulation and decomposition algorithm. Case studies, performed using the publicly available datasets, are conducted to demonstrate the economic and technical improvement by implementing the proposed planning model. The annual planning results show that incorporating the coordination between SOPs and methane injection results in a 6.77% reduction in investment cost, a 22.64% reduction in operating cost, a 62.69% decrease in voltage violation, and a 23.58% increase in the wind power penetration rate. Moreover, SOPs are more applicable to the safe operation of the IEGDS under high energy load conditions.

Improving islanded distribution system stability with adaptive decision-making framework

Abstract In an integrated distribution system incorporating distributed generation (DG), various technical challenges must be addressed when the grid becomes disconnected and transforms into an islanded system. The main focus in such circumstances revolves around ensuring the stability of the islanded network. This study presents an advanced decision-making framework for supporting islanded networks by integrating metaheuristic Black Widow Optimization (BWO) and the rate of change of the voltage stability index (RoCVSI). The Rate of Change of the Voltage Stability Index (RoCVSI) detects instability in islanded networks by continuously monitoring rapid changes in the voltage stability margin. Upon identifying potential instability, an advanced decision-making strategy utilizing the Black Widow Optimization (BWO) algorithm is deployed. BWO generates multiple load-shedding scenarios and evaluates their impact on system stability, iteratively refining the solutions through processes similar to selection and cannibalism in black widow spiders. The optimal load-shedding strategy is then implemented to selectively shed specific loads, thereby reducing demand and enhancing island stability. The proposed scheme’s effectiveness for islanded network stability is assessed by extensively analyzing the IEEE 33-bus system. The efficiency of the proposed approach is confirmed through a comparative analysis, with results indicating the better efficiency of the proposed method in the islanded network.

O-band QKD link over a multiple ONT loaded carrier-grade GPON for FTTH applications.

We have successfully demonstrated the integration of a commercial O-band Quantum Key Distribution (QKD) system over a testbed that replicates a carrier-grade Fiber-to-the-Home (FTTH) optical access network consisting of components and systems installed in real-life FTTH operational deployments. The experiment demonstrated a QKD transmission over a 1:16 user Gigabit Optical Passive Network (GPON) configuration featuring a total of 9 Optical Network Terminals (ONTs) at the premises of the Telecom Operator COSMOTE that followed the operator's standard FTTH divided in two splitting stages. The architecture we implemented was a downstream access network with the quantum transmitter located at the operator's Central Office (CO) and the quantum receiver located on the end user's side.

Optimal Placement and Capacity of BESS and PV in EV Integrated Distribution Systems: The Tenth Feeder of Phitsanulok Substation Case Study

Installing a battery energy storage system (BESS) and renewable energy sources can significantly improve distribution network performance in several aspects, especially in electric vehicle (EV)-integrated systems because of high load demands. With the high costs of the BESS and PV, optimal placement and capacity of them must be carefully considered. This work proposes a solution for determining the optimal placement and capacity of a BESS and photovoltaic (PV) in a distribution system by considering EV penetrations. The objective function is to reduce system costs, comprising installation, replacement, and operation and maintenance costs of the BESS and PV. The replacement cost is considered over 20 years, and the maintenance and operation costs incurred in the distribution system include transmission line loss, voltage regulation, and peak demand costs. To solve the problem, two metaheuristic algorithms consisting of particle swarm optimization (PSO) and the African vulture optimization algorithm (AVOA) are utilized. The tenth feeder of Phitsanulok substation 1 (PLA10), Thailand, which is a 91-bus distribution network, is tested to evaluate the performance of the proposed approach. The results obtained from the considered algorithms are compared based on distribution system performance enhancement, payback period, and statistical analysis. It is found from the simulation results that the installation of the BESS and PV could significantly minimize system cost, improve the voltage profile, reduce transmission line loss, and decrease peak demand. The voltage deviation could be reduced by 86%, line loss was reduced by 0.78 MW, and peak demand could be decreased by 5.706 MW compared to the case without BESS and PV installations.

Locational marginal price based scheduling strategy for effective utilization of battery energy storage in PV integrated distribution system

Integration of renewable energy resources (RERs) and complexities associated with varying load patterns urge the demand for energy storage systems (ESS) to ensure real power balancing of distribution system. Among various ESS, battery energy storage system (BESS) guarantees the reliable operation of microgrids in terms of economic and technical functionalities. The scheduling of microgrids becomes essential for the economic and optimal performance of both generating sources and loads. In this work, the load-shifting capability of BESS is utilized for the optimal scheduling of grid-connected microgrids. BESS has a significant role in the effective utilization of power from RERs during grid balancing. This paper discusses the scheduling of grid-connected microgrid with two scheduling strategies, which differ in the charging behaviour of BESS. Scheduling decisions are based on the value of locational marginal price (LMP) of distribution system. In scheduling strategy-I, BESS charges at off-peak hours, either from the PV system or from the grid. Meanwhile, in scheduling strategy- II, BESS charges from the PV system at peak or off-peak hours. These two scheduling methods are also compared with the scheduling of the distribution system without integrating the microgrid. The cost of power generation, power from the main grid, and active power losses of the distribution system are calculated by performing optimal power flow (OPF). The effectiveness of the proposed scheduling strategies are validated on the IEEE-69 bus system for 24 h time duration by using MATPOWER simulation tool. The results obtained after OPF establishes the requirement of effective utilization of BESS in PV integrated distribution system.

Opportunistic Pathogens in Drinking Water Distribution Systems-A Review.

In contrast to "frank" pathogens, like Salmonella entrocolitica, Shigella dysenteriae, and Vibrio cholerae, that always have a probability of disease, "opportunistic" pathogens are organisms that cause an infectious disease in a host with a weakened immune system and rarely in a healthy host. Historically, drinking water treatment has focused on control of frank pathogens, particularly those from human or animal sources (like Giardia lamblia, Cryptosporidium parvum, or Hepatitis A virus), but in recent years outbreaks from drinking water have increasingly been due to opportunistic pathogens. Characteristics of opportunistic pathogens that make them problematic for water treatment include: (1) they are normally present in aquatic environments, (2) they grow in biofilms that protect the bacteria from disinfectants, and (3) under appropriate conditions in drinking water systems (e.g., warm water, stagnation, low disinfectant levels, etc.), these bacteria can amplify to levels that can pose a public health risk. The three most common opportunistic pathogens in drinking water systems are Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa. This report focuses on these organisms to provide information on their public health risk, occurrence in drinking water systems, susceptibility to various disinfectants, and other operational practices (like flushing and cleaning of pipes and storage tanks). In addition, information is provided on a group of nine other opportunistic pathogens that are less commonly found in drinking water systems, including Aeromonas hydrophila, Klebsiella pneumoniae, Serratia marcescens, Burkholderia pseudomallei, Acinetobacter baumannii, Stenotrophomonas maltophilia, Arcobacter butzleri, and several free-living amoebae including Naegleria fowleri and species of Acanthamoeba. The public health risk for these microbes in drinking water is still unclear, but in most cases, efforts to manage Legionella, mycobacteria, and Pseudomonas risks will also be effective for these other opportunistic pathogens. The approach to managing opportunistic pathogens in drinking water supplies focuses on controlling the growth of these organisms. Many of these microbes are normal inhabitants in biofilms in water, so the attention is less on eliminating these organisms from entering the system and more on managing their occurrence and concentrations in the pipe network. With anticipated warming trends associated with climate change, the factors that drive the growth of opportunistic pathogens in drinking water systems will likely increase. It is important, therefore, to evaluate treatment barriers and management activities for control of opportunistic pathogen risks. Controls for primary treatment, particularly for turbidity management and disinfection, should be reviewed to ensure adequacy for opportunistic pathogen control. However, the major focus for the utility's opportunistic pathogen risk reduction plan is the management of biological activity and biofilms in the distribution system. Factors that influence the growth of microbes (primarily in biofilms) in the distribution system include, temperature, disinfectant type and concentration, nutrient levels (measured as AOC or BDOC), stagnation, flushing of pipes and cleaning of storage tank sediments, and corrosion control. Pressure management and distribution system integrity are also important to the microbial quality of water but are related more to the intrusion of contaminants into the distribution system rather than directly related to microbial growth. Summarizing the identified risk from drinking water, the availability and quality of disinfection data for treatment, and guidelines or standards for control showed that adequate information is best available for management of L. pneumophila. For L. pneumophila, the risk for this organism has been clearly established from drinking water, cases have increased worldwide, and it is one of the most identified causes of drinking water outbreaks. Water management best practices (e.g., maintenance of a disinfectant residual throughout the distribution system, flushing and cleaning of sediments in pipelines and storage tanks, among others) have been shown to be effective for control of L. pneumophila in water supplies. In addition, there are well documented management guidelines available for the control of the organism in drinking water distribution systems. By comparison, management of risks for Mycobacteria from water are less clear than for L. pneumophila. Treatment of M. avium is difficult due to its resistance to disinfection, the tendency to form clumps, and attachment to surfaces in biofilms. Additionally, there are no guidelines for management of M. avium in drinking water, and one risk assessment study suggested a low risk of infection. The role of tap water in the transmission of the other opportunistic pathogens is less clear and, in many cases, actions to manage L. pneumophila (e.g., maintenance of a disinfectant residual, flushing, cleaning of storage tanks, etc.) will also be beneficial in helping to manage these organisms as well.

A Branch-and-Price Algorithm for an Integrated Online and Offline Retailing Distribution System with Product Return

This study identifies critical inefficiencies within a dual-channel operation model employed by a fast fashion company, particularly the independent operation of three logistics distribution systems. These systems result in high operational costs and low resource utilization, primarily due to redundant vehicle dispatches to meet the distinct demands of retail store replenishment, online customer orders, and customer return demands, as well as random and scattered return requests leading to vehicle underutilization. To address these challenges, we propose a novel integrated logistics distribution system design and management method tailored for dual-channel sales and distribution businesses. The approach consolidates the three distribution systems into one cohesive framework, thus streamlining the delivery process and reducing vehicle trips by combining retail and customer visits. An optimization algorithm is introduced to factor in inventory and distribution distance, aiming to achieve global optimization in pairing retail store inventory with online customer orders and unifying the distribution of replenishment products, online products, and returned products. The paper contributes to the field by introducing a new variation of the Vehicle Routing Problem (VRP) that arises from an integrated distribution system, combining common VRP issues with more complex challenges. A custom Branch-and-Price (B&P) algorithm is developed to efficiently find optimal routes. Furthermore, we demonstrate the benefits of the integrated system over traditional, segregated systems through real-world data analysis and assess various factors including return rates and inventory conditions. The study also enhances the model by allowing inventory transfers between retail stores, improving inventory distribution balance, and offering solutions for scenarios with critically low inventory levels. Our findings highlight a significant reduction in total operating cost savings of up to 49.9% and vehicle usage when using the integrated distribution system compared to independent two-stage and three-stage systems. The integrated approach enables the utilization of vacant vehicle space and the dynamic selection and combination of tasks, preventing unnecessary mileage and space wastage. Notably, the integration of inventory sharing among retail stores has proven to be a key factor in generating feasible solutions under tight inventory conditions and reducing operational costs and vehicle numbers, with the benefits amplified in large-scale problem instances.

Impact of operational conditions on drinking water biofilm dynamics and coliform invasion potential.

The revelation that even low concentrations of coliforms can infiltrate into mature drinking water biofilms highlights a potential public health concern. Nowadays, the measurement of coliform bacteria is used as an indicator for fecal contamination and to control the effectiveness of disinfection processes and the cleanliness and integrity of distribution systems. In Flanders (Belgium), 533 out of 18,840 measurements exceeded the established norm for the coliform indicator parameter in 2021; however, the source of microbial contamination is mostly unknown. Here, we showed that mature biofilms, are susceptible to invasion of Serratia fonticola. These findings emphasize the importance of understanding and managing biofilms in drinking water distribution systems, not only for their potential to influence water quality, but also for their role in harboring and potentially disseminating pathogens. Further research into biofilm detachment, long-term responses to operational changes, and pathogen persistence within biofilms is crucial to inform strategies for safeguarding drinking water quality.

A differential amplitude variation based pilot relaying scheme for microgrid integrated distribution system

Abstract The inclusion of inverter-interfaced distributed generating sources (IIDGS) in the active distribution network offers operational and protection constraints. Dynamic fault behavior of these DGS results in changes like the radial distribution systems. Thus, conventional protection schemes fail to discriminate the in-zone and out-zone faults. Hence, this manuscript describes a new protection scheme based on current variation at the relay location used to discriminate the internal and external faults. This technique requires phasor information of the current signals of both ends and adjacent lines using micro phasor measurement units (µPMUs). Using the current phasor information two components named internal and external are computed at the relay location which is called differential amplitude variation index (DAVI), used to identify the internal and external faults. A modified two-feeder radial distribution network and modified IEEE-13 bus test systems are modeled using EMTDC/PSCAD to validate the proposed strategy. Numerous disturbance cases have been simulated and the feasibility and applicability attributes of the suggested method are verified from the results.

Research on Grid-connected Voltage Improvement Technologies for High-penetration Photovoltaic Power Generation

The degradation in power quality due to the high penetration of grid-connected photovoltaic (PV) systems is a critical issue that urgently needs to be addressed in the field of renewable energy generation. Solar PV systems typically lack mechanical inertia, which means that they are unable to provide additional mechanical inertia to maintain voltage and frequency stability when the power system is subjected to external disturbances. Therefore, to ensure stable operation of the power system, alternative measures need to be relied on to maintain voltage stability. This article first analyzes the mechanism of voltage fluctuations when photovoltaic power generation is connected to the grid. It then delves into the challenges of power quality brought about by the grid integration of renewable distributed generation systems, as well as the current research status of mainstream voltage improvement technologies, customized power devices, and energy storage systems. Finally, the paper presents recommendations for improving grid voltage quality, enhancing the stability and reliability of the power system, and promoting the widespread application of renewable energy in power systems.

Comparison of PetrifilmTM AC and Pour plate techniques used for the heterotrophic aerobic bacterial count in water.

Heterotrophic bacteria (HPC) are commonly found in water samples. While these bacterial counts do not necessarily indicate a health hazard, high counts provide a good indication of the efficiency of water disinfection and integrity of distribution systems. The aim of this study was to compare the PetrifimTM AC method to the Pour Plate technique for the testing of HPC in water samples. Artificially contaminated (192 samples) and natural water samples (25) were processed using two methods. Both methods accurately detected high, medium and low counts of HPC, producing average Z scores between -2 and+2. Paired-wise student t-test and correlation coefficient showed nonsignificant differences between the results of two methods. Acceptable repeatability and reproducibility was obtained using both the methods. Uncertainty of measurement for PetrifilmTM AC and Pour Plate method was found to be 2.9% and 5.4% respectively. PetrifilmTM AC proved to be robust at 33°C and 37°C. In conclusion, PetrifimTM AC, which is easy to process, read and less time consuming, proved to be comparable to the conventional Pour Plate method in establishing HPC in water. In addition, PetrifimTM AC requires less space for the processing and incubation, generate small volume of waste for disposal and requires no equipment, except for the incubator.

Optimal allocation of open unified power quality conditioner in integrated distribution system environment with renewable energy sources

ABSTRACT The growing utilization of renewable energy sources (RES) that rely on inverters has adverse impacts on distribution systems, resulting in challenges such as power quality (PQ) issues and increased losses in the distribution network. One potential remedy for these issues involves the strategic allocation of open unified power quality conditioner (UPQC-O). This paper introduces a comprehensive two-layer integrated optimization model designed for the allocation of UPQC-O and RES in an active distribution network. The primary objective is to enhance energy efficiency, PQ, and economic benefits simultaneously. Furthermore, an innovative solver known as the multi-improved whale optimization method (multi-IWOA) has been implemented to address the optimization problem at hand. The efficacy of this approach was validated through testing on both the standard IEEE 69-bus radial distribution system and a real-world Indian 52-bus system. The evaluation results underscore the significance of optimally distributing UPQC-O resources while taking into consideration the integration of RES within the distribution system. It’s worth noting that the proposed methodology achieved a substantial 56.72% cost reduction for the IEEE 69-bus radial distribution system and a significant 76.092% cost reduction for the Practical System Indian 52-bus system. This highlights the substantial advantages of the proposed methodology for the efficient management of UPQC-O and RES integration in distribution systems.

The Use of Artificial Intelligent Applications In Electrical Power Distribution and Automation Control System

Artificial intelligence has provided great potential and space for the optimization of electrical engineering and it will bring about great improvement not only in economic aspect but also in safety and actual operation control. Since the advent of artificial intelligence it has been widely applied in all fields of life and achieved notable application effect its emergence has even pointed out the direction for the development of many fields and the field of electrical automation control is no exception. In reality, the application of artificial intelligence technology has greatly promoted the progress of the concrete practice of electrical automation and should be paid full attention to by related enterprises and staff. This paper aims to summarize the emergence and development of artificial intelligence and its components and finally summarize the advantages and functions of artificial intelligence in electrical automation control. Advances in machine learning and artificial intelligence (AI) techniques bring new opportunities to numerous intractable tasks for operation and control in modern electric distribution systems. Revolving around the characteristics of distribution system operation and integration of distributed energy resources this paper also illuminates prospects and challenges typified by the privacy explain ability and interpretability of such AI applications in smart grids. KEYWORDS: - Distribution systems, smart buildings, neural networks, Artificial Intelligence, Electrical Engineering, power systems.

Power Supply Reliability Analysis of Distribution Systems Considering Data Transmission Quality of Distribution Automation Terminals

A distribution automation system is the integration of physical power distribution systems and information systems. Its information system guarantees the safe operation and reliable power supply of physical systems by monitoring, collecting and transmitting information. In the information system, the remote terminal unit of distribution automation is the hub of the information system, connecting it to the physical power system. Considering the unreliability of terminal information transmission in the information system, this paper aims to build a model to quantitatively evaluate the impact of unreliable transmission information on the power supply reliability of distribution systems. Firstly, the m-segment and n-connection unit model of distribution feeders is established, and then, the power supply reliability indices in the process of handling feeder terminal unit error are analyzed and calculated under the configuration modes of “three-remote” and “two-remote” of remote terminals. Then, considering the impact of a transmission error in the information system, the reliability index calibration model under the condition of unreliable information transmission is established. Finally, a case study is presented to illustrate how the proposed model is implemented.

Honeycomb integrated energy distribution system: Networking structure and operation mode

AbstractThe distribution system is undergoing a transformation into a platform that integrates multiple energy sources, including electricity, gas, and heat, to facilitate point‐to‐point energy transmission. However, the existing tree radiation structure of the distribution system is inadequate to meet the demand. To address this, this paper proposes the networking structure and operation mode of the honeycomb integrated energy distribution system (HIEDS). Firstly, the paper outlines the network structure of HIEDS, which includes flexible interconnection modes between micro‐networks and key equipment, such as the integrated energy stations. Secondly, two typical operation modes of HIEDS with the objectives of operation economy and load balancing are proposed, respectively. Finally, the operation characteristics of HIEDS in different scenarios are analysed through case studies, and HIEDS is compared with other typical interconnection structures of micro‐energy networks further. The results demonstrate that HIEDS provides a more flexible energy supply mode, which can improve the operation economy and reliability of the distribution system. This study will provide a theoretical basis for optimising the structure and operation mode of future integrated energy distribution systems.

A cooperative resilience-oriented planning framework for integrated distribution energy systems and multi-carrier energy microgrids considering energy trading

Integrated distribution systems (IDSs) and multi-carrier energy microgrids (MCEMs) can play a crucial role in enhancing distribution energy systems’ overall efficiency and flexibility. By cascading energy usage and cooperating through energy trading, IDSs and MCEMs can reduce overall system costs and provide more flexibility for system operators. Adding resilience to the planning problem of IDSs can reduce planning costs in the long term, as proactive preparedness is key to coping with high-impact rare (HR) events. Adding resilience to the planning problem of IDSs can reduce the planning costs in the long term since proactive preparedness is a key necessity to cope with high-impact rare (HR) events. This paper proposes a resilience-oriented stochastic tri-level and two-stage cooperative expansion planning of IDSs and MCEMs, considering energy trading between IDSs and MCEMs. The first stage comprises two levels; the first level minimizes the investment and operation costs of IDSs and MCEMs, while the second level desires to maximize the energy exchange profit for MCEMs and thus reduce the overall costs. The second stage includes the third level problem involving two objective functions: resilience cost minimization and resilience index (RI) maximization. The multi-objective problem in the second stage is converted into a single-objective problem using the min–max regret method. The DC and AC configurations for the power distribution system (PDS) and power microgrids (PMGs) are studied to identify the optimal configuration of these networks in the expansion planning problem. A new framework is proposed based on an aggregator-agent splitting solution using the aggregator coupling coordinator unit (ACC) responsible for coordinating IDNs and MCEMs. The studied large-scale complex optimization problem is efficiently solved computationally by introducing a combined adaptive dynamic programming (ADP) and linearized alternating direction method of multipliers with parallel splitting (LADMMPSAP) algorithm. Three cases are studied to demonstrate the effectiveness of the proposed model and method. The results depict that MCEMs help reduce expansion planning costs and improve the system’s resilience. Adding resilience to the expansion planning problem enhances the resilience of the whole system and simultaneously reduces the costs by 2.7%. The expansion planning costs for the AC and DC configuration are close, and the AC is the optimal choice in all case studies. By increasing the planning horizon from 5 to 10 years, DC will be the optimal solution since network reinforcement costs and power losses are significantly lower.