Simulation Of Distribution Network Research Articles

Study on Large-Scale Urban Water Distribution Network Computation Method Based on a GPU Framework

Large-scale urban water distribution network simulation plays a critical role in the construction, monitoring, and maintenance of urban water distribution systems. However, during the simulation process, matrix inversion calculations generate a large amount of computational data and consume significant amounts of time, posing challenges for practical applications. To address this issue, this paper proposes a parallel gradient calculation algorithm based on GPU hardware and the CUDA Toolkit library and compares it with the EPANET model and a model based on CPU hardware and the Armadillo library. The results show that the GPU-based model not only achieves a precision level very close to the EPANET model, reaching 99% accuracy, but also significantly outperforms the CPU-based model. Furthermore, during the simulation, the GPU architecture is able to efficiently handle large-scale data and achieve faster convergence, significantly reducing the overall simulation time. Particularly in handling larger-scale water distribution networks, the GPU architecture can improve computational efficiency by up to 13 times. Further analysis reveals that different GPU models exhibit significant differences in computational efficiency, with memory capacity being a key factor affecting performance. GPU devices with larger memory capacity demonstrate higher computational efficiency when processing large-scale water distribution networks. This study demonstrates the advantages of GPU acceleration technology in the simulation of large-scale urban water distribution networks and provides important theoretical and technical support for practical applications in this field. By carefully selecting and configuring GPU devices, the computational efficiency of large-scale water distribution networks can be significantly improved, providing more efficient solutions for future urban water resource management and planning.

Simulation of Intermittent Water Distribution Networks by EPA-SWMM: Comparing Model Results and Field Experiments

Simulation of Intermittent Water Distribution Networks by EPA-SWMM: Comparing Model Results and Field Experiments

Modeling and Simulation of Distribution Networks with High Renewable Penetration in Open-Source Software: QGIS and OpenDSS

Modeling and Simulation of Distribution Networks with High Renewable Penetration in Open-Source Software: QGIS and OpenDSS

A Data–Physics-Driven Modeling Approach of Key Equipment for Large-Scale Distribution Network Simulation

Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.

Large-scale quantum key distribution network simulator

The wide range of supported services in modern telecommunication networks has increased the demand for highly secure means of communication. Common security frameworks based on the computational security model are expected to become insecure due to significant advances in quantum computing. Quantum key distribution (QKD), a new secret key agreement primitive, enables long-anticipated practical information-theoretical security (ITS). Over the past two decades, academic and industrial communities have devoted their time and resources to developing QKD-based networks that can distribute and serve ITS keys to remote parties. However, because the availability of QKD network testbeds to the larger research community is limited and the deployment of such systems is costly and difficult, progress in this area is noticeably slow. To address this problem and spur future development and education, we provide a valuable, unique tool for simulating a QKD network. The tool is essential to testing novel network management methodologies applied to large-scale QKD networks. The simulator model contained in the tool was validated by simulating a network with six nodes and three pairs of users. The results indicate that the designed functional elements operate correctly.

Modeling and Simulation of Distribution Networks under Lightning Transients: A Comparative Study of Accuracy and Complexity

Nowadays, electricity consumption is closely linked to the economic growth of cities, states, and countries, providing a better quality of life and security. Overhead power distribution networks at medium- and low-voltage levels are responsible for serving and supplying electricity to the largest consumer class, as they represent most consumer installations. Due to this reason, there is a vast expanse of exposed networks vulnerable to the effects of atmospheric discharges. Therefore, the objective of this article is to implement and evaluate the models available in the literature to represent distribution networks during transient events caused by lightning, using simulation in ATPDraw. These structures pose a significant complexity in their representation, and there are studies that assess more accurate methods for simulating transients in transmission lines, which have different structural and configuration characteristics. Ultimately, the results demonstrate that the choice of which model to implement in a simulation heavily depends on the analysis to be conducted by the researcher, and it can be observed that more accurate methods do not always yield substantial differences in the obtained outcomes.

Communicationless Overcurrent Relays Coordination for Active Distribution Network Considering Fault Repairing Periods

This paper presents an integrated overcurrent relays coordination approach for an Egyptian electric power distribution system. The protection scheme suits all network topologies, including adding distribution generation units (DGs) and creating new paths during fault repair periods. The optimal types, sizes, and locations of DGs are obtained using HOMER software (Homer Pro 3.10.3) and a genetic algorithm (GA). The obtained values align with minimizing energy costs and environmental pollution. The proposed approach maintains dependability and security under all configurations using a single optimum setting for each relay. The calculations consider probable operating conditions, including DGs and fault repair periods. The enhanced coordination procedure partitions the ring into four parts and divides the process into four paths. The worst condition of two cascaded overcurrent relays from the DGs’ presence viewpoint is generalized for future work. Moreover, a novel concept addresses the issue of insensitivity during fault repair periods. The performance is validated through the simulation of an Egyptian primary distribution network.

SPICE‐compliant load flow analysis of power distribution networks with behavioral loads

AbstractThis paper discusses an alternative and Simulation Program with Integrated Circuit Emphasis (SPICE)‐compatible solution for the steady‐state simulation of power distribution networks. It introduces two alternative auxiliary subcircuits that allow to efficiently simulate the network in any simulation tool for circuit analysis. This feature introduces remarkable benefits in terms of simplicity and generality, since it avoids the need for any iterative method, thus bridging the gap between classical industry‐standard and general‐purpose simulators based on circuital equations, such as SPICE, and dedicated tools for the load flow analysis of power systems. The approach is first demonstrated based on a simple illustrative example, for which the performance in terms of accuracy and efficiency is discussed and then applied to the standard IEEE 33‐node power distribution benchmark.

Optimizing Algerian Company’s Delivery Fleet with Agent_Based Model in Anylogic

Abstract The utilization of simulation modelling in supply chain management has proven to be a valuable tool for logistics service providers, enabling them to optimize their operations and meet customer demands efficiently. AnyLogic, with its diverse capabilities in discrete event simulation, system dynamics, and agent-based simulation, stands out as a powerful software solution for tackling complex supply chain challenges. This paper significantly contributes by demonstrating the practical implementation of AnyLogic in the modelling and simulation of agro-food product distribution network, particularly vegetable oils from the Cevital group. Additionally, the study integrates an optimization experiment to ascertain the optimal number of vehicles required to meet a specific customer demand while ensuring a high level of fleet utilization. The obtained results are very encouraging and demonstrate the feasibility and effectiveness of our approach.

Analysis of Intermittent Water Distribution Networks Using a Dummy Emitter Device at Each Demand Node

The pipe component of a water distribution network (WDN) is sized based on the fixed design demand considering a peak factor and design period. Simulation of the designed network by a hydraulic solver provides nodal pressure head, head loss, velocity, and flow in each pipe as the prime outputs for the design demand, and it can also be used for extended-period simulation for a particular demand pattern over the supply hours. But, in reality, the behavior of the network does not match with such a result in an intermittent water supply (IWS) system due to the fact that all house service connections behave as an uncontrolled orifice. This has made it a challenging task in understanding and in predicting the behavior of the networks by the municipal engineer once the water starts flowing through the house service connections (HSCs). Though the municipal engineer provides the same pipe size for HSCs to all residences, the flow received by each house could vary based on the available pressure head at the ferrule point of the main water supply pipeline. In reality, maintaining constant pressure at each HSC is not feasible due to frictional head loss. Hence, variation in flow at the HSC is inevitable even with a small water supply system. This paper illustrates how to simulate the behavior of an IWS system based on the number of HSCs provided to each pipeline using a hydraulic solver. Hydraulic simulation of the water distribution network that provides IWS to consumers can be implemented easily by adding a fictitious node by assigning an appropriate emitter coefficient to each demand node through a fictitious link having a check valve in it. The method for finding the appropriate value of the emitter coefficient that helps in simulating HSCs is illustrated in the present work.

Optimal Exploitation of Urban Water Supply Networks Based on Pressure Management with the Nondominated Sorting Differential Evolution (NSDE) Algorithm

Urban water distribution networks are crucial infrastructures for providing essential services to society, but their exorbitant costs and limited water resources make their optimization a critical research area. Optimal management and design of these networks can help to reduce costs and enhance their efficiency while meeting technical, economic, and quality standards. In particular, the management of network pressure is critical for reducing leakage in water distribution systems. Thus, this study aimed to investigate two objective functions for optimizing the water distribution network: (i) minimizing costs while considering the number of pressure-relief valves, and (ii) minimizing network pressure by observing the optimal pressure range. To achieve this, the Nondominated Sorting Differential Evolution (NSDE) multi-objective metaheuristic algorithm was employed as the optimization tool, and a computer program was written in MATLAB software for solving the optimization models. EPANET software was also used for hydraulic simulation of the water distribution network. The efficiency and capabilities of these models were tested on the case study of the third district of Mashhad in Iran. The results indicated that the installation and adjustment of pressure-relief valves in accordance with the positions and optimal settings of the output of the proposed models significantly improved the desired goals, particularly the average pressure of the network. As an example of optimization, the study achieved a 56.12% reduction in pressure compared to the case without a plan, considering five pressure-relief valves.

Local Electricity Market operation in presence of residential energy storage in low voltage distribution network: Role of retail market pricing

Local Electricity Market (LEM) appears as a promising consumer-centric market-based approach that extends the self-consumption method, widely implemented in residential households, to collective self-consumption in the local energy communities, enabled through peer-to-peer (P2P) transactions. To facilitate the integration of LEM in the wholesale electricity market (WEM), it is paramount to comprehend the synergy of retail electricity pricing on the LEM operation hosted in the low-voltage distribution network (LVDN). The paper presents a co-simulation framework consisting of a local electricity market model coupled with a three-phase distribution network simulator to perform a holistic case study for a smart energy community in Ireland. The novel contribution of the work is to explore the potential of local electricity trading in the presence of residential energy storage (ES), under different retail pricing schemes existent in Ireland, by evaluating economic benefits to the energy community and network performance of three-phase LVDN. Extensive simulation studies indicate that the presence of residential ES significantly boosts P2P transactions under static time-of-use (SToU) pricing. These P2P transactions are primarily contributed by energy arbitrage (among customers in LEM) in the winter and surplus PV-generated electricity in the summer. On the other hand, the scheduling of ES under SToU pricing deteriorates the network performance of LVDN in winter, showing the highest active power loss and under-voltage scenario among all the cases. Another unique aspect of LVDN is the voltage unbalance studied and found to be highly correlated with ES operation under SToU pricing. Recommendations have been made to the relevant stakeholders and market actors, identifying key aspects necessary to roll out the LEM under retail electricity pricing schemes.

Optimization design of short-circuit test platform for the distribution network of integrated power system based on improved K-means clustering

Short-circuit test platform can verify the correctness of the distribution network simulation model and the effectiveness of short-circuits protection. It is necessary to simplify the structure of the distribution network into a typical branch and build an equivalent test platform due to the system’s complexity. The equivalent system based on empirical classification has particular subjectivity and randomness, which will reduce the representativeness of the short-circuit test platform. Therefore, this paper adopts the improved K-means clustering algorithm to cluster the short-circuit impedance parameters from the typical short-circuit point of the distribution network to the power supply into different clusters. Each cluster center is used as the equivalent system’s characteristic impedance to realize the complex system’s simplification. The feasibility of the improved K-means clustering algorithm is verified by comparing the short-circuit simulation results with the original and the empirical classification equivalent system.

Load Flow Study of GCT Powerhouse using ETAP

Load flow is one of the most significant aspects to consider while studying and analyzing power system functioning. A comprehensive study of load flow analysis at the Government College of Technology (GCT) powerhouse is offered in this research. The Electrical Transient Analyzer Program (ETAP) software is used to construct a case study of modelling and simulation of the actual power distribution network (Version: 19.1). A comparison of common load flow approaches for power distribution is also offered. This evaluation provides and compares numerical and practical approaches such as Adaptive Newton-Raphson, Newton-Raphson, and Fast Decoupled. The study is an analysis of high voltage substations to loads utilizing ETAP software. The capabilities and usefulness of load flow evaluation are proved by applying ETAP simulation findings to the actual distributed power system of GCT, Coimbatore. ETAP makes easy the conversion of traditional to a smart grid.

Evaluation of technical and economic potential of waste heat distribution networks in industrial sites

This paper presents a methodology for the evaluation of waste heat distribution networks in industrial sites. In the context of ultra-efficient industrial sites, implementing these networks shows significant energy cost and emission reduction potential through cooperation between companies. To this end, a mathematical methodology for waste heat distribution network simulation was developed. In this approach, a differential equation relating radial heat losses and internal temperature was derived to include temperature changes inside the pipe system. Furthermore, relevant parameters such as diameter, insulation thickness, and temperature at source and sink were used to determine the distribution network’s technical and economic feasibility . Using time discrete, characteristic thermal energy supply and demand data in the analysis framework, the technical and economic assessment of waste heat distribution networks was carried out via the use case of an industrial park. In this use case, the economic and ecological advantages were quantified and shown.

Numerical simulation of quantum key distribution network based on wavelength division multiplexing technology

Wavelength division multiplexing (WDM) technology can improve the networking level and overcome the shortcomings of low key rate under the existing technic background of measurement device independent quantum key distribution (MDI-QKD) protocol application. reference frame independent quantum key distribution (RFI-MDI-QKD) protocol cut down on the influence of the reference frame drift on the key distribution system. The decoy state protocol has important development prospects in the development of quantum communication networking. Combining the advantages of of the above protocols to realize RFI-MDI-QKD with WDM, the results show that the key distribution efficiency is improved with the increase in the number of WDM multiplexed channels, which promotes the further exploration and achievement of QKD networking application.

Implementation of Quantum Key Distribution network simulation in Quantum Channel

The aim is to analyze the efficiency of a communication method, Quantum key distribution. This newly popularized method of communication uses the principles of quantum mechanics. The simulation environment allows researchers to create complex network topologies and a high degree of control and repeatable experiments, allowing them to conduct studies and verify their outcomes. It would be costly to implement QKD in reality, which would need optical and Internet connections between network nodes and the verification of a certain network method or protocol. Thus, the performance analysis here is done in open-source software called NS-3 or Network Simulator- 3, which has an in-built module called QKD netsim for creating the quantum channel.

Distribution Network Regionalized Fault Location Based on an Improved Manta Ray Foraging Optimization Algorithm

To address the problem that the accuracy of traditional intelligent algorithms in distribution network fault location decreases with the expansion of distribution network scale, a regionalized fault location method for distribution networks containing distributed power sources based on the improved manta ray foraging optimization (IMRFO) algorithm is proposed. First, the global convergence property of the basic manta ray foraging optimization (MRFO) algorithm is improved by fusing the restart strategy and the opposition-based learning strategy. Then, based on the two-port equivalence principle, a topological model for regionalized fault hierarchical localization in distribution networks is constructed. Finally, the algorithm is improved by binary discretization using the Sigmoid function to output the fault vector and complete the fault location of the distribution network. Simulation experiments are conducted using MATLAB for IEEE-33 node distribution networks and the simulation results show that the IMRFO algorithm combined with the regionalization of complex distribution networks has a better effect of dimensionality reduction. Compared with the traditional distribution network simulation model, the fault location fault tolerance is greatly improved and its accuracy rate is increased by 1.8% and the location speed is improved by 15.537 ms.

The gas grid as a vector for regional decarbonisation - a techno economic case study for biomethane injection and natural gas heavy goods vehicles

This paper presents a novel method for incorporating the seasonal variations in gas demand into an assessment of the economic viability of a biomethane production and injection facility. A simulation of a gas distribution (Dx) network was built to investigate the impact of limits imposed by the gas network operator on the quantity of biomethane that can be injected. The results calculated the grid’s capacity to accept biomethane on an hourly basis over the course of a year. Scenarios of maximum, minimum and no demand at a Dx-connected compressed natural gas (CNG) filling station were computed for the 3 potential locations being investigated for the biomethane production and injection facility. This data was then used to determine a range of possible plant sizes for each potential facility location and CNG demand scenario. Next, a spatially explicit geographical information systems (GIS) model was created to map the distribution of feedstock suitable for biomethane production in the surrounding area and determine transportation distances. These two submodels fed into a techno-economic model that calculates the net present value (NPV) and levelised cost of energy (LCOE) for each configuration. Notably, the profitability of the plant was seen to increase proportionally with an increase in demand at the CNG filling station. Location 2 was determined to be the most economically viable site for the biomethane production and injection facility. The most economically competitive configurations resulted in an LCOE of 81.63 €/MWh, 83.59 €/MWh, and 83.73 €/MWh, with corresponding NPVs of M€ 9.56, M€ 3.98 and M€ 0.94, for maximum, minimum and no demand at the CNG filling station respectively. The most competitive configurations are achieved at a plant size of 115 GWh/a for the maximum CNG demand, 82.2 GWh/a for the minimum CNG demand, and 81.8 GWh/a for no CNG demand replacing 40%, 34%, and 35% of annual natural gas demand in the Dx network respectively.

Asynchronous multi‐rate method of real‐time simulation for active distribution networks

The real-time simulation of active distribution networks (ADNs) can provide an accurate insight into transient behaviours, but faces challenges in simulation efficiency and flexibility brought by larger system scales and wider time-scale ranges. This paper presents an asynchronous multi-rate (AMR) method and design for the real-time simulation of large-scale ADNs. In the proposed method, the entire ADN was decoupled into different subsystems according to accuracy requirements, and optimized time-steps were allocated to each subsystem to realize a fully distributed simulation. This not only alleviated the time-step coordination problem existing in multi-rate real-time simulations, but also enhanced the flexible expansion capabilities of the real-time simulator. To realize the AMR real-time simulation, a multi-rate interfacing method, synchronization mechanism, and data communication strategy are proposed in this paper, and their hardware design is also presented in detail. A modified IEEE 123-node system with photovoltaics and wind turbine generators was simulated on a 3 field-programmable gate arrays (FPGAs)-based AMR real-time simulator. The real-time results were captured by the oscilloscope and verified with PSCAD/EMTDC, which demonstrated the superiority in simulation flexibility and accuracy compared with the synchronous multi-rate (SMR) method.