Local Distribution Network Research Articles

Power Distribution System Characterization With Active Probing: Real-World Testing and Analysis

Power distribution systems are traditionally characterized using passive means such as parameter estimation and topology identification. This work investigates an active way to test and characterize dynamically changing distribution systems. The method actively perturbs local distribution networks with programmable pulses using a Grid Resonance Probe (GRP) and observes the response using a micro-phasor measurement unit ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> PMU). After applying advanced data analytics, the perturbation and response measurements can reveal characteristics of distribution systems, such as feeder parameters and topologies. To validate the proposed approach, three case studies are executed on a real distribution system, including visualization, feeder connection identification, and feeder impedance estimation. Real data processing considerations and sensitivity analysis are also discussed. The proposed testing and analysis approach is expected to provide engineers a new solution to measure, parameterize, and characterize distribution systems.

A day-ahead market clearing mechanism for nodal carbon intensity control using the flexibility of charging stations

A large number of high-capacity charging stations are being built and will enter the wholesale electricity market as independent entities. Energy storage is considered to be an effective means of mitigating carbon emissions. When a large number of charging stations with storage capacity enter the market, how to make full use of their flexibility in the wholesale market to control the carbon intensity of the power system is an urgent problem to be solved. To address this problem, in this paper, a day-ahead market clearing mechanism for nodal carbon intensity control using the flexibility of charging stations is proposed, and a distributed clearing algorithm based on the alternating direction method of multipliers is designed. The local distribution network operators are used as intermediate coordinators, through which the market operator and the local charging station operators transmit system flexibility demands and energy schedules, respectively. Market clearing is completed through several iterations. This reduces the complexity of the unified clearing model. Moreover, based on the data-model hybrid driven approach, the generalized energy storage model of the charging stations and the linear nodal carbon intensity constraints of the power system are established. The locational marginal price considering the carbon emission cost is derived. The simulation verifies that using the flexibility of the charging stations to improve the power flow distribution of the power system can control the nodal carbon intensity with only 0.11% cost increase. The distributed algorithm has good convergence.

Energy tunnels as an opportunity for sustainable development of urban areas

The use of renewable energies will be increasingly necessary to reduce carbon dioxide emissions. An important contribution can be provided by energy tunnels, which make it possible to draw on a form of clean, renewable and locally accessible thermal energy for heating and air conditioning of buildings. The paper describes the characteristics of an energy tunnel and the design aspects necessary for its conception. Explicit reference will be made to the studies conducted at the Politecnico di Torino which led to the development of an innovative energy segment then used to create an experimental prototype in the true size of an energy tunnel. The data collected allowed to evaluate the performance of the system and to study the possibility of thermally activating the tunnels of the future Line 2 of the Turin Metro, allocating the heat partly to the air conditioning of the stations and partly to external users. With a view to sustainable urban development, the possibility of integration with district heating systems and the possible creation of local heat distribution networks at different temperatures, directly connected to the underground infrastructure, is particularly attractive and promising.

Optimising the energy-water-CO2 nexus of a water distribution network

The digital age attracts significant challenges in the delivery of Fourth Industrial Revolution (4IR) based technologies. The energy-water-CO 2 nexus benefits of 4IR technologies are a significantly greater challenge, especially across the Water Distribution Network (WDN). A business process based energy-water-CO 2 nexus model was developed with the capacity to simulate a comprehensive WDN, and predict the impact of 4IR technologies on the energy-water-CO 2 nexus. The model was applied to the monitoring and control business process of a local water utilities water distribution network. The model simulates the baseline (as-is) energy-water-CO 2 nexus, and evaluates the impact of the adoption of variable speed drive (VSD) and the internet of things (IoT) based on three operational regimes: normal operating pressure, low pressure and high pressure. The model evaluates VSD and IoT adoption singly and in-combination. The VSD has the largest positive impact on the energy-water-CO 2 nexus, reducing the energy demand and CO 2 emissions by16% each, and the water losses by 22%. A reduction in water losses, results in an increase in revenue for the water utility enabling the upgrading of aging infrastructure, investment in digital technologies and the expansion of infrastructure to increase access to clean drinking water. Whilst the impact of IoT on the WDN water-energy-CO 2 nexus is low, it is critical towards developing a “smart” and “self-adjusting” water distribution network.

Review of PV Solar Energy Development 2011–2021 in Central European Countries

According to the data collected in 2022 during 5th International Off-Grid Renewable Energy Conference organized in Abu Dhabi by the International Renewable Energy Agency, the global energy requirements show a negative impact on approximately 785 million people facing energy poverty. The long-term energy sustainability solutions should consider off-grid solutions in the planning of an energy mix and be considered as interim both in remote and already urbanized areas. These measures require integrated planning and partnering with local distribution networks. The review presents the development of photovoltaic installations in Central European countries. For more than 40 years, this area belonged to different regimes and joined the European Union at various dates. Hence, the development of energy policies and cultural and social expectations differ even when based on the Green Deal presented by the European Union in 2020. The outcomes prove that even with a variety of policy measures, the strongest boost can be given only by a set of national rules and financial incentives supporting the stakeholders. It should be noted that the advancement of PV often does not rely on climatic conditions, but more on the level of incentives undertaken by each country, as well as the general policy measures undertaken on the EU level.

Geothermal deep closed-loop heat exchangers: A novel technical potential evaluation to answer the power and heat demands

This paper investigates and optimises the thermal performance of deep closed-loop heat exchanger (DCHE) systems by applying a computational numerical approach. The investigated DCHE configuration accounts for two deep vertical boreholes, an injection and a production well, connected by a horizontal borehole at depth and an insulated pipeline at the surface, establishing an effective closed-loop system. First, a parametric sensitivity study explores the effects of the environmental, design and operating variables on the production temperature. The simulation uses realistic geological and geothermal conditions, depths, circulation rates and injection temperatures. Two complex numerical models are then solved for site-specific DCHEs in different geological scenarios: a foreland basin and a convergent margin hosting low-to-intermediate and high-temperature geothermal resources, respectively. Production temperatures beyond 40–60 °C and 100 °C, sustainable for both heat and electric power generation, are obtained, depending on the geothermal conditions and closed-loop dimensions. Furthermore, circulation rates of 0.02–0.04 m3 s−1 are cost-effective, and the system's efficiency and sustainability increase when a fluctuating and periodic heat extraction strategy is employed. When efficiently operated, DCHEs are a viable solution for renewable energy production and should be integrated into the local heat market and distribution network infrastructure. Field of researchEarth and Planetary Sciences; Energy; Environmental Sciences

Techno-economic optimization of large-scale deep geothermal district heating systems with long-distance heat transport

Geothermal energy can play an important role in decarbonizing the heating sector, however, a limiting factor is that heat demand in urban areas does not usually coincide spatially with geological settings favorable to the extraction of geothermal energy. Long-distance heat transport could enable the direct use of geothermal resources even in areas with low or no geothermal potential. This paper proposes the cost-optimal coordinated deployment of geothermal heating plants together with heat transport and distribution networks to simultaneously supply geothermal heat to multiple urban areas. To this end, a holistic approach comprising the mapping of geothermal potential for direct-use, the estimation of district heating potential, and a two-step optimization model to calculate cost-optimal large-scale geothermal district heating systems, is presented and applied to the Free State of Bavaria in Germany. As a result, heat supply costs can be reduced by 15% if fewer geothermal wells are drilled in more geologically favorable areas at greater distances from heat sinks. Calculated levelized costs of heat without local distribution networks of 33–39 €/MWh show that geothermal energy could transition from a local to a regional use if utilized in in scenarios with high full-load hours. The proposed methodology can be adapted to develop expansion strategies for deep geothermal energy in other similar regions worldwide.

Electrical power supply system planning for a modern catenary-free rapid charging

Electric power supply system planning is practically an important function of the modern light rail transit system with catenary free operation and rapid charging. Installing a modern dynamic load of the traction power supply system with the local electric distribution network needs to consider its capacity and feeder to support enough and efficiently. In this paper, the design of the electrical power supply system of the pilot project of Nakhon Ratchasima Green Line light rail system with 11.6-km line length and 21 passenger stations operated with catenary-free and powered with an on-board energy storage device has been proposed and planned to replace the old local transportation. The traction power supply of the light rail system drawn power from the MV distribution feeder practically consist of receiving power substation, MV power feeding system power feeder substation, charging power supply and service power supply have been designed provided the configuration circuit. A rapid charge system to delivery high power to fulfill the on-board energy storage is considered to recharge at passenger stations with an overhead conductor or wireless power transfer during a short dwell time. A number of charging station is determined accordingly the capacity of the power substation and its positions. The traction power drawn by a train service round-trip that related to the capacity of the power substation as a charging station has been calculated by the simulation of the train movement. The regenerative braking energy during train operated in braking mode is also considered as a partial charging energy the on-board energy storage device. From the proposed design, the motive energy consumption of each scenario charging formations obtains the maximum charging energy drawn by the train between charging points, the capacity of on-board energy storage devices, maximum charging power and the total charging points.

Flexible management and decarbonisation of rural networks using multi‐functional battery control

To support the electrification of heat and transport, distribution network operators are looking to adopt network management solutions which can exploit local flexibility to advance their decarbonisation efforts in line with the evolving management requirements of the network. This paper develops a multi-functional battery control strategy that integrates constraint management with carbon-intensity linked control dispatch – carbon control – to support decarbonisation of rural distribution networks in Scotland by displacing last resort backup diesel generation and facilitating low carbon network balancing in the drive towards self-sustaining local distribution networks. The interplay between the different functionalities is considered to understand the challenges, and opportunities, of adopting multi-functional battery storage as an alternative management solution based on an operational distribution network in Scotland. Case studies are presented which consider network constraints at different times of day and year for various generation, demand and carbon intensity profiles to support this investigation. The findings of this work provide for the near-term, realisation of self-sustaining carbon-neutral local distribution networks that are in keeping with both the operational objectives of incumbent network operators, smart local energy systems and also low carbon policy objectives.

Anonymization of distribution feeder data using statistical distribution and parameter estimation approach

Distribution networks are undergoing a transition due to the rapid increase in distributed energy resources (DERs). Concerns over revealing critical infrastructure information and breaching consumer privacy have significantly hindered their development. Many applications that require data sharing are still impractical due to the lack of sufficient datasets, privacy concerns, and data access problems. To address these issues, a statistical distribution approach for parameter estimation is proposed. The statistical patterns of real distribution feeders are examined by accessing the confidential database of a local distribution network service provider (DNSP). An algorithm based on the Maximum Likelihood Estimate (MLE) is applied to estimate the statistical distribution parameters that represent the actual data. Then, these statistical distribution parameters are used to generate anonymized datasets that are realistic. A Kolmogorov–Smirnov (K-S) test is conducted to confirm the effectiveness of anonymized datasets, and results are compared with the actual feeder datasets. Validation is carried out with existing methods and comparisons are shown on the different portions of the datasets (25 percent, 50 percent, 75 percent, and 100 percent). The comparison results indicate superior performance over traditional methods, with a performance improvement ranging from 1 to 13 percent. The practical application of the method is demonstrated on the IEEE 123-node test feeder. The method achieves consistent results on voltage profiles, with a maximum difference of 0.420 percent between actual and anonymized datasets.

Steady-State Analysis of Electrical Networks in Pandapower Software: Computational Performances of Newton–Raphson, Newton–Raphson with Iwamoto Multiplier, and Gauss–Seidel Methods

At the core of every system for the efficient control of the network steady-state operation is the AC-power-flow problem solver. For local distribution networks to continue to operate effectively, it is necessary to use the most powerful and numerically stable AC-power-flow problem solvers within the software that controls the power flows in these networks. This communication presents the results of analyses of the computational performance and stability of three methods for solving the AC-power-flow problem. Specifically, this communication compares the robustness and speed of execution of the Gauss–Seidel (G–S), Newton–Raphson (N–R), and Newton–Raphson method with Iwamoto multipliers (N–R–I), which were tested in open-source pandapower software using a meshed electrical network model of various topologies. The test results show that the pandapower implementations of the N–R method and the N–R–I method are significantly more robust and faster than the G–S method, regardless of the network topology. In addition, a generalized Python interface between the pandapower and the SciPy package was implemented and tested, and results show that the hybrid Powell, Levenberg–Marquardt, and Krylov methods, a quasilinearization algorithm, and the continuous Newton method can sometimes achieve better results than the classical N–R method.

Designing the drone based end-to-end local supply chain distribution network

People in rural areas suffer due to lack of proper health care specifically during the emergency condition. Ontime delivery of emergency lifesaving medicine at the remote area is a one of the major concerns and one of the major reasons for this cause is the negligence and lack of proper transportation and road infrastructure. In this paper we have proposed a mixed integer non-linear programming (MINLP) model that is based on drone delivery for end-to-end local supply chain distribution network to ensure the fastest possible delivery of lifesaving medicine at the remote area. Moreover, we have used the Dijkstra algorithm to find the shortest path to deliver the lifesaving medicine at the patient home location using drone. The objective of this paper is to design an end-to-end local supply chain network to minimize the total delivery lead time of the lifesaving medicines under emergencies conditions. Also, the proposed MINLP model help to select the optimal healthcare facility location to minimize the total delivery lead time.

DG Locational Incremental Contribution to Grid Supply Level

Due to decarbonisation and decentralisation of energy sectors, the rise of distributed generation (DG) will modify generation and demand patterns at grid supply points (GSPs), where the interface between distribution and transmission systems takes place. With the increasing penetration of such devices, methodologies able to evaluate its contribution to both local distribution network and transmission system become crucial. This paper proposes an analytical method to evaluate the DG locational incremental contribution (LIC) to the interface with the transmission grid. Accordingly, the original model of the UK engineering recommendation P2 is enhanced by studying the impacts from high-voltage distribution networks (i.e. ≤ 132 kV) under normal and contingent conditions. This approach enables a more accurate network security assessment, especially when considering contingencies such as distribution system faults. To illustrate the proposed method, the original P2 model is compared against different enhanced approaches on three basic distribution networks, followed by a case study and a sensitivity analysis on a revised IEEE 14-bus GSP system. The proposed LIC method produces results that assess a wider range of conditions including DG penetration, concentration, and system reliability. Furthermore, it provides an increased DG visibility for transmission planning and operation.

Inka and Local Ceramic Production and Distribution Networks: A View from the Chinchaysuyo and Colesuyo

Inka and Local Ceramic Production and Distribution Networks: A View from the Chinchaysuyo and Colesuyo

Simulation of hybrid electrical vehicle charging station in multimode operation

The use of electric vehicles is growing very rapidly, and more and more people are switching to electric vehicles as the problem of air pollution has become a concern in most parts of the world. In addition, the spike in fuel prices around the world has prompted people to opt for an alternative vehicle option other than conventional Internal Combustion Engine (ICE) vehicles. But as the number of electric vehicles increases, the need to install charging stations on a very large scale also increases. The main problem with conventional grid-based charging stations is that they increase the load on the main grid and affect the power quality of the local distribution network. This paper discusses the modeling and simulation of a hybrid electric vehicle charging station operating in multi-mode (i.e., grid-connected or Grid Power Connected Mode (GPCM) and solar-powered or Solar Power Connected Mode (SPCM). The Electric Vehicle (EV) charge controller automatically switches between GPCM and SPCM. With this hybrid electric vehicle charging station model, renewable energy can be integrated with the main grid to improve the efficiency and reliability of the electric vehicle charging station, so the Electric Vehicle Charging Station (EVCS) hybrid model can help to expand the electric vehicle charging network on a large scale. The simulation was performed using MATLAB 2016.

Distribution grid impacts of electric vehicles: A California case study

SummaryCalifornia has adopted a substantial number of electric vehicles over the last decade but there are many challenges associated with the electrification of vehicles, including how they interact with the electricity grid. We employ real-world feeder circuit level data in California from PG&E to measure the capacity of local feeders. We model the adoption of electric vehicles down to the census block and take advantage of real-world vehicle charging data to simulate the future loading on circuits throughout Northern California. In our highest adoption scenario of 6 million electric vehicles in California, we find that across PG&E's service territory, 443 circuits will require upgrades (nearly 20% of all circuits) and merely 88 of these feeders have planned upgrades in the future. The costs of these feeders are an essential part of a utility's planning process, and this work speaks to the importance of electric vehicles on local distribution networks.

Emergent virtual networks amid emergency: insights from a case study

ABSTRACT In the aftermath of catastrophic events, problems always arise in the supply of goods in places affected by the emergency. During the early stages of the COVID-19 pandemic, the shortage of Personal Protective Equipment (PPE) created problems, especially in the healthcare sector, contributing to the uncontrolled spread of the virus. This paper presents a case in which the emergence of a voluntary local production and distribution network based on 3D printing technology played an important role in compensating for the lack of PPE. From the case analysed, we compare the core characteristics of the emergent virtual networks against the features of well-established supply chains models to systematize relevant differences and common traits. This research contributes to defining, developing, and scoping the concept of emergent supply chains and illustrates how such networks can constitute an essential first response to the lack of materials and goods in emergency contexts.

Remaking the regulatory model? Taking stock of ten years of customer engagement in Britain’s energy networks

Over the past decade, a concerted effort has been made in Britain to encourage and incentivise regulated energy network companies to engage directly with their customers through a process known as customer engagement (CE). Drawing on a series of semi-structured interviews and document analysis, the paper tracks the processes of implementing CE within regulation from 2010 to 2020. Given its increasing prominence in the regulatory framework for energy networks, the paper examines how various stakeholders involved in the regulatory process have experienced it and evaluate its importance. Based on this analysis we discuss what lessons can be learned as the challenge of transitioning to more active and flexible local and regional energy distribution networks is faced. We identify key challenges of moving from an experimental phase and embedding CE in the mainstream regulatory framework.

Decentralized blockchain-based peer-to-peer energy-backed token trading for active prosumers

This paper designs and models a fully decentralized peer-to-peer (P2P) energy token market for small-scale prosumers using blockchain technology in a smart grid environment in the presence of the demand response (DR) program and demurrage mechanism. As the market players, prosumers in the local distribution network are considered in two groups, producers (sellers) and consumers (buyers). Using smart contracts, all sellers and buyers in the proposed market can engage in bilateral energy token transactions (P2P) with each other under an agreed price and with the retail market at a certain price. Furthermore, the local consumers can participate in price-based DR programs and shift their consuming load to the periods with high local generation. Demurrage mechanism is applied to avoid energy token accumulation and enhance attraction for local transactions. With demurrage in place, the redemption value of energy-backed tokens reduces with time. A fully decentralized approach called the primal-dual sub-gradient method is developed to clear this fully decentralized energy market in the presence of DR programs and demurrage. The proposed market-clearing scheme guarantees the global and feasible solution without requiring the players' private information. Numerical studies demonstrated the feasibility and effectiveness of the proposed energy token market and the decentralized approach for its clearing.

Prospects of photovoltaic rooftops, walls and windows at a city to building scale

Many cities across the world are committing to deep decarbonisation efforts. While solar photovoltaics (PV) will play a critical role in this pursuit, the role of rooftop and facade-integrated PVs within the urban landscape is yet to be fully understood. This work presents an analysis into the solar energy harvesting potential of PVs integrated as building rooftops, walls, and windows at various spatial resolutions that range from city to building scale within the City of Melbourne, Australia, as a contemporary case study. It further investigates the relationship between calculated electricity production from such PVs with the urban morphology, seasonal variation and the measured electricity consumption by the local distribution network service providers. The results indicate that PV rooftops are responsible for the largest share of the city’s solar energy potential. However, for individual blocks with high densities of high-rise and glazed buildings, it is shown that the PV potential from windows becomes more prominent. The technical workflow presented here will enable different cities to facilitate decision-making on the PV implementation in urban environments.