Distribution System Operators Research Articles

Efficient reduction of power losses by allocating various DG types using the ZOA algorithm

The continuous challenge of ensuring energy supply is a significant concern. Traditionally, utilities have addressed increasing load demands by building new central power plants or expanding existing ones. However, these methods are time-consuming and costly, providing only short-term solutions. Additionally, power plants are often far from load centers, resulting in higher power losses during long-distance transmission. The integration of distributed generation (DG), characterized by smaller scale and lower capital costs, with nearby consumers can effectively address these challenges. Due to the significant influence of DG penetration and their specific locations on the distribution system's performance, this study offers a novel Zebra Optimization Algorithm (ZOA). The suggested ZOA is used to optimize the capacity and position of various DG units connected to a radial distribution system to reduce power losses and study the stability of the system after DG allocation using the Voltage Stability Index (VSI). The evaluation is conducted using the IEEE 33-bus test system, considering various scenarios including single and multiple DGs of different types. The results demonstrate that in the best scenario, the ZOA can reduce losses by up to 94.25 % and improve the VSI from 0.69643 to 0.9605. These findings highlight the superior performance of the ZOA over other techniques in optimizing DG placement and sizing for power system performance.

A multi-stage techno-economic model for harnessing flexibility from IoT-enabled appliances and smart charging systems: Developing a competitive local flexibility market using Stackelberg game theory

The increasing integration of renewable energy sources with power systems has led to greater uncertainties, heightening the need for more flexible services. Demand-side resources can provide significant flexibility cost-effectively, making it crucial to design new business models to harness their flexible capacities. Hence, this paper introduces a three-stage techno-economic framework designed to enhance the exploitation of flexible capacities from demand-side resources such as Internet-of-Things (IoT)-Enabled Appliances (IEAs), Battery-Integrated Rooftop Solar Panels (BIRSPs), and Electric Vehicle (EV) smart charging systems in the local flexibility market. The proposed framework operates in three stages. First, smart homes with IEAs, BIRSPs, and smart charging systems assess their flexibility and report it to their Microgrid (MG) operators. Next, MG operators optimize strategies to maximize market returns and report capacities to the Distribution System Operator (DSO). Finally, the DSO manages flexibility transactions based on MG inputs. A Stackelberg game theory model using a gradient-based method updates the coupling variables between market parties, ensuring convergence in the second and third stages within a decentralized space with limited information sharing. Implemented on a modified IEEE 69-node distribution system, the model fully utilizes the potential of smart homes, including IEAs, BIRSPs, and smart charging systems in the local flexibility market. It reduces the Upstream Network (UN) share in the local flexibility market by 56.86% and decreases DSO costs for energy balancing by 22.36%.

TSO-DSO interface for Net Zero: the German case of 50Hertz and its DSO neighbour TEN Thüringer Energienetz*

As Germany advances towards its energy transition goals, the imperative to expand and restructure its power grid infrastructure becomes increasingly evident. The current infrastructure lacks the capacity to meet future demands, highlighting the pressing need for action. Escalating challenges related to system security and grid reliability underscore the critical importance of fostering close coordination between Distribution System Operators (DSOs) and Transmission System Operators (TSOs). Collaboration is particularly crucial in control areas such as for instance 50Hertz’s in north-eastern Germany, where efficient management of energy fluctuations is essential for the successful transition to high renewable energy usage. Regulatory strategies aimed at facilitating this transition must prioritize a strong collaboration between DSOs and TSOs necessary for stability, optimizing operations, and securing the network. This article is intended to illustrate how a regulatory framework for such TSO-DSO cooperation in north-eastern and eastern Germany for congestion management could be necessary, in accordance with the next grid development plans. Regulatory gaps associated with such interface will be identified and policy recommendations derived from them will address the challenges and opportunities linked to congestion management and the utilization of smart grid technologies.

Enhancing fault-clearing algorithm for renewable-energy-based distribution systems using artificial neural networks

Abstract Integrating small and large-scale photovoltaic (PV) solar systems into electrical distribution systems has become mandatory due to increased electricity bills and the concern for limiting greenhouse gases. However, the reliable and efficient operation of PV-based distribution systems can be confronted by the intermittence and high variability of solar sources and their consequential faults. In this regard, this article suggests a moderated fault-clearing strategy based on the incremental conductance–maximum power point tracking (IC–MPPT) technique and artificial neural networks (ANNs) to enhance fault detection, localization, and restoration processes in PV-based distribution systems. The proposed strategy leverages IC–MPPT to ensure optimal power generation from the PV solar system, even in the presence of faults. By tracking the maximum power point, the algorithm maintains the performance of the system and mitigates against the impact of faults on the output power. Furthermore, an ANN is employed to improve fault detection and localization accuracy. The developed ANN-based moderated fault-clearing strategy is trained using historical data and fault scenarios, enabling it to recognize fault patterns and make informed decisions through extensive simulations and comparisons with traditional fault-clearing methods. To accomplish this study, benchmarks in PV-based distribution systems are constructed and employed using the MATLAB®/Simulink® software package. Moreover, to validate the efficacy of the developed ANN-based moderated fault-clearing strategy, a real case study of a 1-MW PV-based distribution system in an industrial field located in Giza governorate, Egypt, is tested and investigated. The obtained results demonstrate the effectiveness of the IC–MPPT and ANN-based moderated fault-clearing strategy in achieving faster fault detection, precise fault localization, and efficient restoration in PV solar-based distribution systems while preserving maximum power extraction under small and large system disturbances. Furthermore, IC–MPPT based on an ANN achieves an average power of 98.556 kW and 299.632 kWh energy availability, whereas the IC–MPPT based on a proportional–integral controller achieves 95.7996 kW and 283.4036 kWh, and the classic perturb-and-observe MPPT algorithm achieves 92.2657 kW and 276.8014 kWh.

Operationalizing the Circular Economy—A Longitudinal Study on Sustained Circular Action

Circularity is becoming increasingly important for Distribution System Operators (DSOs) as their infrastructure ages and needs replacement, alongside compliance with stringent environmental regulations like the Corporate Sustainability Reporting Directive (CSRD). However, implementing circular economy (CE) practices is challenging due to the fragmented nature of the current CE landscape and its limited interaction with practical application. A longitudinal case study at the Dutch DSO, Liander, focusing on the circularity of distribution transformers, was conducted to generate prescriptive knowledge on operationalizing circularity. This resulted in the formulation of six design propositions for circular action that suggest to (1) initiate small-scale circularity experiments; (2) involve technical and strategic experts; (3) synergize circularity with more urgent, primary goals; (4) translate circular initiatives bottom-up and top-down; (5) collaborate with other DSOs; and (6) create multidisciplinary teams. The propositions suggest to situationally select interventions and build upon the outcomes of previous interventions in order to incrementally contribute to circular change. Other DSOs could use these propositions to optimize their strategy toward circular action. Additionally, the findings contribute to advancing scientific knowledge to implementable actions in order to initiate and sustain circular change.

Hybrid strategy of flexibility regulation and economic energy management in the power system including renewable energy hubs based on coordination of transmission and distribution system operators

Energy management of energy hubs in the power system impacts both transmission and distribution networks and their operations. Hence, to enhance efficiency, there should be bilateral coordination between distribution and transmission networks. Moreover, thanks to including power sources, storage, and responsive loads, hubs can earn financial benefits from the energy and ancillary services market. Therefore, this paper presents the operation of distribution and transmission networks in the presence of flexible-renewable energy hubs based on transmission system operator (TSO)-distribution system operator (DSO) coordination according to the market clearing price modeling in energy and flexibility markets. The proposed scheme minimizes the sum of the expected operating costs of the networks and hubs minus the expected flexibility profit of the hubs. The scheme is constrained to optimal power flow equations of the networks, flexibility limit of the networks, and flexibility-operation model of renewable energy hubs located in transmission and distribution networks. The unscented transformation method is used to model the uncertainties of load, renewable sources, and stationary storage (aggregation of electric vehicles). Energy price and flexibility are among the dual variables of the problem. To simultaneously calculate these variables and the main variables of the problem, an integrated model of the suggested scheme based on the penalty function technique is extracted. Eventually, numerical results validate the capability of the scheme in enhancing the operation, economic, and flexibility status of the proposed scheme, in which renewable sources along with storage and responsive load in the energy hub can obtain 100 % flexibility conditions for the networks. They help enhance the economic and operation indices of distribution and transmission networks by about 26 %-44 % and 22 %-33 % compared to the case without hubs and renewable sources.

Impact of visibility limiting conditions on satellite and high-altitude platform quantum key distribution links.

Satellite and aerial platforms are critical in the deployment of global quantum communications networks. Currently, there remain significant challenges including operation during daytime and robustness to visibility limiting conditions. In this work we investigate, through simulation, the impact of visibility limiting conditions on low-Earth orbit CubeSat dimensioned satellites, small satellites and high-altitude platform implementations. Three different operational wavelengths were considered: currently used near-infrared (at 850 nm); next-generation short-wave infrared (at 1550 nm); and a candidate longer wavelength (at 2133 nm). We present channel attenuation and consider quantum key distribution (QKD) system performance parameters. Results indicate that the "best wavelength" for an implementation depends on the minimum visibility rated and the single-photon detector technology utilized. In the cases where tolerated meteorological visibility is short, 1550 nm and 2133 nm wavelengths provide better performance. In cases when the visibility is long, the operational wavelength of 850 nm provides better QKD system performance.

Calculation Methodology to Determine Electricity Distribution Tariffs Using an Approach Based on Cost Causation

The cost reflectivity of electricity distribution network tariffs has been debated in several countries, and various ways to enhance it have been investigated in recent years. However, the recent academic literature regarding the approach based on cost causation has a clear gap because no case studies show how distribution network tariffs can be determined in practice for large customer groups. This article offers a calculation methodology to determine distribution network tariffs based on cost causation along with a case study where unit prices are determined for the tariff structures still widely used today using the data for two separate network areas being operated by two Finnish distribution system operators (DSOs) in an unbundled electricity market environment. The results of the case study show that the total differences between the target and the realized turnovers in both investigated networks are smaller than 1%, which means almost a full cost recovery. In addition to traditional tariff structures, the proposed calculation methodology can also be modified to design and determine other pricing schemes. The need for systematic calculation processes is growing to improve the cost reflectivity of present tariffs and adapt to the needs of the evolving operating environment, novel tariff structures, and new emerging customer groups.

Development of a conceptual model for management of technological losses of electricity in distribution networks 150-0.38 kV

The work developed a conceptual model of the process of managing the technological costs of electrical energy in 150-0.38kV distribution networks. The relevance and necessity of developing a conceptual model of the process of managing the technological costs of electricity, which is carried out in relation to the system of distribution of electrical energy (or the electrical distribution system) as a whole, including distribution electrical networks of 150-0.38 kV, is analyzed. The paper proposes a conceptual decomposition, considers the description and formalization of the power distribution system management process based on the criterion of reducing the technological costs of electricity. The proposed conceptual model describes the process of managing the technological costs of electricity in the power distribution system, as a process of regular improvement (optimization) of the functioning of the power distribution system and allows further optimization and automation of the process of managing the technological costs of electricity in the power distribution system, in order to achieve higher levels of energy efficiency of its functioning. It is shown that this model can be used to solve the tasks of not only strategic and tactical management (in terms of years and months) when forming development plans and current operation of distribution systems, but also operational optimization of technological costs of electricity at the pace of the process. Provided that the appropriate software is developed (including the forecasting of power distribution system modes and external environmental influences), the system for managing the technological costs of electrical energy is represented by three control loops that correspond to the stages of its development. Processes and information links between them are shown for each control loop. Each process in the conceptual model of the management of technological costs of electric energy has its own formal representation through generalized functional dependencies, and the information links between the processes correspond to the arguments and values of these functions. The conceptual model describes the process of managing the technological costs of electrical energy in the power distribution system as a process of regular improvement (optimization) of its functioning through increasing its energy efficiency.

Enhanced distribution system performance through optimal placement of hybrid dynamic voltage restorer

Enhanced distribution system performance through optimal placement of hybrid dynamic voltage restorer

The impact of metering methods on collective self-consumption: Insights from multi-dwelling buildings in Finland

Globally, legislative reforms have significantly promoted the adoption of solar photovoltaic systems. In many European countries, updated legislation encourages the formation of energy communities and collective self-consumption in residential buildings. This study investigates the financial viability of solar photovoltaic systems in Finnish multi-dwelling buildings, focusing on the impact of recent legislative enhancements supporting collective self-consumption through virtual net-metering, known as the credit calculation model. By analyzing hourly consumption data from two properties in 2018 and 2020, and incorporating simulated photovoltaic production with electricity market prices, our findings highlight the advantages of virtual net-metering. Self-consumption ratios increased from 15% to 38 %, and annual revenue improved by 10 EUR/kWp to 29 EUR/kWp. Comparing the credit calculation model with behind-the-meter approaches using joint electricity subscriptions revealed self-consumption ratio differences of 5 % to 15 % for identical system sizes. Additionally, electricity purchasing cost savings of 16 % to 19 % were identified with behind-the-meter, increasing further compared to costs from other Finnish distribution system operators. This underscores the economic benefits of such arrangements and highlights potential savings across different regional pricing models. These insights demonstrate the financial benefits of collective self-consumption and joint electricity subscriptions in multi-dwelling contexts, signaling the need for extended research across diverse settings to validate these findings.

Maximizing social welfare in local flexibility markets by integrating the value of flexibility loss (VOFL)

The increasing integration of Renewable Energy Sources (RESs) poses challenges due to their unpredictable nature. To address these challenges, flexible Distributed Energy Resources (DERs), such as Distributed Generators (DGs), Flexible Loads (FLs), and Energy Storage Systems (ESSs), have emerged in distribution networks. This paper proposes a linear programming formulation for optimizing flexibility provision in the Local Flexibility Market (LFM) to maximize Social Welfare (SW), contrasting with existing literature. The concept of the Value of Flexibility Loss (VOFL) is introduced to enable the Distribution System Operator (DSO) to optimize flexibility procurement, ensuring economic profitability for both providers and consumers. Additionally, the DSO can interchange flexibility with the Transmission System Operator (TSO) based on economic incentives. Numerical results demonstrate the accuracy and efficiency of the proposed model.

Optimal allocation of solar photovoltaic distributed generation for performance enhancement of electrical distribution networks considering optimal volt‐var regulation under uncertainty and high load variation

AbstractThis article proposes an optimal placement and sizing of photovoltaic (PV) power systems based distributed generation (DG) in radial electrical distribution networks considering the capability of PV inverters to regulate the voltage by optimal injecting and absorbing reactive power at the point of common coupling (PCC) using honey badger algorithm (HBA), as a recent and efficient optimization algorithm to solve the complicated optimal allocation. Several objective functions are achieved for distribution system performance enhancement: minimizing the power loss and the voltage deviation index (VDI) and maximizing the voltage stability index (VSI). Based on historical data and probabilistic models, seasonal hourly solar irradiance, ambient temperature, and load variation curves have been modeled, which simultaneously consider the light, normal, and heavy load demand. The essential components of distribution power systems have been characterized. To investigate the validity of the proposed approach, IEEE 33 and IEEE 69 BUS radial distribution test systems have been considered for power flow (PF) analyses, where Newton's Raphson method has been applied to solve the PF issue. The simulation results of different numerical scenarios have shown the effectiveness and validity of the newly proposed method to solve the optimal allocation problem considering optimal volt‐var regulation control of PV inverters compared to several valid and robust optimization algorithms.

Dynamic assessment approach for intelligent power distribution systems based on runtime verification with requirements updates

The study aims to address the challenge of dynamic assessment in power systems by proposing a design scheme for an intelligent adaptive power distribution system based on runtime verification. The system architecture is built upon cloud–edge-end collaboration, enabling comprehensive monitoring and precise management of the power grid through coordinated efforts across different levels. Specifically, the study employs the adaptive observer approach, allowing dynamic adjustments to observers to reflect updates in requirements and ensure system reliability. This method covers both structural and parametric adjustments to specifications, including updating time protection conditions, updating events, and adding or removing responses. The results demonstrate that with the implementation of adaptive observers, the system becomes more flexible in responding to changes, significantly enhancing its level of efficiency. By employing dynamically changing verification specifications, the system achieves real-time and flexible verification. This research provides technical support for the safe, efficient, and reliable operation of electrical power distribution systems.

Improved Newton-Raphson method with simplified Jacobian matrix and optimized iteration rate for power flow calculation of power system

With high penetration of renewable energy and novel loads connected to the distribution network, the voltage fluctuation becomes more severe and frequent, which may cause over- and under-voltage. The distribution system operator should calculate the power flow and validate the state to optimize the distribution network. Power flow calculation is the solution to the multivariate nonlinear problem, and the Newton-Raphson method is an effective algorithm for solving nonlinear problems. However, calculating the Jacobian matrix is a crucial process of the Newton-Raphson method, which is time-consuming. Therefore, this paper proposed an improved Newton-Raphson method, which simplifies and decreases the iterations of the calculation process of the Jacobian matrix to improve the calculation rate. To verify the effectiveness of the proposed method, the power flow of the IEEE 33-node power distribution system is calculated by the improved Newton-Raphson method and the conventional Newton-Raphson method.

Intelligent alarm flood management for power systems

Alarm floods pose a challenge to the successful operation of transmission and distribution systems because the alarm rate is often higher than what operators can effectively manage. Such a high volume of alarms can distract operators from unrelated but relevant alarms that occurred during the flood. To mitigate this situation, we propose a method to group alarm floods into clusters and identify additional alarms that might be lost in the flood and ignored by the operator. To do so, three different clustering approaches are introduced and tested using historical alarm data from a transmission system operator (TSO). Importantly, the results are validated by the end user highlighting the applicability of the proposed alarm flood management tool in real world scenarios.

A multi-objective mixed integer linear programming approach for simultaneous optimization of cost and resilience of power distribution networks

In recent years, customers have experienced a significant increase in weather-related power outages. The power distribution network (PDN), a subset of the power system, in particular is more susceptible to extreme events. Therefore, ensuring the resilient and cost-effective operation of PDNs following extreme weather conditions poses a significant challenge for distribution network operators. This paper presents an approach for simultaneously optimizing the cost and load restoration for resilience enhancement of power distribution networks while determining the optimal positioning and generation levels of mobile emergency generators. The proposed method, in addition, employs a distribution network reconfiguration to improve the load restoration process, by optimally determining the status of switches. The multi-objective formulation involves the minimization of load shedding to increase the resilience of the system, while the other objective is formulated to minimize the cost of load restoration. A weighted sum method is employed to address the multi-objective mixed-integer linear programming (MILP) model. A set of non-dominated solutions determined using the proposed formulation provides opportunities to the distribution system operator in choosing a resilience improvement strategy according to the availability of the operational budget. The proposed model is implemented on 33-bus distribution system to validate the efficacy of the proposed model.

Projected Analysis of Fulfilling Pdam Clean Water Needs in Domestic Customers of Waginopo Village, Wangi-Wangi District, Wakatobi District

Clean water is a very vital need for society, to meet the needs for drinking water, bathing, cooking, washing and including industrial needs. The existence of clean water in an area is very important considering the very dynamic activities of society. In its implementation, the drinking water supply system in Waginopo Village has not been able to run smoothly. In fact, according to a temporary survey that has been carried out, PDAM water only flows once every 2 days, once a week and the maximum flow time is only 12 hours. The aim of this research is to calculate the amount of clean water needed for the service area of Waginopo Village, Wangi-Wangi District, Wakatobi Regency until 2033. In this research, not only numerical data will be collected, but also information about what the community desires regarding the performance of the clean water distribution system, so this research study approach uses a combination of quantitative and qualitative approaches. From the results of the analysis it can be said that the total water demand of PDAM Wakatobi Regency for the Waginopo Village service area in 2033 is 867,894 m3/year. Meanwhile, based on water demand in 2024, it is 592,737 m3/year. So the calculation results from 2024 to 2033 have increased.

Flexibility modeling for parking lots with multiple EV charging stations

The paper proposes an aggregated model that represents the flexibility potential of car parks equipped with multiple electric vehicle (EV) charging stations. The model is used in a stochastic optimization procedure to estimate in advance the maximum flexibility margins of the parking lot. The EV aggregator responsible for the charging stations offers intra-day ancillary services to the grid by specifying the possible margins within which the absorbed power can be varied, either up or down. These adjustments are made at the request of the distribution system operator, ensuring an appropriate level of EV charging. The effectiveness of the model is evaluated for parking lots with different numbers of charging stations and different daily profile forecasts of the number of EV arrivals and departures.

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control (nmpc) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework’s effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.