Distribution System Operators Research Articles

Modeling of high uncertainty photovoltaic generation in quasi dynamic power flow on distribution systems: A case study in Java Island, Indonesia

Integrating uncertainties associated with photovoltaic (PV) generation is an important aspect used to ensure the planning and operation of power distribution systems. Therefore, this research proposed an uncertainty model for PV generation by combining the methods of change point detection, cyclic k-means clustering (KMC), Monte Carlo simulation (MCS) with freedman diaconis estimator (FDE), and KMC with soft-dynamic time warping (DTW). Firstly, a seasonal split was performed using change point detection techniques and cyclic KMC to identify shifts in global horizontal irradiance (GHI) points. Secondly, the uncertainty of the GHI was generated using MCS for each season and the FDE method to optimize the number of bins of the data distribution. Finally, the PV generation curve from MCS was simplified through KMC with the soft-DTW metric, which facilitated a more straightforward representation of a PV profile. The impact of PV profile integration on quasi-dynamic power flow was tested on an IEEE 33 Bus system. The voltage profile on the feeder significantly impacted the PV integration, specifically during hours when high PV power is produced. For instance, at 11:00 a.m., voltage values on buses 18, 17, and 33 increased from 0.933, 0.934, and 0.935, respectively, to 0.982, 0.980, and 0.972. Similarly, with the value of power losses, the greater the PV power profile produced at a certain hour, the smaller the losses generated. The experimental results of the uncertainties PV model proposed in this research indicated that changes in electrical parameters change over time according to the input PV power profile produced.

A temporal and spatial electric vehicle charging optimization scheme with DSO-EVA coordination framework

Burdens of increasing penetration of electric vehicles (EVs) on distribution systems have attracted wide attention to the research of EV charging coordination. Nevertheless, existing coordination lacks the joint consideration of the temporal-spatial flexibility of EVs, which could reduce load fluctuations when meeting the EV charging demands. Moreover, a thorough investigation is required for the coordination of the benefits to the distribution system operator (DSO), EV aggregator (EVA), and EVs. In this paper, a novel EV charging scheme considering the temporal-spatial features of EVs is proposed, achieving the coordination of DSO, EVA, and EVs in two steps. First, a mixed-integer second-order cone programming (MISOCP)-based EV charging schedule is developed for DSO. Second, the temporal-spatial features of EVs are exploited by EVA to track the charging schedule. Specifically, a dynamic charging price mechanism based on active power margin is proposed for public charging facilities and a specific load regulation is designed for private charging facilities. On this basis, the modified adaptive multi-objective particle swarm optimization (AMOPSO) algorithm is proposed, including adaptive flight parameter adjustment and termination mechanisms. Case studies demonstrate the proposed strategy can attenuate load variance and raise EVA revenue. Further, the impact analysis of penalty price and the price elasticity of electricity demand can provide references for stable distribution network operation, higher EVA revenue, and charging cost reduction.

P2P local market concept with dynamic network usage tariff via asset enablement – Horizon2020 project demo experiences

With the growth of renewables, the increased interconnection of European grids, the development of local energy initiatives, and the specific requirements on transmission system operator (TSO) – distribution system operator (DSO) cooperation as set forth in the different Network Codes and Guidelines, TSOs and DSOs face new challenges that will require greater coordination. The European Commission adopted legislative proposals on the energy market that promote cooperation among network operators as they procure balancing and other ancillary services and provide congestion management. Therefore, this creates the need for a specific project such as the H2020 INTERRFACE project, having the greater coordination between TSOs and DSOs as its core objective. In this project, one of the demonstrations is a local asset-enabled energy market to provide data-driven, simulation-based results, with a realistic market setting. There the transactions beneficial for the distribution grid are facilitated via dynamic pricing (DNUT – dynamic network usage tariff). In the demonstration of a local market that runs based on data, provided from 3 sites (2 Hungarian, 1 Slovenian), local distribution system operators are involved to provide grid and consumption/production data. This paper discusses the first results from one demonstration site, which contribute to the development of local P2P markets. It also facilitates the introduction of grid calculation based dynamic tariffs by providing practical results from the cooperation of research entities and DSOs in the H2020 INTERRFACE project.

Expanding the Role of DSOs in Establishing Flexible Local Markets: A Brokerage Perspective

As more distributed energy resources are deployed into distribution networks, supply and demand matching between prosumers becomes a new challenge for distribution system operators (DSOs) due to the intermittency of DERs. Recent studies begin to expand the responsibilities of DSOs towards local generation and consumption optimization, such as establishing a flexible local market. However, the difficulty of boosting local power exchange while reducing operation costs still remains unsolved. In this paper, we propose a new way of power trading management for DSOs from a brokerage perspective. Specifically, DSOs endeavor to coordinate prosumers in the local market by setting a fair transactive price as incentive signals. Meanwhile, to compensate for the operation cost (e.g., power line loss), DSOs need to charge commission. We investigate how to compute the optimal transactive price in a privacy-preserving way by using a distributed algorithm and set a fair service fee, which attracts more power transactions in the local market as well as reduces the operation cost of DSOs. Moreover, to accelerate the distributed algorithm, we derive an optimal transactive price updating rule for DSOs, and the closed-form expression of the optimal strategy for each prosumer with respect to the transactive price. Numerical results on Southern California Edison 56-bus feeder and IEEE 123-node test feeder show that the proposed power trading management for DSOs from a brokerage perspective leads to a TRIPLE win. With the proposed mechanism, the prosumers' payoffs largely increase by as much as 192.85%. Then, the prosumers are more willing to exchange power locally, which significantly reduces the increasing transmission burden in transmission networks of power systems. Moreover, DSOs obtain compensation by charging a service commission and reduce their operating costs.

Distributed Energy Resource and Energy Storage Investment for Enhancing Flexibility Under a TSO-DSO Coordination Framework

This paper presents a distributed energy resource and energy storage investment method under a coordination framework between transmission system operators (TSOs) and distribution system operators (DSOs), which simultaneously addresses two main aspects of the flexibility aggregation of DSOs, i.e., flexibility enhancement and dynamic flexibility provision. First, to characterize the key flexibility features of power distribution networks, a multi-port multi-period feasible region formulation is designed using the robust optimization conception while avoiding over-parameterized formulations that require extensive information exchange. Second, a two-stage robust planning model is built to enhance distribution system flexibility by maximizing the volume of feasible regions, in which the uncertainty of dispatch instructions is modeled as a decision-dependent uncertainty (DDU) set and the worst realization is identified for the operational security evaluation. The proposed two-stage robust planning model is solved via a customized column-and-constraint generation algorithm. Finally, a distributed framework for TSO-DSO coordination is proposed to enable the dynamic adjustment of feasible region provision of DSO, given the TSO’s preference, which is then solved by a DDU-based two-stage robust extension of the alternating direction method of multipliers algorithm. Numerical results verify the effectiveness of our proposed models and the scalability of the associated algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The increasing integration of renewable energy resources has stimulated the need for aggregated flexibility provided by power distribution networks (PDNs). However, there are three challenges: i) using the currently feasible region formulation of PDN requires extensive information exchange with the transmission system operator (TSO), thus not compatible with the current structure. ii) the optimal investment of various assets to leverage their cost-effectiveness in feasible region enhancement needs to be addressed. iii) lack of a proper coordination mechanism between TSO and distribution system operators (DSOs) to facilitate the optimal feasible region provision and leverage the spatiotemporal flexibility. To address the above challenges, we design an easy-to-implement feasible region formulation to characterize the key flexibility features of PDNs. Upon this, we propose a feasible region enhancement planning method based on an extended two-stage robust model to address the decision-dependent uncertainty. Furthermore, we facilitate the optimal feasible region provision through the TSO-DSO coordination process in a distributed manner. The numerical results show that the proposed planning method and coordination mechanism could effectively achieve optimal flexibility enhancement and dynamic flexibility provision. In practical application, our proposed planning method can be readily implemented with advanced analytical tools. The coordination mechanism is also compatible with the current TSO-DSO structure and can be easily integrated into it.

Distribution System Operator (DSO) Functions in South Korea—Part I: Development, Practical Obstacles, and Future Work

This paper presents our initial research findings on distribution system operator (DSO) functions in South Korea. The project team includes the Korean Electric Power Corporation, which is the only public utility company in South Korea. The planned development is based on a real distribution network and real‐world environments. The project encompasses DSO–transmission system operator coordination and management of real‐time distribution network congestion; this paper focuses on the latter aspect. For real‐time congestion management, algorithms that handle all steps from database analysis to data export, including data preprocessing, topological configuration, power flow calculation, sensitivity analysis, and derivation of solutions to congestion, are developed. The distribution system equipment database of Korean Electric Power Corporation is used to develop a network congestion management system. When examining the database, many gaps between the theoretical and practical environments were found which are introduced in this paper. A practical distribution network database for South Korea is developed to narrow these gaps and to implement practical congestion management techniques. The remaining problems are introduced as future works.

Experimental measurements of the new gas smart meters’ current discharges to suggest improvement solutions for power supply battery life extension

Several reasons justified introducing the smart metering concept in the gas distribution sector and supporting its digitalization. Specifically, among their functionalities, the new smart meters would improve the ability to identify abnormal consumption or malfunctions in the gas grid or at customers’ appliances as soon as possible, improving the gas distribution system’s safety performance. The installation and operation of gas smart meters result in a significant amount of data to be managed. Specifically, gas consumption, the supply pressure, and information about the status of the device, such as the events that occurred, are some of the data communicated daily to the gas Distribution System Operators (DSOs). However, despite the advantages, some drawbacks were first experienced by the DSOs, requiring unplanned intervention and increasing the operative costs. Among these, the discharge of the batteries sooner than expected increases the operative costs. In fact, due to ATEX safety aspects, the smart meters are not directly connected to the electric grid but they are powered by batteries that have to be replaced only by authorized personnel. The present paper reports the preliminary results obtained during an experimental campaign to investigate the impact of data communication on the battery lifetime. Specifically, four communication protocols that differ in the number of data strings and the communication frequency were compared, and preliminary conclusions were given.

Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations With PowerModelsITD.jl

Conventional electric power systems are composed of different unidirectional power flow stages of generation, transmission, and distribution, managed independently by transmission system and distribution system operators. However, as distribution systems increase in complexity due to the integration of distributed energy resources, coordination between transmission and distribution networks will be imperative for the optimal operation of the power grid. However, coupling models and formulations between transmission and distribution is non-trivial, in particular due to the common practice of modeling transmission systems as single-phase, and distribution systems as multi-conductor phase-unbalanced. To enable the rapid prototyping of power flow formulations, in particular in the modeling of the boundary conditions between these two seemingly incompatible data models, we introduce PowerModelsITD.jl, a free, open-source toolkit written in Julia for integrated transmission-distribution (ITD) optimization that leverages mature optimization libraries from the InfrastructureModels.jl-ecosystem. The primary objective of the proposed framework is to provide baseline implementations of steady-state ITD optimization problems, while providing a common platform for the evaluation of emerging formulations and optimization problems. In this work, we introduce the nonlinear formulations currently supported in PowerModelsITD.jl, which include AC-polar, AC-rectangular, current-voltage, and a linear network transportation model. Results are validated using combinations of IEEE transmission and distribution networks.

Renewable energy integration and distributed generation in Kosovo: Challenges and solutions for enhanced energy quality

&lt;abstract&gt; &lt;p&gt;The growing demand for energy, driven by rapid economic development, necessitates higher electricity consumption. However, conventional energy systems relying on fossil fuels present environmental challenges, prompting a shift towards renewable energy sources. In Kosovo, coal-fired power plants dominate electricity production, highlighting the need for cleaner alternatives. Worldwide efforts are underway to increase the efficiency of photovoltaic systems using sustainable materials, essential for ecological and human health. Solar and wind energy are emerging as sustainable alternatives to traditional fossil fuels. However, global concerns about energy security and environmental sustainability are driving countries to prioritize renewable energy development.&lt;/p&gt; &lt;p&gt;In Kosovo, the integration of renewable energy sources, such as wind and solar energy, is progressing rapidly. However, challenges such as voltage stability and power losses need to be addressed. Distributed generation offers a solution by increasing energy reliability and reducing greenhouse gas emissions. Further research is needed to assess the technical, economic, and environmental implications of integrating renewable resources into Kosovo's energy system, focusing on power quality, system reliability, and voltage stability. The research focused on the eastern region of the country, operating at the 110 kV substation level. Challenges in energy quality arise due to the lack of 400 kV supply and the continuous increase in energy consumption, especially in the Gjilan area. This paper investigated integrating renewable energy, especially wind and solar sources, into the medium- and long-term plans at the Gjilan 5 substation to enhance energy quality in the area. Successful integration requires detailed analysis of energy flows, considering the impact of photovoltaics (PVs) on distribution system operation and stability. To simulate and analyze the effects of renewables on the transmission system, voltage profile, and power losses, a case study was conducted using ETAP software. The simulation results present a comparison between scenarios before and after integrating renewable systems to improve energy quality in the identified area.&lt;/p&gt; &lt;/abstract&gt;

Optimizing the power quality of the MV distribution network in fault condition based on D-STATCOM in accordance with the Moroccan Grid Code requirements

In this work, we present a novel method concerning a D-STATCOM integration to the Moroccan electrical distribution network, which is not yet adopted by national DSO’s (Distribution system Operator), the device is implemented at the PCC (Point of common Coupling) of a grid connected PV power plant, which is a typical case of the increasing penetration of renewable generators in the national electrical network. The device is proposed to compensate for voltage fluctuation and the dynamic support of grid voltage in the event of disturbances or the failure of renewable generators especially in context of the increasing integration of these sources. The control strategy is tuned to achieve performance constraints imposed by the national Grid Code. The proposed system overcomes network uncertainties and grid disturbances and significantly improves the power quality at the point of common connection PCC while absorbing and providing reactive power to the network in an acceptable reversing time due to voltage sags and swells and mitigating voltage flicker. The considered D-STATCOM (Distribution Static Compensator) was able to ride through grid faults in most cases which is necessary to achieve LVRT (Low voltage Ride through) and dynamic voltage support requirements. The results of the simulation are compared to the technical requirements according to the Moroccan Grid code and show good results in simulation while respecting the technical limits imposed by local regulations.

Artificial intelligence-powered energy community management for developing renewable energy systems in smart homes

The increase in demand due to scientific innovation and economic expansion raises challenges linked to environmental impact and sustainable market development. This study analyzes the role played by Peer-to-Peer (P2P) energy trading in system operation. Several case studies with four distinct prosumer models, each fitted with diverse Energy Storage Systems (ESS), photovoltaic (PV) systems, and responsive demand technologies such as Electric Vehicles (EV), are examined. An economic analysis is conducted using the developed interface. An energy management system establishes a dynamic market framework, enabling energy trading via P2P market operators and distribution system operators. The implemented trading platform is chosen depending on pricing variations across different time intervals for home models. The P2P energy trading system employs mathematical modeling via deep learning to achieve an optimal solution that minimizes costs. The study uses other domestic models and optimization techniques to explore the amount of energy traded across households and timeframes. Additionally, it investigates the accomplishment of two-way energy transfer in electric cars, the importance of energy storage and photovoltaic systems, and various housing scenarios concerning peer-to-peer energy trading. Additionally, the system's advantages are demonstrated to participants beforehand by validating and presenting data through an input and output system that accepts these instances.

Using Digital Twins to Improve Pumping and Distribution System Operations

Key TakeawaysDigital twins of water systems can give utility staff the real‐time, detailed analyses they need to manage the complexities of pumping and distribution operations.Among others, the benefits yielded by investing in digital twins include cost savings, improved staff efficiency, optimal equipment operation, and the ability to quickly and accurately identify system issues.Five utility case studies illustrate how real‐time data analysis effortlessly produced information that helped solve significant problems, some of which might not have been discovered otherwise.

Opflow Celebrates 50 Years of Operators Teaching Operators

After 50 years of publication, Opflow continues to share practical advice and wisdom with water treatment and distribution system operators. Operators sharing what they’ve learned is one of the most effective ways to ensure successful continuity in any utility.

A Discrete Predator-Prey Brain Storm Optimization Technique for Optimal Allocation of Micro-PMUs in Distribution System State Estimation

This paper proposes a practical method for determining the optimal allocation of micro-Phasor Measurement Units (μPMUs) for distribution system state estimation (DSSE). The proposed method formulates the state estimation based on the nest structure of DistFlow, which is used for power flow calculation in distribution systems due to the redundancy of less than 1. The use of μPMUs can significantly improve the accuracy of estimates. However, Distribution System Operators (DSOs) need to consider optimization constraints before deciding on the optimal location of μPMUs. To tackle this issue, this paper proposes the use of DPPBSO (Discrete Predator-Prey Brain Storm Optimization) of Evolutionary Computation (EC) to optimize the location of μPMUs. PPBSO is an extension method that applies the Predator-Prey strategy to Brain Storm Optimization (BSO), and DPPSO is the discrete version of PPBSO used in solving combinatorial optimization problems. The Predator-Prey strategy is critical in improving the solution candidates by intensifying and diversifying solution searches in EC. Simulation results demonstrate the effectiveness of the proposed method in the IEEE 69-node distribution system.

Impact of combining party building activities and digital transformation on distribution system performance

Abstract How to effectively combine modern digital technology and the results of the experience accumulated in the traditional party building work, effectively solve the problems existing in the traditional party building work, so that the party building work carried out transparently and efficiently has become a new issue and challenge. In this paper, the overall framework of an intelligent party building system is designed based on the necessity of digital transformation of building activities and performance requirements. The system is divided into four modules: party building management, service management, statistical analysis, and system management, and the functions of each module have been designed and integrated. Based on the principles of database design, a conceptual structure design is proposed, and the association rules and FP-growth algorithm are utilized to perform association mining on party-building activity data. The results of the association rule mining test show that the fluctuation range of confidence and support is between [0.9148, 0.9587] and [0.9048, 0.9348], respectively, and the system passed the association rule mining test. The majority of people believe that using the party building information platform is beneficial for conducting party-building activities. 80% of the users think that the party building system platform is better and meets their needs for use.

Automated Correction of GIS Data for Loads and Distributed Energy Resources in Secondary Distribution Networks

Currently, utilities are making significant efforts to correct their secondary models in geographic information systems (GISs) to capture the distribution system performance due to the increased penetration of distributed energy resources (DERs) such as renewable energy resources, distributed energy storage, and electric vehicles (EVs). However, their databases are often not reliable in terms of GIS coordinates of elements such as loads and DERs resulting in an approximate representation of the secondary distribution network. This paper presents an automated tool for accurate secondary network topology GIS coordinates correction. The proposed automated tool provides a more accurate feeder topology for utilities to estimate and operate distribution systems by assigning the load and DER nodes to their corresponding customer location. To simplify the complexity of the proposed new tool, only two commonly available inputs are being used as input data: municipal parcel GIS delimitation data, and utility secondary feeder topology database. A three-stage framework is proposed to develop the automated tool: the first stage reads and processes the raw input data; the second stage works automatically with no human intervention to assign the load and DER nodes to their associated location; the third stage provides the load and DER coordinates and physical address. The proposed procedure is implemented on an actual feeder from an electrical utility with high penetration of DERs.The results show that the proposed method provides a more accurate estimation of the topology of the feeder in terms of coordinates.

A Distributed Filtering-Based Comprehensive Framework to Optimize Grid Performance of Harmonic-Polluted Distribution Systems

A Distributed Filtering-Based Comprehensive Framework to Optimize Grid Performance of Harmonic-Polluted Distribution Systems

Underwater continuous variable quantum key distribution scheme based on imperfect measurement basis choice

Measurement basis choice is an essential step in the underwater continuous variable quantum key distribution system based on homodyne detection. However, in practice, finite bandwidth of analog-to-digital converter at the receiver’s side is limited, which can lead to defects in the measurement basis choice. That is, the receiver cannot accurately modulate the corresponding phase angle on the phase modulator for measurement basis choice to implement homodyne detection. The imperfect measurement basis choice will introduce extra excess noise, which affects the security of underwater continuous variable quantum key distribution scheme. To solve this problem, we propose an underwater continuous variable quantum key distribution scheme based on imperfect measurement basis choice, and analyze the impact of imperfect measurement basis choice on the performance of underwater continuous variable quantum key distribution system in detail. The research results indicate that the extra excess noise introduced by imperfect measurement basis choice can reduce the secret key rate and maximum transmission distance of the underwater Gaussian modulated quantum key distribution, thus reducing the security of the system. In order to achieve reliable underwater continuous variable quantum key distribution, we quantitatively analyze the extra excess noise introduced by the imperfect measurement basis choice and obtain its security limit. Besides, we also consider the influence of different seawater depths on the security limit of the proposed scheme, effectively solving the security risks caused by the imperfect measurement basis choice. Furthermore, for the proposed scheme, we not only consider its asymptotic security case but also its composable security case, and performance curves obtained in the latter are tighter than that achieved in the former. The proposed scheme aims to promote the practical process of underwater continuous variable quantum key distribution system and provide theoretical guidance for the accurate evaluation of water channel parameters in underwater communication of global quantum communication networks.

A Game-Theoretic Approach for Electric Vehicle Aggregators Participating in Phase Balancing Considering Network Topology

With the increasing popularity of electric vehicles (EVs), uncontrolled charging of single-phase plug-in EVs will result in severe three-phase unbalance problem in distribution networks. To solve the problem, a phase balancing (PB) scheme performed by EV aggregators (EVAs) based on the linear multiphase power flow model is proposed in this paper. In the scheme, the PB compensations are provided to encourage EVAs to help the distribution system operator reduce the phase unbalance of the entire grid. Considering all EVAs are selfish and rational, the PB scheme is formulated as a game problem, in which each EVA competes with other EVAs to determine its charging strategy to minimize the charging cost minus the PB compensation. The consideration of coupling voltage constraints leads this game model to a challenging generalized Nash equilibrium problem (GNEP). By employing the theory of variational inequality, the properties of solutions for the GNEP are investigated. Furthermore, a two-level distributed algorithm is designed to find the unique variational solution, a fair and stable solution. Finally, comprehensive case studies are conducted on the IEEE-13 and IEEE-123 test systems to corroborate that the proposed PB game model can effectively mitigate voltage unbalance and cut EV users’ costs.

Incentive Control Signals to Support Resilient Distribution System Operations

Incentive Control Signals to Support Resilient Distribution System Operations