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The object of the study is the processes in distribution electric networks and their influence on technical and economic characteristics aimed at achieving the main indicators of reliability, which is characterized by the continuity of electricity supply, namely, indicators of the quality of services: the index of the average duration of long interruptions and the index of the average frequency of long interruptions ( SAIDI, SAIFI), as well as compliance with the guaranteed quality standards of electric energy supply services, which are established by the Resolution of the NCRECP. The problem to be solved is a set of factors aimed at reducing the index of the average duration of long interruptions and the index of the average frequency of long interruptions (SAIDI, SAIFI), taking into account and applying effective measures of stimulating tariff formation (Rab - tariff) aimed at providing quality services to consumers of electric energy in accordance with the guaranteed standards established by the Resolution of the NCRECP. The analysis of the main indicators of the quality of SAIDI and SAIFI services for the period from 01.01.2022 to 03.31.2022 was carried out on the example of the operator of the distribution system JSC "Kharkivoblenergo". The impact of natural and unnatural factors on the formation of these indicators is analyzed, taking into account force majeure circumstances and military aggression on the territory of the Kharkiv region. The changes in the quality indicators of SAIDI and SAIFI services and their compliance with the normative values established by the NCRECP were analyzed. The conducted analysis of SAIDI and SAIFI service quality indicators allows us to state that achieving the target values of electricity supply continuity indicators is a fundamental factor for improving the quality of electricity supply services to consumers. The provision of the necessary guaranteed quality standards for the supply of electric energy to consumers is substantiated taking into account the stimulating tariff formation (Rab - tariff). It is shown that the introduction and development of stimulating tariff formation lays a reliable foundation for a strong and competitive Ukraine on the territory of the European Union and introduces dynamic development for a strong and independent Ukrainian economy. Ref. 19, figure, table.

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. [ABSTRACT FROM AUTHOR]

Wide-area voltage quality assessment represents one of the mandatory objectives for distribution system operators in the development of advanced distribution management systems supporting smart grid requirements. This paper introduces a zonal approach for wide-area temporary voltage quality evaluation in a distribution network. The concept of temporary voltage quality evaluation and assessment is recommended to incentivize active/online management of voltage quality issues. A decision support system based on simple deterministic rules is proposed for rating the voltage quality zones in a distribution network and making recommendations to the distribution system operator. Voltage RMS level, unbalance, and total harmonic distortion are considered voltage quality indices representing the inputs in the decision support system. Residential, commercial, and industrial load types are considered when setting the thresholds for voltage quality indices. The proposed zonal approach for the division of distribution networks in voltage quality zones is applied to the example of a typical European-type distribution network. The operation of a decision support system is tested using the developed distribution smart grid model. The following simulation case studies are conducted: loads with low power factors, manual voltage regulation at MV/LV transformers, unbalanced loads, integration of solar power plant, and nonlinear loads. The obtained simulation results reveal the benefits of the proposed voltage quality assessment approach. Cybersecurity challenges that may impact the proposed approach are addressed, including security vulnerabilities, data privacy, and resilience to cyber threats. [ABSTRACT FROM AUTHOR]

As offline control photovoltaic (PV) plants are not equipped with online communication and remote control systems, they cannot adjust their power in real-time. Therefore, in a distribution network saturated with offline control PVs, the distribution system operator (DSO) should schedule the distributed energy resources (DERs) considering the uncertainty of renewable energy to prevent curtailment due to overvoltage. This paper presents a day-ahead network operation strategy using a mobile energy storage system (MESS) and offline control PVs to minimize power curtailment. The MESS model efficiently considers the transportation time and power loss of the MESS, and models various operating modes, such as the charging, discharging, idle, and moving modes. The optimization problem is formulated based on mixed-integer linear programming (MILP) considering the spatial and temporal operation constraints of MESSs and is performed using chanced constrained optimal power flow (CC-OPF). The upper limits for offline control PVs are set based on the probabilistic approach, thus mitigating overvoltage due to forecasting errors. The proposed operation strategy was tested in the IEEE 33-node distribution system coupled with a 15-node transportation system. The test results show the effectiveness of the proposed method for minimizing curtailment in offline control PVs. [ABSTRACT FROM AUTHOR]

This paper proposes a set of digitalisation indicators focused on measuring the different digital capabilities and infrastructure of electricity distribution systems, as opposed to previous indicators which have mainly focused on performance and quality of service aspects.The indicators are classified according to the pillars of digitalisation: sensor and actuator, connectivity, data processing, and digital culture. They are use-case-agnostic and do not require a huge amount of information. In addition to this, three possible new applications of these indicators for distribution system operators and regulatory authorities are identified and discussed.The extensive use of these indicators in Europe could allow the development of fruitful collaborations between distribution system operators, allow the identification of cause–effect relations between grid performance and digital infrastructure, and improve the replicability of innovative smart grid solutions. However, this will only be possible if regulators promote the adoption of the proposed indicators and the dissemination of their results.

This paper presents a comprehensive study on the impacts of peer-to-peer (P2P) energy markets on distribution systems, specifically focusing on voltage, power loss, and congestion. While P2P energy markets create opportunities for direct trading between prosumers and consumers, ensuring compliance with distribution system constraints remains a challenge. This paper proposes an iterative method and graphical interpretation in order to assess complex interactions, addressing the persistent issue of network constraints. Additionally, this paper proposes a method to determine distribution locational marginal prices (DLMPs) for real-time traditional energy markets. This ensures effective coordination among sellers, buyers, and the distribution system operator. The proposed method aims to prevent negative impacts on distribution system operation via the determination of the allowable maximum trading power (MTP), ensuring empirical validity and practical implementation via operating conditions and forecast errors, thus distinguishing it from prior studies. This paper also establishes a model for P2P energy market interactions, utilizing linear estimations for efficient DLMP updates. The contributions of this paper enhance the understanding and operation of P2P energy markets, and is supported by simulation results validating the proposed method. [ABSTRACT FROM AUTHOR]

This article presents the methodology and results developed as part of the Integration of Energy Resources through Local Electricity Markets (IREMEL) project, whose aim is to assess the capability of flexibility markets to manage eventual distribution network (DN) congestion produced by a high penetration of distributed energy resources (DERs), including photovoltaic (PV) panels, battery energy storage systems (BESSs), and electric vehicles (EVs). The distribution system simulator OpenDSS has been used to simulate three Spanish DNs under multiple DER penetration scenarios considering an urban and rural low-voltage network and an industrial medium-voltage DN. Likewise, the congestion events detected in the annual simulations have been used to measure the potential of flexibility markets under different DER penetrations and energy pricing. The results suggest that oversized distribution networks could prevent a profitable flexibility market implementation since the simulations developed in this article shows that networks with high congestion levels are prime candidates to solve this issue through a market mechanism. Likewise, the results suggest that a proper price for the energy managed through a local flexibility market (LFM) could have a bigger effect on market viability than DER penetration. [ABSTRACT FROM AUTHOR]

The development of a local energy market (LEM) in Thailand involves prosumers and electric vehicle (EV) owners in a low-voltage distribution system (LVDS). However, both maximizing social welfare through independent energy transactions and managing distribution network constraints (DNCs) remain challenging. Additionally, defining fair incentives and ensuring equitable participation in local grid service programs further add to these challenges. This paper proposes an optimal LEM operation incorporating participants’ selection of energy transaction partners and independent price negotiations to maximize social welfare. The distribution system operator provides grid service programs to address violations, define fair incentives, ensure equitable participation, and guarantee the resolution of DNC violations while participants maintain control over their power consumption. A novel penalty scheme is proposed to support these grid service programs. Numerical simulations on a 380-V LVDS in Thailand demonstrate that social welfare is maximized at 19.17 THB/h across all preference cases during the study period. The LEM trades electricity without violating DNCs while allowing self-management. Results show that EVs contribute 83.66% of the demand reduction required by the distribution system operator, while the penalty scheme discourages 100% of individual benefit pursuit. Revenue compensation covers 100% of all prosumers’ revenue before implementing the grid service programs for all periods.

The separation of transmission and distribution systems raises a variety of questions concerning the integration of many distributed generators (DGs) into future grids. They are difficult to solve by using current energy management methods. Especially, the cooperative control between transmission system operator (TSO) and distribution system operator (DSO) has been increasingly emphasized to manage the line congestion. This paper proposes a new cooperative control of TSO-DSO based on the generation-load power sensitivity analysis. To minimize the required computational effort and data communication, the information of TSO and DSO is processed separately in the generation-load power sensitivity matrix of power system. The proposed cooperative control is implemented by three-step process, which is aggregation, specification, and local distribution. Firstly, the DSOs aggregate the flexibility area of DGs in their networks, and they inform the TSO of the feasible operation regions (FORs). Then, the TSO sends the power references at the boundary buses to many DSOs. Thereafter, the DSOs use these references as loads to calculate the detailed power references for their generators. As the result, the net power of DSOs satisfies the power references requested by the TSO. The case studies are carried out to verify the effectiveness of proposed control. The results show that when the load is increased by 20%, the overall average of line loading is decreased by 4.34% with the proposed control. Also, when the generator of 634 MW is disconnected, the frequency nadir is increased by 0.1 Hz compared with the $P$ - $f$ droop control.

The importance of accurate forecasting in the electric sector has grown due to the increasing demand and adoption of high volume of Renewable Energy Sources (RES). Short-term forecasting (STF) using deep learning methods has shown potential for improving forecasting accuracy. However, the accuracy of these methods can be further enhanced by combining them to generate a hybrid model, selecting appropriate input features, generating new features, and optimizing model parameters. This paper proposes a novel multi-stage framework for PV and load STF that employs feature generation, feature selection, and optimal hyperparameter tuning preprocessing techniques. An enhanced hybrid CNN-LSTM deep learning model architecture is developed in the final stage of the proposed framework. The framework is assessed and compared to other leading-edge approaches across different DSO scenarios, including multiple single-phase residential loads, three-phase feeders, and secondary substation, demonstrating a significant reduction in forecasting errors.

The power grid and transportation network are coupled by the charging behavior of electric vehicles. Based on the coupled power-transportation network model, this paper first analyzes the effect of the distribution system operator's (DSO) electricity selling price on guiding the charging behavior of electric vehicles in the transportation network and then builds the DSO's optimal pricing formulation. Considering the competition between multiple charging network operators (CNOs), this paper establishes a game model between CNOs and solves it iteratively through the best response dynamic method. An approximation method using the elasticity matrix is proposed to speed up the solution by reducing the multi-layer optimization to a single layer one in each iteration, with its effectiveness validated through numerical tests. Furthermore, the paper discusses the issue of the prisoner's dilemma that arises among CNOs and explores the potential impact of their cooperative strategies on the overall system. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to summarize and share the field experiment results of KEPCO's project consortium to create a TSO-DSO-DERA interaction scheme. The field experiment was conducted based on the prequalification algorithm proposed in previous research from the same consortium, and was designed to verify the validity of the algorithm under realistic grid conditions. In addition, during the course of the field experiment, it was found that points that were missed or not given much importance in the existing prequalification algorithm could affect the completeness of the overall system, and then practical improvements were made to improve this. The demonstration results confirm that the proposed algorithm is effective in real-world grid environments and can help DSOs to ensure the reliability of the distribution system while supporting DERA's participation in the wholesale market using the proposed prequalification scheme. [ABSTRACT FROM AUTHOR]

Wide-area voltage quality assessment represents one of the mandatory objectives for distribution system operators in the development of advanced distribution management systems supporting smart grid requirements. This paper introduces a zonal approach for wide-area temporary voltage quality evaluation in a distribution network. The concept of temporary voltage quality evaluation and assessment is recommended to incentivize active/online management of voltage quality issues. A decision support system based on simple deterministic rules is proposed for rating the voltage quality zones in a distribution network and making recommendations to the distribution system operator. Voltage RMS level, unbalance, and total harmonic distortion are considered voltage quality indices representing the inputs in the decision support system. Residential, commercial, and industrial load types are considered when setting the thresholds for voltage quality indices. The proposed zonal approach for the division of distribution networks in voltage quality zones is applied to the example of a typical European-type distribution network. The operation of a decision support system is tested using the developed distribution smart grid model. The following simulation case studies are conducted: loads with low power factors, manual voltage regulation at MV/LV transformers, unbalanced loads, integration of solar power plant, and nonlinear loads. The obtained simulation results reveal the benefits of the proposed voltage quality assessment approach. Cybersecurity challenges that may impact the proposed approach are addressed, including security vulnerabilities, data privacy, and resilience to cyber threats.

As offline control photovoltaic (PV) plants are not equipped with online communication and remote control systems, they cannot adjust their power in real-time. Therefore, in a distribution network saturated with offline control PVs, the distribution system operator (DSO) should schedule the distributed energy resources (DERs) considering the uncertainty of renewable energy to prevent curtailment due to overvoltage. This paper presents a day-ahead network operation strategy using a mobile energy storage system (MESS) and offline control PVs to minimize power curtailment. The MESS model efficiently considers the transportation time and power loss of the MESS, and models various operating modes, such as the charging, discharging, idle, and moving modes. The optimization problem is formulated based on mixed-integer linear programming (MILP) considering the spatial and temporal operation constraints of MESSs and is performed using chanced constrained optimal power flow (CC-OPF). The upper limits for offline control PVs are set based on the probabilistic approach, thus mitigating overvoltage due to forecasting errors. The proposed operation strategy was tested in the IEEE 33-node distribution system coupled with a 15-node transportation system. The test results show the effectiveness of the proposed method for minimizing curtailment in offline control PVs.

The power grid and transportation network are coupled by the charging behavior of electric vehicles. Based on the coupled power-transportation network model, this paper first analyzes the effect of the distribution system operator’s (DSO) electricity selling price on guiding the charging behavior of electric vehicles in the transportation network and then builds the DSO’s optimal pricing formulation. Considering the competition between multiple charging network operators (CNOs), this paper establishes a game model between CNOs and solves it iteratively through the best response dynamic method. An approximation method using the elasticity matrix is proposed to speed up the solution by reducing the multi-layer optimization to a single layer one in each iteration, with its effectiveness validated through numerical tests. Furthermore, the paper discusses the issue of the prisoner’s dilemma that arises among CNOs and explores the potential impact of their cooperative strategies on the overall system.

The increasing integration of renewable energy sources into the electricity sector for decarbonization purposes necessitates effective energy storage facilities, which can separate energy supply and demand. Battery Energy Storage Systems (BESS) provide a practical solution to enhance the security, flexibility, and reliability of electricity supply, and thus, will be key players in future energy markets. Directive 2019/944, which focuses on common rules for the internal market of electricity, provides a regulatory framework for the deployment of energy storage facilities. However, several gaps and challenges remain regarding the implementation of the directive, particularly in insular energy systems with immature storage infrastructures such as Cyprus, an EU Member State. This study examines these challenges and gaps by investigating the case study of Cyprus while also presenting the handling of energy storage in other European countries such as Germany and Poland. The primary aim of this study is to identify gaps in the legislation regarding energy storage and potential bottlenecks or monopolistic approaches that could hinder the widespread deployment of BESS under the liberalization of the energy market. In light of several BESS technologies available in the market, the study focuses on lithium-based technologies, which account for the largest share of the BESS market and are projected to grow at the highest compound annual growth rate by 2030. Therefore, the authors concentrate on Lithium BESS. The study highlights the crucial role of storage facilities in transforming the power generation sector by shifting toward renewable sources of energy. As such, the study emphasizes the importance of effective regulatory frameworks in enabling the deployment of BESS, particularly in insular energy systems. Overall, this study sheds light on the gaps and challenges facing the deployment of BESS, providing valuable insights for policymakers and stakeholders to design effective regulatory frameworks to facilitate the widespread adoption of BESS. [ABSTRACT FROM AUTHOR]

With a national emissions profile revealing a persistent role for fossil fuels in the energy and electricity fuel mixes, Australia's ability to realise its net zero emission ambitions is inherently linked to how the country manages and supports the decarbonisation of its energy sector to ensure the realisation of net zero goals by 2030, 2050, and beyond. Rapid growth in distributed energy resources is now challenging Australia's electricity system and the regulatory framework, both of which were established on assumptions of centralized electricity supply from large generators to passive consumers. This article recognises that while regulatory frameworks – policies, laws, other instruments – can be critical enablers of desirable transitions, the current regulatory regime governing Australia's energy markets has been a significant impediment to the energy sector decarbonisation and emission mitigation. Aspects of the regulatory framework that can encourage or hinder the development of future high DER markets and the decarbonisation transition across the national energy market are also explored. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the impacts of peer-to-peer (P2P) energy markets on distribution systems, specifically focusing on voltage, power loss, and congestion. While P2P energy markets create opportunities for direct trading between prosumers and consumers, ensuring compliance with distribution system constraints remains a challenge. This paper proposes an iterative method and graphical interpretation in order to assess complex interactions, addressing the persistent issue of network constraints. Additionally, this paper proposes a method to determine distribution locational marginal prices (DLMPs) for real-time traditional energy markets. This ensures effective coordination among sellers, buyers, and the distribution system operator. The proposed method aims to prevent negative impacts on distribution system operation via the determination of the allowable maximum trading power (MTP), ensuring empirical validity and practical implementation via operating conditions and forecast errors, thus distinguishing it from prior studies. This paper also establishes a model for P2P energy market interactions, utilizing linear estimations for efficient DLMP updates. The contributions of this paper enhance the understanding and operation of P2P energy markets, and is supported by simulation results validating the proposed method.

An optimization-based platform is presented to request ancillary services and perform demand response. The work has seen a joint effort of the Italian TSO and DSO (Transmission and Distribution System Operators) and active local prosumers within the LIVING GRID innovation and demonstration project. The platform, a pure software architecture based on existing control and supervision equipment in the prosumer's plant, embeds optimization models, can communicate reference values for active and reactive power and perform intentional islanding and demand response in portions of the distribution grid and microgrids. Two possible configurations have been tested: Single PoC (Point of Connection) and Multi-PoC. The results of the optimization model and in-field experiments are presented and discussed for the considered pilot site: the Savona Campus Smart Polygeneration Microgrid (University of Genova, Italy).

Planning public electric vehicle (EV) charging infrastructure has gradually become a key factor in the electrification of mobility and decarbonization of the transport sector. In order to achieve a high level of electrification in mobility, in recent years, different studies have been presented, proposing novel practices and methodologies for the planning and operation of electric vehicles charging infrastructure. In this paper, the authors present an up-to-date analysis of the existing literature in this research field, organized by considering the perspectives and objectives of the principal actors/operators of the EV public charging infrastructure value chain. Among these actors, the electric vehicle, the charging operators and service providers, and the power system infrastructure (transmission and distribution system) are analyzed in depth. By classifying the reviewed literature based on this manifold viewpoints approach, this paper aims to facilitate researchers and technology developers in exploring the state-of-the-art methodologies for each actor's perspective, and identify conflicting interests and synergies in charging infrastructure operation and planning. [ABSTRACT FROM AUTHOR]

This paper proposes a centralized model to activate a residential demand response to improve the reliability of a distribution network. The model aims to minimize the damage cost imposed by load curtailments following the occurrence of unexpected events. In this model, the Distribution System Operator (DSO) and responsive customers have already signed a contract authorizing the DSO to alter the operation of responsive appliances in case system reliability is jeopardized. The model addresses consumers' preferences and guarantees that the operation of appliances be displaced within the bounds defined by the owners. Once an unexpected event occurs, the DSO commits responsive appliances to avoid likely violations in the network operational limits and costly load curtailments. The proposed model is mathematically formulated in the form of Mixed Integer Linear Programming (MILP) and its capability is depicted via applying to a realworld distribution network with some residential consumers. The comparison of service reliability indices after and before utilizing demand response potentials illustrates the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Electrical power system operators (SOs) are free to realize grid operations according to their own strategies. However, because resulting power flows also depend on the actions of neighboring SOs, appropriate coordination is needed to improve the resulting system states from an overall perspective and from an individual SO perspective. In this paper, a new method is presented that preserves the data integrity of the SOs and their independent operation of their grids. This method is compared with a non-coordinated local control and another sequential method that has been identified as the most promising distributed optimization method in previous research. The time series simulations use transformer tap positioning as well as generation unit voltage setpoints and reactive power injections as flexibilities. The methods are tested on a multi-voltage, multi-SO, realistic benchmark grid with different objective combinations of the SOs. In conclusion, the results of the new method are much closer to the theoretical optimum represented by central optimization than those of the other two methods. Furthermore, the introduced method integrates a sophisticated procedure to provide fairness between SOs that is missing in other methods. [ABSTRACT FROM AUTHOR]

Followed by the extensive activation of demand side entities, the anti-competitive and monopolistic aspects of distribution system operator (DSO) is becoming more apparent. The business model of the DSO and its regulations are not capable enough to fully leverage the capacity of emerging technologies and responsive prosumers. This paper criticized the challenges/deficits revolving around the conventional DSO model and proposes an interactive platform based on the sharing economy business model at the network level. The electricity distribution stakeholders' organization (EDSO) as the substitute of DSO in active distribution networks is developed based on the collaborative governance decision-making model. The EDSO has the privilege to legislate on the platform operation and its main policy is to preserve the public interest as well as the integrity of electric distribution system. The superiority of proposed operation model is its non-monopolistic and non-profit nature which materializes the perfect competition of active customers and guaranties their maximum utilization. [ABSTRACT FROM AUTHOR]

Operating virtual power plants (VPP) solely based on economic feasibility can cause stability problems, such as voltage violation and power congestion in the distribution system. A cooperation-based operation between the VPP and distribution system operator (DSO) is regarded one of the methodologies for solving stability problems. In the cooperation-based operation method, a VPP establishes an operation strategy considering the information provided beforehand by the DSO, such as the distribution system constraint (DSC). The DSC is uncertain because it is determined based on the forecasted grid situation. Therefore, operational strategies that rely only on the DSCs provided by DSOs may make the operation of the VPP passive and reduce profits depending on the accuracy of the announced DSCs. This study proposes an operating methodology and optimal operation model considering the uncertainty of the DSC to increase the profit of the VPP. In the proposed model, the VPP independently forecasts the DSC for profit maximization and establishes an operational plan considering penalties. Case studies were conducted to demonstrate the economic improvement of the VPP, considering the uncertainty of the DSC. The case study results demonstrated that the proposed model increased the profit of the VPP by 1.6 % compared with that of the conventional method.

This article presents the methodology and results developed as part of the Integration of Energy Resources through Local Electricity Markets (IREMEL) project, whose aim is to assess the capability of flexibility markets to manage eventual distribution network (DN) congestion produced by a high penetration of distributed energy resources (DERs), including photovoltaic (PV) panels, battery energy storage systems (BESSs), and electric vehicles (EVs). The distribution system simulator OpenDSS has been used to simulate three Spanish DNs under multiple DER penetration scenarios considering an urban and rural low-voltage network and an industrial medium-voltage DN. Likewise, the congestion events detected in the annual simulations have been used to measure the potential of flexibility markets under different DER penetrations and energy pricing. The results suggest that oversized distribution networks could prevent a profitable flexibility market implementation since the simulations developed in this article shows that networks with high congestion levels are prime candidates to solve this issue through a market mechanism. Likewise, the results suggest that a proper price for the energy managed through a local flexibility market (LFM) could have a bigger effect on market viability than DER penetration.

The purpose of this paper is to summarize and share the field experiment results of KEPCO’s project consortium to create a TSO-DSO-DERA interaction scheme. The field experiment was conducted based on the prequalification algorithm proposed in previous research from the same consortium, and was designed to verify the validity of the algorithm under realistic grid conditions. In addition, during the course of the field experiment, it was found that points that were missed or not given much importance in the existing prequalification algorithm could affect the completeness of the overall system, and then practical improvements were made to improve this. The demonstration results confirm that the proposed algorithm is effective in real-world grid environments and can help DSOs to ensure the reliability of the distribution system while supporting DERA’s participation in the wholesale market using the proposed prequalification scheme.

The conventional volt-VAR control (VVC) in distribution systems has limitations in solving the overvoltage problem caused by massive solar photovoltaic (PV) deployment. As an alternative method, VVC using solar PV smart inverters (PVSIs) has come into the limelight, which can respond quickly and effectively to solve the overvoltage problem by absorbing reactive power. However, the network power loss, that is, the sum of line losses in the distribution network, increases with reactive power. Dynamic distribution network reconfiguration (DNR), which hourly controls the network topology by controlling sectionalizing and tie switches, can also solve the overvoltage problem and reduce network loss by changing the power flow in the network. In this study, to improve the voltage profile and minimize the network power loss, we propose a control scheme that integrates the dynamic DNR with volt-VAR control of PVSIs. The proposed control scheme is practically usable for three reasons: Primarily, the proposed scheme is based on a deep reinforcement learning (DRL) algorithm, which does not require accurate distribution system parameters. Furthermore, we propose the use of a heterogeneous multiagent DRL algorithm to control the switches centrally and PVSIs locally. Finally, a practical communication network in the distribution system is assumed. PVSIs only send their status to the central control center, and there is no communication between the PVSIs. A modified 33-bus distribution test feeder reflecting the system conditions of South Korea is used for the case study. The results of this case study demonstrates that the proposed control scheme effectively improves the voltage profile of the distribution system. In addition, the proposed scheme reduces the total power loss in the distribution system, which is the sum of the network power loss and curtailed energy, owing to the voltage violation of the solar PV output. [ABSTRACT FROM AUTHOR]

This paper seeks to shed light on the nature of optimal regulation of the electricity distribution system operator (DSO) over the period to 2025 and beyond, following the implementation of the EU Clean Energy Package and its constituent parts: Electricity Regulation (EU) 2019/943 and Electricity Directive (EU) 2019/944. We conducted two parallel surveys of DSOs and their national regulatory authorities (NRAs) across 39 European countries. This produced 39 responses from DSOs and 12 responses from NRAs covering, respectively, 40% and 78% of customers in those countries. We asked both DSOs and NRAs three sets of questions related to: (1) the definition and regulation of the future system operator function of the DSO; (2) lessons learned from transmission system operator (TSO) regulation that can be translated to the DSO; and (3) the way in which regulators support the capacity of the DSO to operate and coordinate the system. Our findings are consistent with the observation that the move towards a more active role for the DSO remains work in progress for both DSOs and their NRAs, given the fact that the Clean Energy Package has only passed into European Law relatively recently and some Member States are still implementing its provisions. [ABSTRACT FROM AUTHOR]

While peer-to-peer energy trading has the potential to harness the capabilities of small-scale energy resources, a peer-matching process often overlooks power grid conditions, yielding increased losses, line congestion, and voltage problems. This imposes a great challenge on the distribution system operator (DSO), which can eventually limit peer-to-peer energy trading. To align the peer-matching process with the physical grid conditions, this paper proposes a cost causality-based network cost allocation method and the grid-aware peer-matching process. Building on the cost causality principle, the proposed model utilizes the network cost (voltage, congestion, and loss) as a signal to encourage peers to adjust their preferences ensuring that matches are more in line with grid conditions, leading to enhanced social welfare. Additionally, this paper presents mathematical proof showing the superiority of the causality-based cost allocation over existing methods. • Proposing a causality-based cost allocation method. • Demonstrating the superiority of causality-based cost allocation. • Designing coordination P2P energy trading and network operation using network costs allocation. [ABSTRACT FROM AUTHOR]

This paper proposes a set of digitalisation indicators focused on measuring the different digital capabilities and infrastructure of electricity distribution systems, as opposed to previous indicators which have mainly focused on performance and quality of service aspects. The indicators are classified according to the pillars of digitalisation: sensor and actuator, connectivity, data processing, and digital culture. They are use-case-agnostic and do not require a huge amount of information. In addition to this, three possible new applications of these indicators for distribution system operators and regulatory authorities are identified and discussed. The extensive use of these indicators in Europe could allow the development of fruitful collaborations between distribution system operators, allow the identification of cause–effect relations between grid performance and digital infrastructure, and improve the replicability of innovative smart grid solutions. However, this will only be possible if regulators promote the adoption of the proposed indicators and the dissemination of their results. • Smart grid indicators are required by European Directive 2019/944. • Indicators on sensors/actuators, connectivity, data processing, and digital culture. • Indicators to provide an overview of the distribution grid. • Indicators to study relation between performance and digital infrastructure. • Indicators to generate information for the replicability of solutions. [ABSTRACT FROM AUTHOR]

The present article aims at modeling a day-ahead local electricity market (DA LEM) for transactive energy trading at the distribution level. In this regard, a wide range of distributed energy resources (DERs) in the form of multiple aggregators (AGs) participates in the DA LEM in order to trade energy with the distribution system operator (DSO), the operator of the market. On the other hand, the DSO, as the owner of the system, has the responsibility to procure the required energy of its customers with respect to the technical constraints of the distribution network. To settle the designed local market, a Stackelberg game-based approach is exploited in this research work. In the raised Stackelberg scheme, the leader of the game, the DSO, seeks to maximize its expected profit, while followers of the game, DER AGs, tend to minimize their operating costs. Ultimately, to evaluate the proposed framework, a typical case study is implemented on a modified IEEE-33 bus test system.

Due to the absence of studies of local energy communities (LECs) where the grid is represented, it is very difficult to infer implications of increased LEC integration for the distribution grid as well as for the wider society. Therefore, this paper aims to investigate holistic modelling and simulation approaches of LECs. To conduct a quantifiable assessment of different control architectures, LEC types and market frameworks, a flexible and comprehensive LEC modelling and simulation approach is needed. Modelling LECs and the environment they operate in involves a holistic approach consisting of different layers: market, controller, and grid. The controller layer is relevant both for the overall energy management system of the LEC and the controllers of single components in a LEC. In this paper, the different LEC modelling approaches in the reviewed literature are presented, several multilayered concepts for LECs are proposed, and a case study is presented to illustrate a holistic simulation where the different layers interact.

Increasing the use of solar photovoltaic (PV) generation in order to decarbonize the electric energy system results in many challenges. Overvoltage is one of the most common problems in distribution systems with high penetration of solar PV. Utilizing demand-side resources such as residential demand response (RDR) have the potential to alleviate this problem. To increase the solar PV hosting capacity, we propose an RDR based load-shifting scheme that utilizes the interaction between the distribution system operator (DSO) and demand-side resources. We first model a customer utility that consists of the cost of purchasing power, revenue from the subsidy, and discomfort due to load shifting. When an overvoltage problem is expected, DSO issues a local subsidy, and customers in the distribution system move their load in response. An optimization framework that minimizes the additional cost due to the subsidy while keeping the voltages in a prescribed range is proposed. Because of the non-linearity of the power flow analysis, we propose a sub-optimal algorithm to obtain a subsidy, prove the performance gap between the optimal subsidy and the subsidy obtained by the algorithm. A case study shows that the proposed RDR scheme increases the hosting capacity to almost its theoretical limit at a lower cost than the curtailment method.

Distribution system operators (DSOs) have difficulty in scheduling distributed energy resources owing to the increasing power demand and penetration of renewable energy. The goal of this study is to determine the charging/discharging of PV energy-integrated energy storage system (PV-ESS), EV charging price, and demand response (DR) incentive values considering voltage management. To achieve the optimal energy operation for a distribution network, this study proposes an evolutionary game theory (EGT)-based new scheduling strategy, considering voltage management for a multi-agent system (MAS). The EGT, which is a decision-making strategy, is used by agents to cooperate and derive the best scheduling with their own behavior pattern functions to minimize the system operating cost. Photovoltaic-energy storage systems, electric vehicles charging power, and loads can perform charging/discharging scheduling, electric vehicle charging planning, and demand response participation, respectively. Under DSO supervision, a reward that stabilizes the voltage profile of the power distribution system is also implemented during the cooperation process. The proposed energy scheduling strategy combines an EGT-based decision-making with particle swarm optimization (PSO) to solve the optimization problem and determine the payoff function through self-evolutionary improvement. The effectiveness of the EGT-PSO has been analyzed for an IEEE 33-bus distribution system, and the results demonstrate that the proposed scheduling strategy not only achieves the most economical decision among agents but also manages the voltage profile.

A local energy trading market (LETM) is a promising market for prosumers who have a photovoltaic (PV) system and want to make a lot of money. When it comes to PV power; however, there are still challenges in market operations. Moreover, the role of a distribution system operator (DSO) in the LETM has not yet been investigated for the centralization of operations to reserve power for PV power uncertainty. Consequently, this paper aims to investigate the effects of PV power uncertainty on the settlement process by proposing centralized optimal operations of the LETM. Furthermore, the DSO is tasked with determining a distribution locational marginal price at each bus in the distribution system, besides analyzing the bus voltage and line current limits. When power is exchanged, the DSO must reserve power to account for the uncertainty of PV power to recover the power balance. The proposed method is formulated as an optimization problem, to maximize the difference between buyers’ and sellers’ total operating costs, because this maximum value could reflect the maximum benefit obtained by each market participant. Additionally, the proposed method’s effectiveness is demonstrated on a typical low-voltage distribution system in Thailand. The simulation results show that the total benefit of market participants with PV power uncertainty is reduced, whereas that of the DSO is increased. This implies that prosumers will miss out on a lucrative opportunity if they do not improve their forecasting system.

Improving the control of flexible assets in distribution grids, e.g., battery storages, electric vehicle charging points, and heat pumps, can balance power peaks caused by high renewable power generation or load to prevent overloading the grid infrastructure. Renewable energy communities, introduced as part of the recast of the Renewable Energy Directive, provide a regulatory framework for this. As a multi-site energy management method, they can tap flexibility potential. The present work quantifies stimulus for renewable energy communities to incentivize the grid-friendly operation of flexible assets, depending on the shares of participants in rural, suburban, and urban grid topologies. Results indicate that an operation of the community, driven by maximizing the economic benefits of its members, does not clearly reduce the annual peak load at the low-voltage substation, while the operation strategy of a grid-friendly renewable energy community achieves a peak power reduction of 23–55%. When there is not full participation, forecasts of the residual load of non-participants provided by the distribution system operator can be considered in the optimization of the renewable energy community. For all simulation cases, the economic benefit between the two operation strategies differs by less than one percent, resulting in a very low additional incentive required for grid-friendliness in terms of reduced peak power. Thus, grid-friendly renewable energy communities might be a cost-effective way to defer future grid reinforcements. [ABSTRACT FROM AUTHOR]

The continued development of distributed energy resources (DER), information and communications technologies is enabling a greater number of parties to participate in electricity markets. This review explores the various methods that DERs may utilize to participate in electricity markets, the differing architectures and methodologies used to model their participation, the past and future development of communications technologies that has enabled this participation, and examples of commercial implementations of solutions to DER participation in electricity markets.

Planning public electric vehicle (EV) charging infrastructure has gradually become a key factor in the electrification of mobility and decarbonization of the transport sector. In order to achieve a high level of electrification in mobility, in recent years, different studies have been presented, proposing novel practices and methodologies for the planning and operation of electric vehicles charging infrastructure. In this paper, the authors present an up-to-date analysis of the existing literature in this research field, organized by considering the perspectives and objectives of the principal actors/operators of the EV public charging infrastructure value chain. Among these actors, the electric vehicle, the charging operators and service providers, and the power system infrastructure (transmission and distribution system) are analyzed in depth. By classifying the reviewed literature based on this manifold viewpoints approach, this paper aims to facilitate researchers and technology developers in exploring the state-of-the-art methodologies for each actor’s perspective, and identify conflicting interests and synergies in charging infrastructure operation and planning.

Electrical power system operators (SOs) are free to realize grid operations according to their own strategies. However, because resulting power flows also depend on the actions of neighboring SOs, appropriate coordination is needed to improve the resulting system states from an overall perspective and from an individual SO perspective. In this paper, a new method is presented that preserves the data integrity of the SOs and their independent operation of their grids. This method is compared with a non-coordinated local control and another sequential method that has been identified as the most promising distributed optimization method in previous research. The time series simulations use transformer tap positioning as well as generation unit voltage setpoints and reactive power injections as flexibilities. The methods are tested on a multi-voltage, multi-SO, realistic benchmark grid with different objective combinations of the SOs. In conclusion, the results of the new method are much closer to the theoretical optimum represented by central optimization than those of the other two methods. Furthermore, the introduced method integrates a sophisticated procedure to provide fairness between SOs that is missing in other methods.

This paper presents a distribution system operator (DSO) framework for wholesale and retail market participation of distributed energy resources (DERs) aggregators. The DSO coordinates aggregators’ energy and regulation offers as well as end-users’ energy consumption through the unbalanced retail market and submits balanced energy and regulation offers to the wholesale market on behalf of all the aggregators and end-users within its territory. Various kinds of DER aggregators including demand response aggregators (DRAGs), energy storage aggregators (ESAGs), electric vehicle (EV) charging stations (EVCSs), dispatchable distributed generation aggregators (DDGAGs), and renewable energy aggregators (REAGs) are modeled. To handle unbalanced distribution grids with single-phase aggregators, a linearized unbalanced power flow is tailored to model operating constraints of the distribution grid with various aggregators. A market settlement approach is proposed for the DSO, which coordinates with wholesale market clearing process and ensures the DSO’s non-profit characteristic. It is proved that at the wholesale-DSO coupling substation, the total payment received/compensated by the DSO under the wholesale price is identical to that under three single-phase retail prices for each phase at the substation. Case studies are performed on the modified IEEE 33-node and 240-node distribution test systems to investigate the market outcomes of the proposed DSO. [ABSTRACT FROM AUTHOR]

Modern active distribution networks (ADNs) have become more resilient to service interruptions due to the flexibility offered by integrated distributed energy resources (DERs). Compared to network-owned DERs, directly controlled by the distribution system operator (DSO), a vast majority of DERs controlled by independent virtual power plants (VPPs) are much more difficult to coordinate. The coordination with the VPPs and the management of uncertainty are the two major obstacles in the utilization of these DERs in the ADN restoration (ADNR). This article proposes a hierarchical framework for the sequential ADNR to overcome these two obstacles. The proposed framework adaptively integrates the sequential ADNR planning and the VPP scheduling models based on a comprehensive DSO and VPP coordination scheme to quantify and include the flexibility of VPPs in the ADNR. Furthermore, to address the uncertainty of renewable DERs and loads, a chance-constraint (CC) approach is used in these models. As the probability distributions of the uncertain parameters are not fully known, a distributionally robust reformulation for CCs is proposed that ensures that the solution is robust to any uncertainty distribution defined within a moment-based ambiguity set. The DR reformulation is further linearized to achieve DRCC mixed-integer linear-programming models for ADNR planning and VPP scheduling. Finally, its effectiveness is evaluated on the IEEE 123 node ADN. [ABSTRACT FROM AUTHOR]

Increasing penetration of distributed renewable energy sources (DRESs) has resulted in the emergence of distributed energy resource aggregators (DERAs). A DERA participates in the transmission-level market operated by a transmission system operator (TSO), and the DERA’s resources are connected to a jurisdiction of the distribution system operator (DSO). Inspired by the structure of the Korean power industry, this study assumes a minimal DSO that cannot directly dispatch the resources in its system. In this study, we develop a detailed procedure for prequalification wherein the DSO checks the DERA’s bids that are submitted to the TSO markets. The proposed prequalification enables the DSO to secure the reliability of its system by providing limited network information to the DERA. The DERA modifies its bid until potential overvoltage and overflow problems are resolved, even in the worst case, including uncertainties. The proposed prequalification process is verified using the IEEE 33-bus distribution network. Compared to previous studies, the results demonstrate that the proposed prequalification can deal with distribution system constraints, even though uncertainties are included. The proposed prequalification process can be applied to power industries where the DSO does not have the full dispatch authority on DRESs.

The consideration of distributed energy resources as non-wires alternatives for the elimination of overloads and voltage problems poses new challenges for their location and management. Traditional location methodologies approach the problem from the distribution system operator perspective, who tries to correct overload and voltage outside margins while minimizing other possible negative impacts in the network. The approach presented in this paper also considers the investor’s point of view, seeking the most appropriate technology alternative, the maximum use of the available resource, and the minimum investment. Those aspects are explicitly taken into account in the formulation of the model, which takes the form of a mixed-integer nonlinear optimization problem. The proposed methodology is tested in two different scenarios using the medium-voltage distribution system benchmark of CIGRE. The results show that the interests of the distribution system operator and the investors can be jointly satisfied, achieving an effective, safe and realistic integration of new distributed resources.

The overall operational costs of home energy systems (HES) has been considered as an objective function (OF) by many articles. This paper shows that considering the energy cost as OF can lead to a decrease in the load elasticity against the electricity price, which can lead to demand response programs failure. So the distribution system operator (DSO) must stop this decline. A new index is introduced to calculate the responsiveness of the PV-integrated HES, based on which a new OF for home energy management system is proposed. This index shows the load elasticity against the electricity price. The relation between energy cost and load responsiveness index is investigated, and several scenarios are analyzed to demonstrate the applicability of the proposed approach in real cases. The proposed method is implemented to a PV- and ESS- integrated HES. The results show the relation between the responsiveness of the loads and the operational costs of home. A sensitivity analysis is added to the paper to show the robustness of the proposed control scheme. • Considering the energy cost leads to a decrease in load elasticity against price. • A new index is proposed to calculate the responsiveness of HEMS, based on a new OF. • Home loads responsiveness index relation with the energy supply cost is discussed. • Roles of ESS to improving the responsiveness of residential loads are investigated. • ESS roles to reduce negative effect of PV in increasing PAR of HES are investigated. [ABSTRACT FROM AUTHOR]