Distribution Grid Level Research Articles

Distributed Energy Resource Integration for Carbon Neutral Power Systems: Market‐Based Approaches to Ancillary Services and Microgrid Operation

Electricity, as a sustainable energy carrier, plays a central role in the transition scenarios for carbon neutralization of energy systems. Expanding the potential of electricity requires intelligent integration of electricity infrastructures and electricity markets with distributed energy resources (DERs) including roof‐top solar photovoltaics (PVs), controllable loads, and storage batteries. This integration will advance the management of power distribution grids, resulting in harmonization of the distribution grids and variable renewable generation. In the foreseeable future, the DERs will be actively used to perform advanced management of power distribution grids and compensate fluctuation in variable renewable power generation such as PVs and wind power. Market‐based coordination mechanisms are already practiced in large‐scale electricity production, electricity trading and transmission around the world. Using these mechanisms at the distribution grid level to integrate numerous flexible devices into the grids remains an important research topic. This paper reviews the role of DER integration toward carbon‐neutral power systems, the state‐of‐art and challenges associated with market‐based approaches for integrating flexible demand, distributed generation, and storage. Methods for assessing the value of DER aggregation such as virtual power plants and microgrids are also explored. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Overcoming challenges in life cycle assessment of smart energy systems – A map of solution approaches

Current research underlines the benefits of digitalization to integrate renewable energy sources (RES) efficiently and to coordinate generation and supply. This development towards smart energy systems (SES) includes emerging use cases at the distribution grid level, e.g., smart charging strategies for electric vehicles or energy management systems in buildings. An environmental assessment of such, however, is challenging. The standardized Life Cycle Assessment (LCA) approaches seem insufficient since SES are emerging systems at the interface of digitalization and energy with multiple intended and unintended environmental effects. This article aims to derive solution approaches for LCA professionals that investigate use cases enabled by information and communication technology (ICT), specifically in SES. To identify challenges during the first two phases of an LCA and solution approaches, we examine seven recent research projects and conduct a real-time Delphi workshop with LCA experts in the field of SES. As a result, the article provides approaches on setting up an LCA, filling data gaps, and methods to draw upon the long-term impacts of use cases in SES. Key findings include a modified taxonomy of potential environmental effects. Results show that systemic effects in SES have potentially the highest impact on the LCA, followed by effects caused by user behavior. Assessing these effects of ‘higher-order’ poses an increased complexity. Determined solution approaches include combining the standardized LCA with energy system modeling or surveys on user behavior. Overall, this article reveals orientation strategies and recommendations to guide LCA professionals toward a holistic environmental assessment of use cases in SES.

Verification of the uninterrupted transition from grid parallel to island grid operation of the Virtual Synchronous Machine in a microgrid

The classic energy supply system is mainly based on the stabilising properties of electromechanical synchronous generators. The structural change of the electrical energy supply system towards a decentralised grid structure means that ancillary services must now also be provided at the distribution grid level. The Virtual Synchronous Machine (VISMA) was developed at the Institute of Electrical Power Engineering at the Clausthal University of Technology with the aim of making a decentralised generation unit in the grid behave like a real synchronous machine and thus actively provide relevant ancillary services. The VISMA is based on a three-phase inverter that can comply with grid requirements by adding an energy storage device in the DC link and using a special control algorithm. The focus of the investigations shown here is on the uninterrupted transition from grid-parallel operation of the VISMA to island grid operation and the subsequent stable continued operation of this island grid. A controller changeover, as most feed-in inverters would require in order to change the operating mode, is not necessary here. It is shown that the transients have subsided after 5 ms, which means that the VISMA has completely taken over the

Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination

The rapid electrification of residential heating and mobility sectors is expected to drive the existing distribution grid assets beyond their planned operating conditions This change will also reveal new potentials through sector coupling, flexibilities, and the local exchange of decentralized generation. This paper thus presents an optimization framework for multi-modal energy systems at the low voltage (LV) distribution grid level. In this, we focus on the reinforcement requirements of the grid and the techno-economic assessment of flexibility components and coordination between agents. By employing a multi-level approach, computational complexity is reduced, and various levels of coordination and flexibilities are implemented. We conclude the work with a case study for a representative rural grid in Germany, in which we observe high economic potential in the flexible operation of buildings, majorly thanks to better integration of photovoltaics. Across all paradigms barring a best-case benchmark, grid reinforcement based on a mix of passive and active measures was necessary. A synergy effect is observed between flexibilities and coordination, as their combination reduces the peaks to the extent of completely avoiding grid reinforcement. The presented framework can be applied with a wide range of grid and component types to outline the broad landscape of future LV distribution grids.

Plug-and-Play Algorithms for the Efficient Coordination of Active Distribution Grids

The tremendous complexity of modern distribution systems calls for alternative coordination architectures, supported by smart, self-adaptable, and, to a large degree, environment-agnostic algorithms. In this article, we discuss decentralized and distributed coordination architectures for the operation of active distribution grids aiming at effectively coping with their complexity. We present relevant methods and algorithms under the framework of multiagent systems (MASs) and decentralized decision-making associated with handling different parts of the optimal grid operation. The decision-making models are based on distributed optimization algorithms using consensus/gossip models, bioinspired algorithms from the field of population dynamics, and a method for decomposing the power-flow model. The developed techniques aim at matching production with demand in microgrids, settling the short-term energy imbalances at the distribution grid level, mitigating voltage deviations, and resolving distribution grid congestions in real-time operation. The algorithms are implemented as MAS-based software platforms, able to aggregate diverse DG units and flexible loads. Results are provided from the theoretical simulation-based models and demonstrations of the operational techniques in actual pilot sites. The applied implementations have been performed in a smart grid pilot site, for which MAS platforms have been developed and tested.

How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany

The energy system decarbonization leads to a decentralization of generation and flexibility. Among the new concepts to integrate distributed flexibility are local energy markets. While a broad range of research investigates local energy markets on a distribution grid level in detail, research on their system impact has been limited. Therefore, we develop a framework to investigate different configurations of local markets as well as the operation of distributed energy resources and their interaction with the wholesale markets. This framework is applied to a pan-European case study with detailed bottom-up modeling of local energy markets in France and Germany. Additionally, transmission grid simulations are carried out to investigate the impact of local trading on grid congestions. Our results show that a direct coordination of distributed flexibility within the wholesale market is more efficient than a preference for local trading. Nonetheless, local energy markets can be used as an incentive for the expansion of distributed flexibility as well as a way to break down the complexity of coordinating millions of distributed assets in a single market. Additionally, our results show that local trading relieves the transmission grid.

On the Importance of Grid Tariff Designs in Local Energy Markets

Local Energy Markets (LEMs) were recently proposed as a measure to coordinate an increasing amount of distributed energy resources on a distribution grid level. A variety of market models for LEMs are currently being discussed; however, a consistent analysis of various proposed grid tariff designs is missing. We address this gap by formulating a linear optimization-based market matching algorithm capable of modeling a variation of grid tariff designs. A comprehensive simulative study is performed for yearly simulations of a rural, semiurban, and urban grids in Germany, focusing on electric vehicles, heat pumps, battery storage, and photovoltaics in residential and commercial buildings. We compare energy-based grid tariffs with constant, topology-dependent and time-variable cost components and power-based tariffs to a benchmark case. The results show that grid tariffs with power fees show a significantly higher potential for the reduction of peak demand and feed-in (30–64%) than energy fee-based tariffs (8–49%). Additionally, we show that energy-based grid tariffs do not value the flexibility of assets such as electric vehicles compared to inflexible loads. A postprocessing of market results valuing the reduction of power peaks is proposed, enabling a compensation for the usage of asset flexibility.

Optimal Fuzzy-Based Energy Management Strategy to Maximize Self-Consumption of PV Systems in the Residential Sector in Ecuador

This paper proposes a fuzzy-based energy management strategy (EMS) to maximize the self-consumption from a PV installation with an energy storage system (ESS) for the residential sector adapted to the Ecuadorian electricity market. The EMS includes two control levels: Energy management at the end-user level (Fuzzy-based EMS and optimized by genetic Algorithm) and Energy management at the distribution grid level (Fuzzy-based EMS). Both strategies aim to maximize the use of the energy generated at home (taking into account the local solar generation profile), fulfilling the loads’ demand and injecting the energy surplus into the main grid to be economically compensated. Additionally, this paper presents economical modeling according to the electricity market in Ecuador. The main results showed a cost reduction in the electricity bill up to 83.64% from the base case (residential consumption without a PV system). In the scenario of a community electricity market (still not contemplated under the Ecuadorian electricity law), the potential economic savings may be more than double compared to the exact case but only with a self-consumption system.

A Cloud-Based Simulation and Testing Framework for Large-Scale EV Charging Energy Management and Charging Control

<div class="section abstract"><div class="htmlview paragraph">The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems. The subsystems can communicate with each other via message queuing telemetry transport communication (MQTT) protocol. The OPAL-RT is used to perform grid simulation and optimal EV charging energy management at the distribution grid level. It communicates with node level EVCSS and the SEP to collect real-time charging data and send charging power commands. The OPAL-RT can also communicate with transmission level controllers to provide grid services, such as frequency regulation. The EVCSS manages regional EV charging to limit the effects of clustered EV charging on the distribution grid. It uses standardized communication protocols: Open Charge Point Protocol 2.0 for charging station networks and ISO 15118 between EVs and charging stations. The modular open systems design approach of the platform allows the integration of EV charging control algorithms and hardware charging systems for performance evaluation and interoperability testing. The experimental test results show that the communication links of the platform work properly, and the EV charging control algorithms can respond to transmission level grid service request with minimal impact on local operations.</div></div>

Linear Optimization Based Distribution Grid Flexibility Aggregation Augmented With OLTC Operational Flexibilities

Ancillary services e.g., voltage control, congestion management and frequency control, require to be compensated increasingly from the Distributed Energy Resources (DERs). DERs are predominantly wind and photo-voltaic power plants, the major share of which are installed at the distribution grid level. Therefore, the previously passive distribution grids require transformation towards a more active role. Provision of ancillary services from the distribution grid level, requires assessment of active and reactive power flexibility (PQ-flexibility) potentials. Furthermore, increased renewable penetration correlates to increased responsibility of the Distribution System Operators (DSOs) for assessing the flexibility potentials. An aggregation of distribution grid potentials, subject to technical grid constraints and technological power limitations, is termed as Feasible Operating Region (FOR) of the distribution grid. The FOR effectively serves as an interface between the DSOs and the Transmission System Operators (TSO), for flexibility exchanges and planning of ancillary services provision. The determination of the FOR is established in current research, using different algorithms e.g stochastic methods, meta-heuristic programming and mathematical optimization techniques. In this paper, an FOR determination algorithm using successive linear programming (sLP) is proposed and validated against established optimization approaches on a uniform medium voltage (MV) grid model. Comparisons reveal competitiveness with established methods and an added advantage of fast calculation times, suitable for real time assessments. Further enhancement of the FOR is proposed, by integrating discrete transformer tap-changing operational flexibilities using a successive mixed integer linear programming (sMILP). Results demonstrate an increase in the flexibility potential from the distribution grid.

Exploitation of Microgrid Flexibility in Distribution System Hosting Prosumers

Increasing the penetration of renewables on prosumers' side brings about operational challenges in the distribution grid due to their variable and uncertain behavior. In fact, these resources have increased the distribution grid net load fluctuation during recent years. In this article, the flexibility-oriented stochastic scheduling of a microgrid is suggested to capture the net load variability at the distribution grid level. In this scheduling, the flexibility limits are set to manage the net load fluctuation at a desirable level for the main grid operator. The uncertainties of load and renewables are considered, and their uncertainties are under control by the risk-averse strategy. Moreover, multiperiod islanding constraints are added to the problem, preparing the microgrid for a resilient response to disturbances. The model is examined on a typical distribution feeder consisting of prosumers and a microgrid. The numerical results are compared for both flexibility-oriented and traditional scheduling of a microgrid at the distribution level. The proposed model reduces the net load ramping of the distribution grid using an efficient dispatch of resources in the microgrid. A sensitivity analysis is also carried out to show the effectiveness of the model.

How much smart charging is smart?

The threat of climate change motivates the expansion of variable renewable energy sources (VRES) as well as the transition to plug-in electric vehicles (PEV). Both technologies present unique challenges to electricity systems, potentially leading to high grid expansion cost. In this paper, we present a detailed assessment on how smart-charging of PEVs can mitigate these problems and reduce cost on the distribution grid level. To this end, we propose a heuristic policy that dynamically decides on charging of PEVs, curtailment of VRES, and subsequently on infrastructure investments trading off fixed investments with variable operational costs. The main inputs are modeled as stochastic and the proposed policy is non-anticipative. We conduct a comprehensive case study for Germany in the year 2035 using detailed descriptions of existing distribution grids, realistic driving patterns, and real-world VRES feed-in data. Potential savings of €6.2 billion in investment costs lead to a reduction in total distribution grid cost of around 19%. This result is achieved by upgrading 7 million (21%) PEV chargers all over Germany. Upgrading 100% of chargers to smart-chargers as is proposed in the extant literature is clearly sub-optimal as it leads to significantly higher total cost. A closer investigation for single grids reveals that savings as well as the optimal share of smart chargers varies widely between grids. In particular, the potential of smart charging is much greater in rural areas than in urban centers. Furthermore, the results suggest that curtailment of VRES production is economically only in rare circumstances.

Enabling low-voltage, peer-to-peer, quasi-real-time electricity markets through consortium blockchains

Variable renewable energy sources are continuously increasing their share in the world energy mix. However, their uncertainty has a deep impact in the electric grid safe operation. One of the most promising solutions to tackle such challenge at a distribution grid level consists of quasi-real-time, peer-to-peer electricity markets. These can use the blockchain to be successfully implemented in a secure and privacy preserving way, making effective use of the increasing intelligence of Internet of Things appliances. Nevertheless, providing blockchain-based solutions compatible with the energy sector is not an easy task. In particular, in order to be compliant with typical electricity costs of the order of some €cents/kWh, blockchain transactions are required to be very cheap. Unfortunately, none of the existing research works took the issue of transaction costs into account. As a result, real-world feasibility of existing solutions is rather to be investigated. In this work, we propose an ad-hoc Ethereum-based consortium blockchain explicitly addressing this issue. Leveraging on this platform, we design a blockchain-based electricity market. The market consists of two-steps. The first (day-ahead) step settles the amounts and prices of the energy traded among peers. The second step is instead quasi-real-time, thus enabling the unexpected excess or lack of electricity to be directly negotiated on a peer-to-peer basis. Negotiations occurs without the need of any intermediary, except for the check of grid physical limits, performed by the distribution system operator. To demonstrate the functionality of the solution, a proof-of-concept has been implemented at the University of Pisa (Italy).

Toward a Retail Market for Distribution Grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). Proper coordination and scheduling of these DERs requires a local retail market which can operate at the distribution grid level. In this paper, we propose a retail market for optimally managing and scheduling DERs, and coordinating ancillary services in a distribution grid. Our proposed retail market leverages a recently proposed distributed proximal atomic coordination (PAC) algorithm which has several advantages over other distributed algorithms, with reduced local computational effort and enhanced privacy. We describe how the market can be implemented using a Distribution System Operator (DSO), whose representatives are located at the primary feeder level and workers are located at the substation level, and how the DSO will interact with the Wholesale Electricity Market. Finally, we extensively validate the performance of the proposed retail market via simulations of three networks: a real distribution grid in Tokyo, a balanced IEEE 123-bus distribution grid, and a modified IEEE 13-bus network. Our results show that the proposed market is practical and can be easily implemented in distribution grids, resulting in optimal real-time scheduling of DERs and compensation in the form of distributed locational marginal prices.

Ancillary Services Offered by Distributed Renewable Energy Sources at the Distribution Grid Level: An Attempt at Proper Definition and Quantification

The gradual displacement of synchronous generators driven by conventional power plants, due to the increasing penetration of distributed renewable energy sources (DRES) in distribution grids, is creating a shortage of crucial ancillary services (AS) which are vital for the frequency and voltage stability of the grid. These AS, and some new ones, could now be offered by the DRES, particularly those that are converter interfaced, in a coordinated way in order to preserve the grid stability and resilience. Although recent standards and grid codes specify that the DRES exhibit some system support functions, there are no specifications on how to measure and quantify (M & Q) them both at DRES level and in aggregated form. The M & Q of AS is crucial, since it would allow the AS to be treated as tradable AS in the current and future AS markets. This paper attempts to define a number of AS that can be offered by converter-interfaced DRES and suggests methods for their M & Q. The new AS addressed are: (1) inertial response; (2) primary frequency response; (3) active power smoothing (ramp-rate limitation); (4) exchange of reactive power for voltage regulation; (5) fault-ride-through (FRT) and contribution to fault clearing; (6) voltage harmonic mitigation. Additionally, a rough estimation of the additional investment and operational cost, as well as the financial benefits associated with each AS is provided in order to form the basis for the development of business models around each AS in the near future.

Impact of electric vehicles: Will German households pay less for electricity?

High energy efficiencies imply that electric mobility is regarded as an important technological option to reduce greenhouse gas emissions from the transport sector. However, electric vehicles (EVs) also have impacts on electricity grids and electricity generation. Hence, this paper explores how private EVs affect residential electricity prices in Germany. We examine effects of EVs on electricity generation, the contribution of controlled charging and impacts on distribution grid grids. We show that in 2030, private EVs can reduce the electricity prices for households since at distribution grid level, the additional electricity demand increases the overall utilisation of the grid and lowers specific costs. Because the additional load of EVs leads to an increased usage of power plants with higher variable costs, there is the opposite effect on electricity generation costs, although limited by controlled charging. Overall, the effect of rising electricity generation costs is usually overcompensated by falling specific grid charges.

How decentralization drives a change of the institutional framework on the distribution grid level in the electricity sector – The case of local congestion markets

The increasing share of renewables in the electricity system results in congestion on all network levels. To address this congestion, the EU Commission proposed that distribution network operators become responsible for local congestion management. Within this paper we analyze the institutional implications of the introduction of local congestion markets (also referred to as flexibility markets) and identify three discrimination concerns related to the DSO's role on these markets. We will argue that the standard governance models (legal unbundling, ownership unbundling, IDSO) do either not sufficiently address the identified discrimination concerns, or come with additional challenges which make their application less feasible. Instead, we discuss two novel approaches: The introduction of Independent Distribution Operators (IDO) or alternatively, a Common Flexibility Platform (CFP). While the IDO results in a change of the regulatory regime in Europe, the CFP could be applied given the current European unbundling rules. Since the CFP does not require stronger unbundling of DSOs, we recommend to investigate this solution further.

Electric Vehicle–Grid Integration with Voltage Regulation in Radial Distribution Networks

In this paper, a vehicle–grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is optimally allocated for charging electric vehicles to meet charging requirements. At the distribution grid level, a distributed voltage compensation algorithm is designed to recover voltage violation when it happens at a distribution node. The voltage compensation is achieved through a negotiation between the grid-level agent and VGI microgrid agents using the alternating direction method of multipliers. In each negotiation round, individual agents pursue their own objectives. The computation can be carried out in parallel for each agent. The presented VGI control schemes are simulated and verified in a modified IEEE 37 bus distribution system. The simulation results are presented to show the effectiveness of the VGI control algorithms and the effect of algorithm parameters on the convergence of agent negotiation.

Ancillary Services Market Design in Distribution Networks: Review and Identification of Barriers

The high proliferation of converter-dominated Distributed Renewable Energy Sources (DRESs) at the distribution grid level has gradually replaced the conventional synchronous generators (SGs) of the transmission system, resulting in emerging stability and security challenges. The inherent characteristics of the SGs are currently used for providing ancillary services (ASs), following the instructions of the Transmission System Operator, while the DRESs are obliged to offer specific system support functions, without being remunerated for these functions, but only for the energy they inject. This changing environment has prompted the integration of energy storage systems as a solution for transfusing new characteristics and elaborating their business in the electricity markets, while the smart grid infrastructure and the upcoming microgrid architectures contribute to the transformation of the distribution grid. This review investigates the existing ASs in transmission system with the respective markets (emphasizing the DRESs’ participation in these markets) and proposes new ASs at distribution grid level, with emphasis to inertial response, active power ramp rate control, frequency response, voltage regulation, fault contribution and harmonic mitigation. The market tools and mechanisms for the procurement of these ASs are presented evolving the existing role of the Operators. Finally, potential barriers in the technical, regulatory, and financial framework have been identified and analyzed.

Phase-space exploration of unit ensembles in energy management

Abstract Currently, a transition of the electrical power system occurs that results in replacing large-scale thermal power plants at transmission grid level by small generation units mainly installed in the distribution grid. A shift from the transmission to the distribution grid level and an increase in ancillary service demand is a direct result of this transition, demanding delegation of liabilities to distributed, small energy resources. Decoder-based methods currently are not able to cope with ensembles of individually acting energy resources. Aggregating flexibilities results in folded distributions with unfavorable properties for machine learning decoders. Nevertheless, a combined training set is needed to integrate e. g., a hotel, a small business, or similar with an ensemble of co-generation, heat pump, solar power, or controllable consumers to a single flexibility model. Thus, we improved the training process and use evolution strategies for sampling ensembles.