Future Distribution Grids Research Articles

Leveraging Prosumer Flexibility to Mitigate Grid Congestion in Future Power Distribution Grids

Leveraging Prosumer Flexibility to Mitigate Grid Congestion in Future Power Distribution Grids

Blockchain-Based Renewable Energy Certificate Trade for Low-Carbon Community of Active Energy Agents

The future distribution grid is a peer-to-peer (P2P) community formed by a large number of active energy agents (AEAs), and renewable energy certificate (REC) trading is an efficient way to realize a low-carbon AEA community. AEAs can trade not only electricity but also RECs among themselves to economically and efficiently meet the renewable portfolio standard (RPS) requirements. Aiming to lower the market barrier and increase the trading benefits for market participants, this paper proposes a blockchain-based renewable energy certificate (BCREC) that supports divisible and multiple transactions. The trade process includes four stages: setup, pre-transaction, transaction, and post-transaction. A scheme based on blockchain oracles and smart contracts is implemented to achieve decentralized BCREC issuance and transaction and to support a more flexible trading market. By exploring two typical market scenarios, we verify the advantages of BCREC trading and evaluate its impacts on AEA profits and market efficiency.

Distribution network voltage analysis with data-driven electric vehicle load profiles

The number of electric vehicles (EVs) is expected to increase significantly in the near future, which will affect the operation of future power networks. This study investigates the impact of EVs on the distribution network voltage profile by collecting measurements from residential, slow commercial, and fast public EV charging stations throughout the annual cycle. It is revealed from the data that annual utilization factors for residential, slow commercial, and fast public charging stations are 89%, 55%, and 24%, respectively. The optimal power flow solutions have been presented without the EV and with EV (home, commercial, and public) load profiles. Simulation results identify the voltage violation's extent, instant, and duration that may affect the future distribution grid. Most voltage violations happen in the evening, weekday afternoon, and midday for residential, slow commercial, and fast public EV charging stations, respectively. Furthermore, multiple enabling technologies have been demonstrated to reduce voltage violations, such as coordinated charging (reduced voltage violation by 50%), renewable charging (by 50%), and combinations of multiple types of customers (by 30%). This study presents some key insights into future power system operational scenarios with widespread EV charging stations that can be managed by multiple enabling technologies.

Assessing the grid impact of Electric Vehicles, Heat Pumps & PV generation in Dutch LV distribution grids

Low Carbon Technologies (LCTs), such as Photovoltaics (PVs), Electric Vehicles (EVs), and Heat Pumps (HPs), are expected to cause a huge electric load in future distribution grids. This paper investigates the grid impact in terms of over-loading and nodal voltage deviations in different distribution grids due to increasing LCT penetrations. The major objectives are the identification of the most severe LCT, grid impact issue, seasonal effect, and vulnerable distributional area, considering the physical models of the LCTs. It is concluded that Winter is the most hazardous for the future grid impact, characterized by nearly 3 times higher over-loading and 2.5 times higher voltage deviations during high HP penetrations, while suburban areas are the most vulnerable. Moreover, while HPs seem to have, in general, a greater impact compared to EVs, EVs cause more prolonged violations. While this work follows a bottom-up approach, using detailed physical models, aggregated national data has also been acquired, which is often used by top-down approaches. Different grid impact issues have been compared for the two approaches in terms of magnitude and duration. While bottom-up approaches generate more pessimistic results regarding the magnitude of the violations, results about the duration of the violations can be contradictory.

Coordinating distributed energy resources for reliability can significantly reduce future distribution grid upgrades and peak load

Coordinating distributed energy resources for reliability can significantly reduce future distribution grid upgrades and peak load

A novel control scheme for load current components sharing improvement, and unbalanced and harmonic voltage compensation, in islanded provisional-microgrids

Microgrids (MGs) are the building blocks of future smart distribution grids, bringing several benefits to both utilities and consumers. In recent years a new class of MGs has been introduced, called provisional-microgrid (P-MG), consisting of master-MG and slave-MG. Slave-MG cannot operate isolated from master-MG. However, power quality is of the major challenges in MG investigations. In this study, a novel hierarchical and distributed control scheme is proposed for the improvement of unbalanced and harmonic load current components sharing among the distributed generation (DG) units as well as voltage quality (VQ) enhancement of sensitive load bus (SLB) in provisional-microgrid. Compared to the previous works, the proposed control strategy takes the instantaneous free capacity of DGs and multi-voltage-quality level (MVQL) indices of different buses into account for both load current sharing and voltage quality improvement functions. Furthermore, it considers the nature of variable power generation-renewable energy resources (VPG-RERs) and does not need any information about the loads or lines impedances. The efficiency of the proposed control scheme is evaluated by simulation of a typical islanded P-MG under several cases. Simulations are carried out in MATLAB/Simulink environment, and their results demonstrate the appropriate speed and accuracy of the presented method.

A Decentralized Blockchain-Based Energy Market for Citizen Energy Communities

Despite the fact that power grids have been planned and utilized using centralized networks for many years, there are now significant changes occurring as a result of the growing number of distributed energy resources, the development of energy storage systems and devices, and the increased use of electric vehicles. In light of this development, it is pertinent to ask what an efficient approach would be to the operation and management of future distribution grids consisting of millions of distributed and even mobile energy elements. Parallel to this evolution in power grids, there has been rapid growth in decentralized management technology due to the development of relevant technologies such as blockchain networks. Blockchain is an advanced technology that enables us to answer the question raised above. This paper introduces a decentralized blockchain network based on the Hyperledger Fabric framework. The proposed framework enables the formation of local energy markets of future citizen energy communities (CECs) through peer-to-peer transactions. In addition, it is designed to ensure adequate load supply and observe the network’s constraints while running an optimal operation point by consensus among all of the players in a CEC. An open-source tool in Python is used to verify the performance of the proposed framework and compare the results. Through its distributed and layered management structure, the proposed blockchain-based framework proves its superior flexibility and proper functioning. Moreover, the results show that the proposed model increases system performance, reduces costs, and reaches an operating point based on consensus among the microgrid elements.

Signaling future or historical distribution grid costs via tariffs? A welfare analysis of long-run incremental cost pricing

Signaling future or historical distribution grid costs via tariffs? A welfare analysis of long-run incremental cost pricing

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.

Research on Coordinated Control Strategy Based on DC Bus Voltage of DC Microgrid

DC microgrid is the trend of the future distribution grid. Coordinated control of different types of distributed generation units, energy storage systems, converters, and loads in the DC microgrid to ensure efficient system operation is the focus of current research on the DC microgrid. In this paper, by taking the renovation project of Liangzi Island Electric Hotel in Hubei Province as a case, a coordinated control strategy based on DC bus voltage is proposed for internal power balance and stable system operation of the DC microgrid. Firstly, the operation mode is divided according to the different working conditions of the DC microgrid. The hierarchical droop control is used to associate each operating mode with different DC bus voltage intervals. Then a multi-source coordinated strategy is proposed, and each unit switches its operation mode according to DC bus voltage to maintain bus voltage and ensure power balance. Finally, the simulation is built and run in MATLAB/Simulink to verify the feasibility of the proposed coordinated control strategy.

Integrating degradation forecasting into distribution grids’ advanced distribution management systems

Advanced distribution management systems (ADMSs) are considered tools for deploying control and management strategies to address challenges in future distribution grids populated with distributed energy resources (DERs). This work presents a framework to integrate a degradation forecasting (DF) layer into ADMSs. Based on observations of considered DERs’ degradation behaviors, a load-dependent degradation model is constructed and integrated into a dynamical Markov chain-based degradation prediction model. Multiple sources of data can be used to train the Markov prediction model, and then Evidence Theory (ET) is used to fuse predicted results from the prediction model to enhance the reliability of the prediction model. Then, the predicted results are used to adjust energy management (EM), which is a component of the ADMS concept, to abate the degradation of components with higher degradation costs. The proposed strategy is verified on the IEEE 33 bus system by numerical simulations. In addition, controller-hardware-in-the-loop (CHIL) experimentation for the proposed scheme is implemented. Both the numerical simulations and CHIL experimentation show operation cost savings for the studied system.

Decentralized, Democratized, and Decarbonized Future Electric Power Distribution Grids: A Survey on the Paradigm Shift From the Conventional Power System to Micro Grid Structures

Decentralized, Democratized, and Decarbonized Future Electric Power Distribution Grids: A Survey on the Paradigm Shift From the Conventional Power System to Micro Grid Structures

Mechanism design for decentralized peer-to-peer energy trading considering heterogeneous preferences

The bottom-up evolution of power systems demonstrates that the integrated decentralized grid is a compelling vision of the future distribution grid. Hence, the concept of fully decentralized peer-to-peer (P2P) energy markets allows the prosumers to directly trade electricity among each other and makes them one step closer to be independent from upstream generation. To this end, an appropriate market mechanism should be designed to not only the prosumers get encouraged to participate in the market but prosumers’ preferences get taken into consideration. In this paper, a fully decentralized market mechanism is designed in which the preferences of prosumers including willingness to trade green energy, trading partner’s reputation and location in the network are taken into account. Prosumers check other peers’ attributes and select the one who satisfies their preferences the most. The designed market mechanism satisfies market properties involving balanced budget, individual rationality, and Bayesian-Nash incentive compatibility. Prosumers with excess/shortage of power are motivated to individually participate in the market while preserving their privacy. Simulation results verify the effectiveness of the proposed mechanism and premiums in the matching pattern and achieving the desired outcome for prosumers over the course of a day. • A decentralized P2P energy trading considering heterogeneous preferences of prosumers. • Introducing premium coefficients to include prosumers preferences in energy trading. • Designing a budget balanced, individually rational and incentive compatible mechanism.

A Multi-Stage Planning Method for Distribution Networks Based on ARIMA with Error Gradient Sampling for Source-Load Prediction.

As the scale of distributed renewable energy represented by wind power and photovoltaic continues to expand and load demand gradually changes, the future evolution of the smart distribution network will be directly driven by both distributed generation and user demand. The smart distribution network contains a wide range of flexible resources, and its flexibility and uncertainty will bring great challenges to grid data acquisition and control feedback. To adapt to the precise control and feedback of smart distribution network access equipment under the high proportion of new energy access and to ensure the safe operation of the system, it is urgent to accelerate the study of the evolution of the future distribution grid based on the existing distribution grid. Hence, a multi-stage planning method for distribution networks based on source-load prediction is proposed in this paper. Firstly, a distribution network source-load prediction method based on the autoregressive integrated moving average model (ARIMA) and error gradient sampling is proposed, using ARIMA to predict the scale of source-load development and error gradient sampling based on the generation of source-load scenarios with error intervals. K-means is further used for scenario reduction, to explore multiple operating scenarios of China's distribution network source-load, and the unit's output forecast interval and load demand from 2021 to 2030 for typical regions are derived using rolling forecasts by combining the unit's output, end-demand and clean energy share over the years. Secondly, the planning model of distribution grid evolution in different stages is constructed to analyze the future evolution form of the distribution grid considering the distribution network's load cross-section, respectively, and to provide a development path reference for the future construction of distribution grid form in China.

Gridchain: an investigation of privacy for the future local distribution grid

As part of building the smart grid, there is a massive deployment of so-called smart meters that aggregate information and communicate with the back-end office, apart from measuring properties of the local network. Detailed measurements and communication of, e.g., consumption allows for remote billing, but also in finding problems in the distribution of power and overall to provide data to be used to plan future upgrades of the network. From a security perspective, a massive deployment of such Internet of Things (IoT) components increases the risk that some may be compromised or that collected data are used for privacy-sensitive inference of the consumption of households. In this paper, we investigate the privacy concerns regarding detailed readings of smart meters for billing purposes. We present Gridchain, a solution where households can opt-in to hide their consumption patterns and thus make Non-Intrusive Load Monitoring (NILM) more challenging. Households form groups where they can trade real consumption among themselves to achieve reported consumption that would be resistant to NILM. Gridchain is built on a publish/subscribe model and uses a permissioned blockchain to record any trades, meaning that dishonest households can be discovered and punished if they steal from other households in the group or the electricity company in the end. We implement and release a proof of concept of Gridchain and use public datasets to allow reproducibility. Our results show that even if an attacker has access to the reported electricity consumption of any member of a Gridchain group, this reported consumption is significantly far from the actual consumption to allow for a detailed fingerprint of the household activities.

Cross domain fusion in power electronics dominated distribution grids

In the near future, a drastic change in the structure of the electric grid is expected due to the increasing penetration of power electronics interfaced renewable energy sources (e.g. solar and wind), highly variable loads (e.g. electric vehicles and air conditioning) and unexpected energy demanding events (e.g. pandemics or natural disasters). Energy balancing management, voltage and frequency stability, reduced system inertia, grid resilience to fault conditions, and power quality of the supply are a few of the main challenges in the future power electronics dominated grids. Power electronics can solve these by integrating information and communication technology in new intelligent, highly reliable, and efficient devices like smart transformers. Smart transformers can increase the power flow flexibility by enabling the correct meshed-hybrid grid operations, as long as load mission and power generation profiles are known. Those profile are generally driven by heterogeneous, highly sparse and often incomplete data that belong to different domains. This article highlights the necessity of new approaches and models to identify patterns and events of interest that can serve as a common base. The resulting patterns can then be cross-fused in a common language and form the basis of further data analytics in future distribution grids.

Special Section on Power Electronics-Enabled Smart Power Distribution Grid

Economic and environmental constraints, as well as technological advancements, are reshaping the traditional view of power distribution systems. In a future distribution grid, as the number of inverter- and converter-based devices increases to more than hundreds of thousands, it is rather intuitive that the current state-of-the-art technical solutions and industry practices will no longer be effective. While tremendous progress has been made in advancing smart grid solutions, not much attention has been paid to bridging the gap between two traditionally disjointed research areas—power systems (especially distribution systems) and power electronics—that will ultimately facilitate the vision of 100% penetration of power-electronics-based distributed energy resources coming to fruition. There is a growing interest in the concepts of power electronics-enabled power systems around the world. This Special Section invites a broad spectrum of contributors (e.g., academics, researchers, engineers, consultants, market regulators and system operators, key policymakers) to define and develop the interdisciplinary technical approaches collectively. Although there are many technical challenges associated with making this vision a reality, policy, economic, and workforce issues also play a significant role. This Special Section hence concentrates on discussing various relevant topics associated with how to accommodate extremely high levels of power-electronics-based distributed energy resources to promote economic efficiency; improve social welfare; reduce energy cost; support plug-and-play of distributed renewable energy; and improve the capability, adaptability, scalability, resiliency, safety, security, and usability that our electric power distribution infrastructure can provide. The articles are authored by a diverse group of experts from academics, industry, and national laboratories around the world ( <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Fig. 1</xref> ). The guest editorial board received 120+ abstract submissions and invited 65 of them for full-paper submissions. After two-round rigorous reviews, 23 papers have been accepted for final publication. It is worth noting that this Special Section places an emphasis on addressing the mutual research interests of academics and industry. Hence, interdisciplinary research and real-world-problem-driven research topics are of particular relevance to this Special Section. The guest editorial board and IEEE PES leadership made tremendous efforts to attract authors from the industry. All the papers have gone through the same review criteria. Approximately 35% of the accepted papers are led or co-led by industry experts.

High-Frequency Ripple Injection Signals for the Effective Utilization of Residential EV Storage in Future Power Grids With Rooftop PV System

The electrification of the transport industry is expected to have a major impact on the operation of future distribution grids which includes overloading of components, voltage unbalance, and power quality issues. This article proposes a novel approach to utilize the ripple injection load control signals for the control of EV charging load, considering a large integration of PV systems in the grid. Currently, ripple injection signals are widely used by distribution network service providers around the world for control of loads such as streetlights and hot water systems. Ripple injection signals or audio frequency injection control (AFIC) signals are the applications of a high-frequency signal superimposed on the 50/60 Hz supply. The proposed control will make use of the existing infrastructure and offers a viable solution where a smart grid solution is not available. AFIC signals can be encoded in binary to carry different information, which can be used to set the maximum allowable charging rate of future charging stations or activate the vehicle-to-grid mode when necessary. This provides a method to control the EV load depending on the stochastic nature of a future grid. A multimode energy management algorithm has been proposed depending on the load consumption of a particular substation. A power flow simulation study has been used to demonstrate the efficacy of the proposed method.

Pathways for the development of future intelligent distribution grids

The next decade will bring several technical and organisational challenges to the electrical distribution grids, which are becoming an important pillar of the energy transition. Distribution system operators will play a crucial role and thus need to find innovative solutions that will prepare them for these changes. Acknowledging large differences between European distribution grids, this paper presents pathways for distribution system operators developed within the scope of the UNITED-GRID project, in close cooperation with distribution grids in the Netherlands, France and Sweden. Investment decision tools based on future scenarios and future-readiness assessment form the first step to steer the distribution system operators towards the necessary technical and digital innovations that increase the observability and controllability of the grid. Secondly, new types of business models are introduced that can be integrated into the operators’ portfolios. Thirdly, a workshop methodology is proposed to define the new internal requirements that make distribution system operators more agile to face the fast impacts of the energy transition. Case studies from the demonstration sites in the three countries are used as examples in the paper.

A Dual Distributed Optimal Energy Management Method for Distribution Grids With Electric Vehicles

Future distribution grids are expected to face an increasing penetration of electric vehicles (EVs) and heterogeneous distributed energy resources (DERs). This demands a distributed energy management (EM) to manage power generation and delivery of energy sources to maintain power quality under the impact of EV charging, to save operating costs, and to enhance resiliency. However, the global optimality of the distributed EM’s optimization problem is still an issue in existing works because of the non-convex nature of the optimization problem. In this paper, a distributed EM strategy for grid-connected distribution networks is proposed. In particular, the EM strategy is composed of two steps. In the first step, some conditions of the EM optimization task are relaxed to apply an algorithm converging to the global optimality. The results of the first step are used to reconfigure constraints of the full optimization problem in Step 2. The proposed scheme is validated by implementing the real-time controller-hardware-in-the-loop (CHIL) experimentation on the IEEE 33 bus system. To study the impact of EV charging, EV data is collected from the market and the literature to generate realistic EV load profiles to demonstrate the effectiveness of the proposed strategy on saving operating costs and maintaining power quality.