Networked microgrids (NMGs) are clusters of microgrids that are physically connected and functionally interoperable The massive and unprecedented deployment of smart grid technologies, new business models, and involvement of new stakeholders enable NMGs to be a conceptual operation paradigm for future distribution systems Much work needs to be done, however, to enable NMGs to achieve seamless coordination, including physical, communication, and functional integration In this paper, we review and summarize the state-of-the-art methodologies for operation and control of NMGs We also specifically discuss the notion of dynamic boundaries for advanced microgrid applications In addition, we introduce the opportunities, challenges, and possible solutions regarding NMGs for improving grid resilience, robustness, and efficiency

Networked Microgrids for Grid Resilience, Robustness, and Efficiency: A Review

Big data analytics for future electricity grids

Probabilistic State Forecasting and Optimal Voltage Control in Distribution Grids under Uncertainty

This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer’s individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers’ energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer’s new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

https://www.mdpi.com/1996-1073/16/3/1143/pdf?version=1674199895

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm—the Low Voltage Control (LVC)—is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

https://www.mdpi.com/2076-3417/10/7/2635/pdf

Predictive Voltage Control: Empowering Domestic Customers With a Key Role in the Active Management of LV Networks

Power systems are becoming more complex and the need for increased awareness at the lower voltage levels of the distribution grid requires new tools that provide a reliable and accurate estimation of the system state This paper describes an innovative state estimation method for low voltage (LV) grids that analyses similarities between a real-time snapshot comprising only a subset of smart meters with real-time communications and fully observed system states present in historical data Real-time estimates of voltage magnitudes are obtained by smoothing the most similar past snapshots with a data-driven methodology that does not relies on full knowledge of the grid topology and electrical characteristics Moreover, the output of the LV state estimator is a conditional probability distribution obtained with kernel density estimation The results show highly accurate estimation of voltage magnitude, even in a scenario characterized by a strong integration of photovoltaic (PV) microgeneration

/pdf/probabilistic-low-voltage-state-estimation-using-analog-1hged5kjp1.pdf

Probabilistic Low-Voltage State Estimation Using Analog-Search Techniques

This paper aims to describe the main outcomes of the ADMS4LV project which stands for Advanced Distribution Management System for Active Management of LV Grids. ADMS4LV targets the development and demonstration of a framework with adequate tools to optimize the management and operation of Low Voltage (LV) networks towards the effective implementation of Smart Grids. This work details the main functionalities of ADMS4LV and discusses their implementation. The validation of the functionalities is presented from demonstrations in a laboratorial setup, namely regarding the algorithms which using advanced data analytics, accomplish to operate LV networks with low observability, (i.e., with few real-time measurements) and without having full knowledge of the networks' technical characteristics, such as the consumers' phase connection to the grid. The assessment of the results shows the adequacy of the ADMS4LV solutions for deployment in distribution networks with current infrastructures, differing unnecessary investments in sensory devices.

On the development of a framework for the advanced monitoring of LV grids

This work presents a methodology to segment the MV electric grid into grid zones for which the active power flexibility needs that solve the forecasted voltage and current issues are computed. This methodology enables the Distribution System Operator (DSO) to publish flexibility needs per zones, allowing aggregators to offer flexibility by optimizing their portfolio of resources in each grid zone. A case study is used to support the methodology results and its performance, showing the feasibility of solving grid issues by activating flexibility per grid zones according to the proposed methodology.

Local flexibility need estimation based on distribution grid segmentation

This study presents Integrid's project framework to manage low voltage (LV) electrical networks, aiming to avoid both technical and quality constraints, induced by the ever-increasing amount of flexible resources spread all over the grid. These assets cover a large amount of renewable-based energy generation to electrical vehicles and energy storage units. For this to be possible, new advanced tools were developed to exploit the benefits of the so-called distributed energy resources, while overcoming limitations on the metering and communication infrastructures. Hence, this study describes the approach taken to perform the active management of LV networks, without a perfect level of observability, exploiting the flexibility provided by the distribution system operator's resources combined with the one offered by private consumers through the home energy management systems. Additionally, some results followed by a brief discussion are presented, enforcing the success of the developed tools. The algorithms within these tools allow to forecast both microgeneration, available flexibility and load profiles, as well as to estimate the network's state, at different time frames.

From home energy management system local flexibility to low-voltage predictive grid management

EUniversal project aims to facilitate the use of flexibility services and interlink distribution systems active management with electricity markets. Implementing market-based flexibility services implies a change in distribution network monitoring and control towards a more predictive approach. However, integrating cost-effective monitoring and control tools for the LV network is still quite challenging. Within the project, a set of operation and planning tools have been developed for a coordinated quantification and activation of flexibility in HV, MV and LV distribution networks. The paper presents the tools developed for the Portuguese pilot and shows preliminary results obtained when considering network operation scenarios characterized by large scale integration of DER and EV. 

Gil Sampaio

Papers

Probabilistic Low-Voltage State Estimation Using Analog-Search Techniques

On the development of a framework for the advanced monitoring of LV grids

Local flexibility need estimation based on distribution grid segmentation

From home energy management system local flexibility to low-voltage predictive grid management

Euniversal's smart grid solutions for the coordinated operation & planning of MV and LV networks with high EV integration