A review of the tools and methods for distribution networks' hosting capacity calculation

Integration of distributed energy resources (DERs) has numerous advantages as well as some disadvantages. To safely integrate DERs into a given distribution network and to maximize their benefits, it is important to thoroughly analyze the impact of DERs on that particular network. The maximum amount of DERs that a given distribution network can accommodate without causing technical problems or without requiring infrastructure modifications is defined as the hosting capacity (HC). In this work, a review of the recent literature regarding the HC is presented. The major limiting factors of HC are found to be voltage deviation, phase unbalance, thermal overload, power losses, power quality, installation location and protection devices’ miscoordination. The studies are found to employ one of four different methods for HC calculation: (i) deterministic, (ii) stochastic, (iii) optimization-based and (iv) streamlined. Commercially available tools for HC calculation are also presented. The review concludes that the choice of tools and methods for HC calculation depends on the data available and the type of study that is to be performed

Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids

All over the world the reduction of greenhouse gas (GHG) emissions, especially in the transportation sector, becomes more and more important. Electric vehicles will be one of the key factors to mitigate GHG emissions due to their higher efficiency in contrast to internal combustion engine vehicles. On the other hand, uncoordinated charging will put more strain on electrical distribution grids and possible congestions in the grid become more likely. In this paper, we analyze the impact of uncoordinated charging, as well as optimization-based coordination strategies on the voltage stability and phase unbalances of a representative European semi-urban low voltage grid. Therefore, we model the low voltage grid as a three-phase system and take realistic arrival and departure times of the electric vehicle fleet into account. Subsequently, we compare different coordinated charging strategies with regard to their optimization objectives, e.g., cost reduction or GHG emissions reduction. Results show that possible congestion problems can be solved by coordinated charging. Additionally, depending on the objective, the costs can be reduced by more than 50% and the GHG emissions by around 40%

Fault-Tolerant Secure Data Aggregation Schemes in Smart Grids: Techniques, Design Challenges, and Future Trends

Secure data aggregation is an important process that enables a smart meter to perform efficiently and accurately. However, the fault tolerance and privacy of the user data are the most serious concerns in this process. While the security issues of Smart Grids are extensively studied, these two issues have been ignored so far. Therefore, in this paper, we present a comprehensive survey of fault-tolerant and differential privacy schemes for the Smart Gird. We selected papers from 2010 to 2021 and studied the schemes that are specifically related to fault tolerance and differential privacy. We divided all existing schemes based on the security properties, performance evaluation, and security attacks. We provide a comparative analysis for each scheme based on the cryptographic approach used. One of the drawbacks of existing surveys on the Smart Grid is that they have not discussed fault tolerance and differential privacy as a major area and consider them only as a part of privacy preservation schemes. On the basis of our work, we identified further research areas that can be explored

ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)

Restoration of an active MV distribution grid with a battery ESS: A real case study

In order to improve power system operation, Battery Energy Storage Systems (BESSs) have been installed in high voltage/medium voltage stations by Distribution System Operators (DSOs) around the world. Support for restoration of MV distribution networks after a blackout or HV interruption is among the possible new functionalities of BESSs. With the aim to improve quality of service, the present paper investigates whether a BESS, installed in the HV/MV substation, can improve the restoration process indicators of a distribution grid. As a case study, an actual active distribution network of e-distribuzione, the main Italian DSO, has been explored. The existing network is located in central Italy. It supplies two municipalities of approximately 10,000 inhabitants and includes renewable generation plants. Several configurations are considered, based on: the state of the grid at blackout time; the BESS state of charge; and the involvement of Dispersed Generation (DG) in the restoration process. Three restoration plans (RPs) have been defined, involving the BESS alone, or in coordination with DG. A MATLAB®/Simulink® program has been designed to simulate the restoration process in each configuration and restoration plan. The results show that the BESS improves restoration process quality indicators in different simulated configurations, allowing the operation in controlled island mode of parts of distribution grids, during interruptions or blackout conditions. The defined restoration plans set the priority and the sequence of controlled island operations of parts of the grid to ensure a safe and better restoration. In conclusion, the results demonstrate that a BESS can be a valuable element towards an improved restoration procedure

A SGAM-based test platform to develop a scheme for wide area measurement-free monitoring of smart grids under high PV penetration

© 2019 by the authors. In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1% by using our PV simulator under high penetration of PV with about 30% error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case

A review of PHIL testing for smart grids—selection guide, classification and online database analysis

The Smart Grid is one of the most important solutions to boost electricity sharing from renewable energy sources. Its implementation adds new functionalities to power systems, which increases the electric grid complexity. To ensure grid stability and security, systems need flexible methods in order to be tested in a safe and economical way. A promising test technique is Power Hardware In-the-Loop (PHIL), which combines the flexibility of Hardware-In-the-Loop (HIL) technique with power exchange. However, the acquisition of PHIL components usually represents a great expense for laboratories and, therefore, the setting up of the experiment involves making hard decisions. This paper provides a complete guideline and useful new tools for laboratories in order to set PHIL facilities up efficiently. First, a PHIL system selection guide is presented, which describes the selection process steps and the main system characteristics needed to perform a PHIL test. Furthermore, a classification proposal containing the desirable information to be obtained from a PHIL test paper for reproducibility purposes is given. Finally, this classification was used to develop a PHIL test online database, which was analysed, and the main gathered information with some use cases and conclusions are shown

Stochastic Operation Optimization of the Smart Savona Campus as an Integrated Local Energy Community Considering Energy Costs and Carbon Emissions

Aiming at integrating different energy sectors and exploiting the synergies coming from the interaction of different energy carriers, sector coupling allows for a greater flexibility of the energy system, by increasing renewables’ penetration and reducing carbon emissions. At the local level, sector coupling fits well in the concept of an integrated local energy community (ILEC), where active consumers make common choices for satisfying their energy needs through the optimal management of a set of multi-carrier energy technologies, by achieving better economic and environmental benefits compared to the business-as-usual scenario. This paper discusses the stochastic operation optimization of the smart Savona Campus of the University of Genoa, according to economic and environmental criteria. The campus is treated as an ILEC with two electrically interconnected multienergy hubs involving technologies such as PV, solar thermal, combined heat and power systems, electric and geothermal heat pumps, absorption chillers, electric and thermal storage. Under this prism, the ILEC can participate in the day-ahead market (DAM) with proper bidding strategies. To assess the renewables’ uncertainties, the roulette wheel method is used to generate an initial set of scenarios for solar irradiance, and the fast forward selection algorithm is then applied to preserve the most representative scenarios, while reducing the computational load of the next optimization phase. A stochastic optimization model is thus formulated through mixed-integer linear programming (MILP), with the aim to optimize the operation strategies of the various technologies in the ILEC, as well as the bidding strategies of the ILECs in the DAM, considering both energy costs and carbon emissions through a multi-objective approach. Case study results show how the optimal bidding strategies of the ILEC on the DAM allow minimizing of the users’ net daily cost, and, as in the case of environmental optimization, the ILEC operates in self-consumption mode. Moreover, in comparison to the current operation strategies, the optimized case allows reduction of the daily net energy cost in a range from 5 to 14%, and the net daily carbon emissions in a range from 6 to 18%