Multi-objective active network management scheme studied in Sundom smart grid with MV and LV network connected DER units

Use of controllable, flexible, distributed energy resources (DER) in MV and LV networks will be in key role in order to improve local and system-wide grid resiliency and maximize utilization of renewable energy sources (RES). These resources will provide different technical services as part of future active network management (ANM) schemes. Therefore, future ANM and protection methods and solutions have to be adapted and developed so that active control and utilization of DER during both grid-connected and islanded operation modes is enabled. In this paper, multi-objective ANM scheme is studied by PSCAD simulations during grid-connected operation of Sundom Smart Grid. Based on the simulation results conclusions are stated, for example, related to preventing unwanted MV and LV network reactive power / voltage control interactions and potential mutual effects between voltage (U) and frequency (f) control functions (QU-, PU- and Pf -control) of DER units which are actively participating on studied multi-objective ANM scheme.fi=vertaisarvioitu|en=peerReviewed

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

Impact of local energy markets integration in power systems layer: A comprehensive review

In recent years extensive research has been conducted on the development of different models that enable energy trading between prosumers and consumers due to expected high integration of distributed energy resources. Some of the most researched mechanisms include Peer-to-Peer energy trading, Community Self-Consumption and Transactive Energy Models. To ensure the stable and reliable delivery of electricity as such markets and models grow, this paper aims to understand the impact of these models on grid infrastructure, including impacts on the control, operation, and planning of power systems, interaction between multiple market models and impact on transmission network. Here, we present a comprehensive review of existing research on impact of Local Energy Market integration in power systems layer. We detect and classify most common issues and benefits that the power grid can expect from integrating these models. We also present a detailed overview of methods that are used to integrate physical network constraints into the market mechanisms, their advantages, drawbacks, and scaling potential. In addition, we present different methods to calculate and allocate network tariffs and power losses. We find that financial energy transactions do not directly reflect the physical energy flows imposed by the constraints of the installed electrical infrastructure. In the end, we identify a number of different challenges and detect research gaps that need to be addressed in order to integrate Local Energy Market models into existing infrastructure

Controller development for reactive power flow management between DSO and TSO networks

In the future, new solutions for active and reactive power control related to the flexibility services offered by distributed energy resources (DER) will be needed even more. One ancillary service which DER could provide is the reactive power flow management between DSO and TSO networks. This research aims to develop a reactive power controller from a preliminary algorithm to a light-weight IED for a wind turbine converter. The purpose of the controller is to maintain the reactive power flow of a medium voltage network within the limit set by a transmission system operator. In his paper, the controller development stages are presented - starting from the preliminary algorithm development by Simscape Power Systems to real hardware and testing it by Controller-Hardware-In-the-Loop simulations. The operation of the controller is investigated in the different development stages of the power network. The outcome is the development suggestions of the real-time simulation platform, as well as the discussion of further improvement possibilities for the controller.fi=vertaisarvioitu|en=peerReviewed

Operational Planning and Optimisation in Active Distribution Networks using Modern Intelligent Power Flow Controllers

In this paper, a centralised control framework is introduced for day-ahead operational planning of active distribution networks which accommodate high levels of distributed generation resources. The purpose of the framework is to plan network operation in order to minimise power curtailment from distributed generation and maintaining acceptable levels of voltage regulation throughout the network. For this purpose, both power flow control and rapid network reconfiguration have been considered as various acceptable levels of control available to the network operator to provide required levels of operational flexibility. The power flow control within the network is promised by the application of fully controlled back-back voltage source converters placed in key points (both normally-open and normally-close) in the network. Meanwhile, the network reconfiguration constraints guarantee that radial topology is always maintained in order to avoid tremendous changes in the protection system coordination. The operation of a modified 33-bus system exemplar is analysed in three case studies namely, passive network (base case), active network using remote-controlled switches and active network using intelligent power converters. Results show a significant saving in terms of operational costs as well as transmission losses in active cases despite the radial constraint condition in place

New dispatching paradigm in power systems including EV charging stations and dispersed generation: A real test case

Electric Vehicles (EVs) are becoming one of the main answers to the decarbonization of the transport sector and Renewable Energy Sources (RES) to the decarbonization of the electricity production sector. Nevertheless, their impact on the electric grids cannot be neglected. New paradigms for the management of the grids where they are connected, which are typically distribution grids in Medium Voltage (MV) and Low Voltage (LV), are necessary. A reform of dispatching rules, including the management of distribution grids and the resources there connected, is in progress in Europe. In this paper, a new paradigm linked to the design of reform is proposed and then tested, in reference to a real distribution grid, operated by the main Italian Distribution System Operator (DSO), e-distribuzione. First, in reference to suitable future scenarios of spread of RES-based power plants and EVs charging stations (EVCS), using Power Flow (PF) models, a check of the operation of the distribution grid, in reference to the usual rules of management, is made. Second, a new dispatching model, involving DSO and the resources connected to its grids, is tested, using an Optimal Power Flow (OPF) algorithm. Results show that the new paradigm of dispatching can effectively be useful for preventing some operation problems of the distribution grids

Design of a multi-agent system for distributed voltage regulation

In this paper, an intelligent distributed multi-agent system (MAS) is proposed for the implementation of a novel optimization technique for distributed voltage regulation. The proposed MAS approach controls a large heavily-meshed distribution network which is grouped into small subnetworks using ε decomposition. The voltage regulation is accomplished by distributed generator (DG) agents, linear programming solver (LPS) agents, network violation detector (NVD) agents, and one ε decomposition agent. The LPS agent has an embedded control algorithm which optimizes DG generation within a subnetwork once the voltage at particular nodes exceeds the normal operational limits. The subnetworks and their control requirements are achieved through self-organization, which is the novelty of the research. Each intelligent agent has its own knowledge and reasoning logic to plan its own activities. The control actions are coordinated through agent communications within the subnetwork. The agent platform, Presage2, with improved autonomy and agent communication capability, has been used to develop the proposed MAS system and design the agents’ behaviors

Responsible Knowledge Management in Energy Data Ecosystems

This paper analyzes the challenges and requirements of establishing energy data ecosystems (EDEs) as data-driven infrastructures that overcome the limitations of currently fragmented energy applications. It proposes a new data- and knowledge-driven approach for management and processing. This approach aims to extend the analytics services portfolio of various energy stakeholders and achieve two-way flows of electricity and information for optimized generation, distribution, and electricity consumption. The approach is based on semantic technologies to create knowledge-based systems that will aid machines in integrating and processing resources contextually and intelligently. Thus, a paradigm shift in the energy data value chain is proposed towards transparency and the responsible management of data and knowledge exchanged by the various stakeholders of an energy data space. The approach can contribute to innovative energy management and the adoption of new business models in future energy data spaces

Responsible Knowledge Management in Energy Data Ecosystems

This paper analyzes the challenges and requirements of establishing energy data ecosystems (EDEs) as data-driven infrastructures that overcome the limitations of currently fragmented energy applications. It proposes a new data-and knowledge-driven approach for management and process-ing. This approach aims to extend the analytics services portfolio of various energy stakeholders and achieve two-way flows of electricity and information for optimized generation, distribution, and electricity consumption. The approach is based on semantic technologies to create knowledge-based systems that will aid machines in integrating and processing resources contextually and intelligently. Thus, a paradigm shift in the energy data value chain is proposed towards transparency and the responsible management of data and knowledge exchanged by the various stakeholders of an energy data space. The approach can contribute to innovative energy management and the adoption of new business models in future energy data spaces. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Modelling battery energy storage systems for active network management : coordinated control design and validation

Control of battery energy storage systems (BESS) for active network management (ANM) should be done in coordinated way considering management of different BESS components like battery cells and inverter interface concurrently. In this paper, a detailed and accurate lithium‐ion battery model has been used to design BESS controls, thereby allowing improved overall power system control design optimisation studies by simultaneously considering both component and system‐level aspects. This model is utilised to develop a multi‐objective ANM scheme (a) to enhance utilisation of wind power generation locally by means of active power (P)‐ control of BESSs; (b) to utilise distributed energy resources (i.e. BESS and wind turbine generators) to maintain system voltage within the limits of grid code requirements by reactive power/voltage (QU)‐ and active power/voltage (PU)‐ controls. BESS control strategies to implement the ANM scheme, are designed and validated through real‐time simulation in an existing smart grid pilot, Sundom Smart Grid (SSG), in Vaasa, Finland.© 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed