The economic and technical requirements of current changes in the distribution system are reflected in the use of all available resources and the activation of mechanisms for local use of flexibility. Local flexibility markets are evolving and face numerous obstacles for which appropriate solutions must be found. The local flexibility market will be complemented by the development of a local flexibility register, which will contain all relevant information about the flexibility assets necessary for the efficient operation of the local flexibility market. In this paper, interpretation and quantification of the flexibility sources location on the flexibility service in the distribution grid is given. The information is derived from power flow simulation results and finally written down in the form of line coefficients, which are determined by applying the least squares method to the power flow results. We have developed a Python-based simulator to perform the methodology to determine the information and test it on a realistic medium voltage distribution grid in Bosnia and Herzegovina. This paper confirms the approximate linearity of the active power changes on the demand side to the line load and to the voltage at the nodes for a given operating condition of the distribution grid.

The growing urban population drives implementation of smart city concept in various domains such as health, energy consumption, water management and air pollution systems. This paper describes smart city use case development utilizing FIWARE technology as an open-source efficient, standardized and secure smart city platform. While some basic details about FIWARE is provided, the paper is focused on the smart city architecture and use case development founded on this technology.

This paper describes the pilot implementation of blockchain technology (Ethereum) for smart grid data management in the IT environment of electrical distribution company Elektro Celje. The work focuses on the decentralised notation of smart meter data to enable secure access and prevent data misuse. The procedure for setting up the pilot project and the operational functions as well as the results of the performance tests are presented and discussed.

The growing penetration of renewable energy sources (RES) in the electrical power sector has increased the amount of distributed generation (DG) units connected at the distribution system level. In this context, new balancing challenges have arisen, creating the need for a novel use case methodology to enable an active role at the distribution system level such that transmission system operators (TSOs) can coordinate with distribution system operators (DSOs) with regard to connected resources for balancing purposes. In this study, the exploitation of the DSO-connected resources for balancing purposes in a market environment is proposed and evaluated via a novel business use case (BUC) methodology based on the categorization of IEC 62913-1. More specifically, in order to address different balancing market situations, two scenarios are considered with regard to the BUC. The first one represents the data exchange between the TSO, the DSO, and the balancing service provider (BSP). The second one represents an alternative scenario where data are exchanged directly between the TSO and the DSO, where the DSO also takes on the role of the BSP. The proposed BUC was also developed in order to validate the required data modeling and exchange mechanisms between DSOs and TSOs in order to exploit DSO-connected resources for overall system balancing purposes across different time scales.

The integration of renewable energy sources (RES) is an important step in the transition to a more sustainable energy system. With the development of EU energy policy, the role of the consumer is more active and recognized as a central role in this transition. One of the concepts that we have investigated is the organisation of consumers and prosumers in energy communities. This master’s thesis deals with approaches to modelling the concept of energy communities, where we chose the prosumer/consumer pair as a baseline model. With different scenarios, we analyzed how the flexibility of energy community members affects the increase of self-consumption of the energy community. Agentbased modelling represents an established approach to modelling socio-technical systems such as energy communities. The proposed models are implemented in the AnyLogic environment. By changing their flexibility and the availability of the energy storage system, we explored the possibilities for increasing the self-consumption of the energy community. With the acquired knowledge, we upgraded the baseline model into a smaller energy community aiming to achieve 100% self-consumption.

Electricity sector has been facing many changes over the last two decades due to rise in penetration of distributed energy resources that significantly affect the operations of distribution grids. Increase in intermittent electricity production from renewable energy sources, requires activating the flexibility contained in the distributed energy resources. Local electricity market as well as demand response present a mechanism to utilize this flexibility. In this paper, we analyze potentials of energy exchange within energy community created at medium voltage feeder of Elektroprivreda BH – d.d. Sarajevo. We use software tool PVSOL Premium to model prosumers and Python for the analysis of power flows and voltage conditions. As a result, we propose the energy community interaction matrix providing the information about prosumers and consumers as a foundation for automation of local energy exchange within the energy community.

This paper investigates a secure data exchange between many small distributed consumers/prosumers and the aggregator in the process of energy balancing. It addresses the challenges of ensuring data exchange in a simple, scalable, and affordable way. The communication platform for data exchange is using Ethereum Blockchain technology. It provides a distributed ledger database across a distributed network, supports simple connectivity for new stakeholders, and enables many small entities to contribute with their flexible energy to the system balancing. The architecture of a simulation/emulation environment provides a direct connection of a relational database to the Ethereum network, thus enabling dynamic data management. In addition, it extends security of the environment with security mechanisms of relational databases. Proof-of-concept setup with the simulation of system balancing processes, confirms the suitability of the solution for secure data exchange in the market, operation, and measurement area. For the most intensive and space-consuming measurement data exchange, we have investigated data aggregation to ensure performance optimisation of required computation and space usage.

One of the major goals in the European Union for reducing greenhouse gas emissions is the electrification of heat. Therefore, it is expected that the winter peak demand will rise significantly in the next few years. Demand Response could play an important role in reducing the need for network reinforcements by providing flexibility. The major motivation behind this paper is to evaluate the difference in demand flexibility between temperature-dependent consumers using electricity for heating and consumers using other energy sources. In this paper, temperature-dependent consumers are first identified by analyzing their smart metering data with machine learning. Further, the response of consumers is evaluated using probabilistic baseline models. The results show that heat electrification will increase the demand during low temperatures, whereas these consumers will also be able to offer far more flexibility during low temperatures and high demand. To the best of our knowledge, there is no empirical study, that would investigate these using state of the art methods in such detail. The paper presents part of the analyses that were carried out after the real demand response program in the scope of the Slovenian-Japanese NEDO project.

This paper presents enhanced coordination between TSOs and DSOs with regard to market related information and data infrastructures that can be developed using a cloud-based approach. The definition of use cases with regard to the levels of portal access is proposed and particular attention is given to the different time and space scales of data that is needed to provide harmonised access. The attributes of the information layer as defined in the Smart Grid Architecture Model (SGAM) are reflected in the formally defined use cases. Different access levels are demonstrated via the definition of use cases for a trusted cloud platform by considering harmonised access processes and role-based access control for security.

Smart grids growing, with deployment of the renewables in European grids, active customers and new stakeholders’ roles in electric supply requires increase of secure and reliable data exchange, using public communication infrastructures. Data classification is important by designing of the sensitive data exchange. To meet these communication needs, ENTSO-E has developed a secure, confidential, comprehensive and accessible communication and connectivity platform – ECCo SP. It is designed to function as a highly reliable and secure messaging system. The ECP platform enables near real-time data exchange, including use case “Activation of DSO-connected resources for balancing purposes in market environment”. It has been demonstrated under world conditions in Slovenia.

There has been an increasing trend of integrating photovoltaic power plants (PVs). One of the important challenges for distribution system operators is to evaluate the total installed power of a PV that a particular network can host (or PV hosting capacity) while keeping voltage and element constraints within required limits. The major drawback of the existing methods for calculating PV hosting capacity is that they use the same installed power of the PV systems for all simulated PVs, as these methods do not use external data sources about building roofs. As a consequence, this has a significant impact on the final accuracy of the results. This paper presents a probabilistic methodology for calculating the PV hosting capacity in low voltage (LV) networks. The main contribution of this paper is the improved modeling of PV generation using actual building roof data when calculating the PV hosting capacity, as every building is treated according to its actual solar potential. Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. The simulation results presented in this paper prove that the proposed methodology increases the accuracy of the final PV hosting capacity calculations.

An increased need for intensive data in support of power systems operation and market underlies the changes in the layout of the electrical networks. The availability of the data at the required time and frequency is becoming a necessity, and a model-based approach is needed to regulate the data flow and coordinate the technical and business functions between the different stakeholders in the network stating from the generation and ending at the consumption level. An energy data flow model and mechanism is provided in this paper for the data flow within the smart grid infrastructure in order to organize the integration process of the renewable energy within the existed energy utilities.