Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
Residential electricity distribution grid capacity is based on the typical peak load of a house and the load simultaneity factor. Historically, these values have remained predictable, but this is expected to change due to increasing electric heating using heat pumps and rooftop solar panel electricity generation. It is currently unclear how this increase in electrification will impact household peak load and load simultaneity, and hence the required grid capacity of residential electricity distribution grids. To gain better insight, transformer and household load measurements were taken in an all-electric neighborhood over a period of three years. These measurements were analyzed to determine how heat pumps and solar panels will alter peak load and load simultaneity, and hence grid capacity requirements. The impacts of outdoor effective temperature and solar panel orientation were also analyzed. Moreover, the potential for smart grids to reduce grid capacity requirements was examined.
The need for increasing further the penetration of Renewable Energy Sources (RESs) is demanding a change in the way distribution grids are managed. In particular, the RESs intermittent and stochastic nature is finding in Battery Energy Storage (BES) systems its most immediate countermeasure. This work presents a reality-based assessment and comparison of the impact of three different BES technologies on distribution grids with high RES penetration, namely Li-ion, Zn-Air and Redox Flow. To this end, a benchmark distribution grid with real prosumers’ generation and load profiles is considered, with the RES penetration purposely scaled up in such a way as to violate the grid operational limits. Then, further to the BES(s) placement on the most affected grid location(s), the impact of the three BES types is assessed considering two Use Cases: 1) Voltage & Congestion Management and 2) Peak Shaving & Energy shifting. Assessment is conducted by evaluating a set of technical Key Performance Indicators (KPIs), together with a simplified economic analysis.
The integration of renewable energy resources, controllable devices and energy storage into electricity distribution grids requires Decentralized Energy Management to ensure a stable distribution process. This demands the full integration of information and communication technology into the control of distribution grids. Supervisory Control and Data Acquisition (SCADA) is used to communicate measurements and commands between individual components and the control server. In the future this control is especially needed at medium voltage and probably also at the low voltage. This leads to an increased connectivity and thereby makes the system more vulnerable to cyber-attacks. According to the research agenda NCSRA III, the energy domain is becoming a prime target for cyber-attacks, e.g., abusing control protocol vulnerabilities. Detection of such attacks in SCADA networks is challenging when only relying on existing network Intrusion Detection Systems (IDSs). Although these systems were designed specifically for SCADA, they do not necessarily detect malicious control commands sent in legitimate format. However, analyzing each command in the context of the physical system has the potential to reveal certain inconsistencies. We propose to use dedicated intrusion detection mechanisms, which are fundamentally different from existing techniques used in the Internet. Up to now distribution grids are monitored and controlled centrally, whereby measurements are taken at field stations and send to the control room, which then issues commands back to actuators. In future smart grids, communication with and remote control of field stations is required. Attackers, who gain access to the corresponding communication links to substations can intercept and even exchange commands, which would not be detected by central security mechanisms. We argue that centralized SCADA systems should be enhanced by a distributed intrusion-detection approach to meet the new security challenges. Recently, as a first step a process-aware monitoring approach has been proposed as an additional layer that can be applied directly at Remote Terminal Units (RTUs). However, this allows purely local consistency checks. Instead, we propose a distributed and integrated approach for process-aware monitoring, which includes knowledge about the grid topology and measurements from neighboring RTUs to detect malicious incoming commands. The proposed approach requires a near real-time model of the relevant physical process, direct and secure communication between adjacent RTUs, and synchronized sensor measurements in trustable real-time, labeled with accurate global time-stamps. We investigate, to which extend the grid topology can be integrated into the IDS, while maintaining near real-time performance. Based on topology information and efficient solving of power flow equation we aim to detect e.g. non-consistent voltage drops or the occurrence of over/under-voltage and -current. By this, centrally requested switching commands and transformer tap change commands can be checked on consistency and safety based on the current state of the physical system. The developed concepts are not only relevant to increase the security of the distribution grids but are also crucial to deal with future developments like e.g. the safe integration of microgrids in the distribution networks or the operation of decentralized heat or biogas networks.
Residential electricity distribution grid capacityis based on the typical peak load of a house and the loadsimultaneity factor. Historically, these values have remainedpredictable, but this is expected to change due to increasingelectric heating using heat pumps and rooftop solar panelelectricity generation. It is currently unclear how this increasein electrification will impact household peak load and loadsimultaneity, and hence the required grid capacity of residentialelectricity distribution grids. To gain better insight, transformerand household load measurements were taken in an all-electricneighborhood over a period of three years. These measurementswere analyzed to determine how heat pumps and solar panelswill alter peak load and load simultaneity and hence gridcapacity design parameters. Moreover, the potential for smartgrids to reduce peak loads and load simultaneity, and hencereduce required grid capacities, was examined.
