PV systems are used more and more. Not always is it possible to install them in the optimal direction for maximum energy output over the year. At the Johan Cruijff ArenA the PV panels are placed all around the roof in all possible directions. Panels oriented to the north will have a lower energy gain than those oriented to the south. The 42 panel groups are connected to 8 electricity meters. Of these 8 energy meters monthly kWh produced are available. The first assignment is to calculate the energy gains of the 42 panel groups, and connect these in the correct way with the 8 energy meter readings, so simulated data is in accordance with measured data.Of the year 2017 there are also main electricity meter readings available for every quarter of an hour. A problem with these readings is that only absolute values are given. When electricity is taken of the grid this is a positive reading, but when there is a surplus of solar energy and electricity is delivered to the grid, this is also a positive reading. To see the effect on the electricity demand of future energy measures, and to use the Seev4-City detailed CO2 savings calculation with the electricity mix of the grid, it is necessary to know the real electricity demand of the building.The second assignment is to use the calculations of the first assignment to separate the 15 minute electricity meter readings in that for real building demand and for PV production.This document first gives information for teachers (learning goals, possible activities, time needed, further reading), followed by the assignment for students.
This research presents a case study exploring the potential for demand side flexibility at a cluster of university buildings. The study investigates the potential of a collection of various electrical devices, excluding heating and cooling systems. With increasing penetration of renewable electricity sources and the phasing out of dispatchable fossil sources, matching grid generation with grid demand will become difficult using traditional grid management methods alone. Additionally, grid congestion is a pressing problem. Demand side management in buildings may contribute to a solution to these problems. Currently demand response is, however, not yet exploited at scale. In part, this is because it is unclear how this flexibility can be translated into successful business models, or whether this is possible under the current market regime. This research gives insight into the potential value of energy demand flexibility in reducing energy costs and increasing the match between electricity demand and purchased renewable electricity. An inventory is made of on-site electrical devices that offer load flexibility and the magnitude and duration of load shifting is estimated for each group of devices. A demand response simulation model is then developed that represents the complete collection of flexible devices. This model, addresses demand response as a ‘distribute candy’ problem and finds the optimal time-of-use for shiftable electricity demand whilst respecting the flexibility constraints of the electrical devices. The value of demand flexibility at the building cluster is then assessed using this simulation model, measured electricity consumption, and data regarding the availability of purchased renewables and day-ahead spot prices. This research concludes that coordinated demand response of large variety of devices at the building cluster level can improve energy matching by 0.6-1.5% and reduce spot market energy cost by 0.4-3.2%.
Here, we delve into Demand Forecasting via Machine Learning, dissecting how to predict future demand using time-sensitive data. Westveer highlights key forecasting models, from the basic Simple Exponential Smoothing to the advanced SARIMA, applied to an electricity production dataset. The session, encapsulating the essence of data-driven forecasting, culminates in a compelling three-year predictive outlook, illustrating the transformative potential of machine learning in strategic planning and decision-making.
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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.
A fast growing percentage (currently 75% ) of the EU population lives in urban areas, using 70% of available energy resources. In the global competition for talent, growth and investments, quality of city life and the attractiveness of cities as environments for learning, innovation, doing business and job creation, are now the key parameters for success. Therefore cities need to provide solutions to significantly increase their overall energy and resource efficiency through actions addressing the building stock, energy systems, mobility, and air quality.The European Energy Union of 2015 aims to ensure secure, affordable and climate-friendly energy for EU citizens and businesses among others, by bringing new technologies and renewed infrastructure to cut household bills, create jobs and boost growth, for achieving a sustainable, low carbon and environmentally friendly economy, putting Europe at the forefront of renewable energy production and winning the fight against global warming.However, the retail market is not functioning properly. Many household consumers have too little choices of energy suppliers and too little control over their energy costs. An unacceptably high percentage of European households cannot afford to pay their energy bills. Energy infrastructure is ageing and is not adjusted to the increased production from renewables. As a consequence there is still a need to attract investments, with the current market design and national policies not setting the right incentives and providing insufficient predictability for potential investors. With an increasing share of renewable energy sources in the coming decades, the generation of electricity/energy will change drastically from present-day centralized production by gigawatt fossil-fueled plants towards decentralized generation, in cities mostly by local household and district level RES (e.g PV, wind turbines) systems operating in the level of micro-grids. With the intermittent nature of renewable energy, grid stress is a challenge. Therefore there is a need for more flexibility in the energy system. Technology can be of great help in linking resource efficiency and flexibility in energy supply and demand with innovative, inclusive and more efficient services for citizens and businesses. To realize the European targets for further growth of renewable energy in the energy market, and to exploit both on a European and global level the expected technological opportunities in a sustainable manner, city planners, administrators, universities, entrepreneurs, citizens, and all other relevant stakeholders, need to work together and be the key moving wheel of future EU cities development.Our SolutionIn the light of such a transiting environment, the need for strategies that help cities to smartly integrate technological solutions becomes more and more apparent. Given this condition and the fact that cities can act as large-scale demonstrators of integrated solutions, and want to contribute to the socially inclusive energy and mobility transition, IRIS offers an excellent opportunity to demonstrate and replicate the cities’ great potential. For more information see the HKU Smart Citieswebsite or check out the EU-website.
