A5000083847- Smart Grid Energy Management
- Electric Power System Optimization
- Integrated Energy Systems Optimization
- Microgrid Control and Optimization
- Energy Load and Power Forecasting
- Power System Reliability and Maintenance
- Monoclonal and Polyclonal Antibodies Research
- Frequency Control in Power Systems
- Energy Efficiency and Management
- Capital Investment and Risk Analysis
- Microtubule and mitosis dynamics
- Electric Vehicles and Infrastructure
- Hybrid Renewable Energy Systems
- Optimal Power Flow Distribution
- Building Energy and Comfort Optimization
Fraunhofer Institute for Energy Economics and Energy System Technology
2018-2022
Hydrogen-based energy storage has the potential to compensate for volatility of renewable power generation in systems with a high penetration. The operation these facilities can be optimized using automated management systems. This work presents Reinforcement Learning-based approach context CO2-neutral hydrogen production and an industrial combined heat application. economic performance presented is compared rule-based strategy as lower benchmark Dynamic Programming-based unit commitment...
The Electricity Supply Chain is a system of enabling procedures to optimize processes ranging from production transportation and consumption electricity. proportion distributed energy sources within the electricity increases steadily, which necessitates an improved monitoring capability ensure overall reliability quality Chain. Automation strongly required process growing amount data. Thus, it inevitable handle large amounts heterogeneous data information using forecasting optimization...
This paper analyses a flexibility market based approach to prevent grid congestions and reduce costs for feedin management. A method implementation are presented simulate this local the district Brunsbüttel in Northern Germany. The analysed introduces regional auction trade energy way that day-ahead forecasted minimised by coordinating potential of area. To quantify mechanism cosimulation was set up, using OpSim co-simulation framework. results show solves 100% at cost 74% conventional...
Energy generation and consumption in the power grid must be balanced at every single moment. Within synchronous area of continental Europe, flexible generators loads can provide Frequency Containment Reserve Restoration marketed through balancing markets. The Transmission System Operators use these flexibilities to maintain or restore frequency when there are deviations. This paper shows future flexibility potential Germany’s household sector, particular for single-family twin homes 2025...
This paper presents a new methodological approach for Unit Commitment of energy unit portfolios in the continuous intraday market using mixed integer linear programming (MILP). For Commitment, state hourly XBID at certain point time is taken into account, consisting up to 24 (independent) limit order books (LOB). The problem considers both possible selling as well its purchase example hybrid power plant. exemplary plant consists wind farm, photovoltaic park and battery storage system (BESS)....
This paper presents an approach to quantify the reliability or security level of a pool flexibility providing controllable energy units (CEUs). In this pool, backup unit secures capacity largest unit. The is then applied determine common wind farms and CEUs, making use probabilistic forecasts. advances previous research conducted in joint project with industry partners on Frequency Restoration Reserve (FRR) provision pools power plants.
Schedule deviations have become a major issue in Germany's power system recent years. This paper introduces fast local intraday market design to address this problem. It shows the concept of clearing process for 15- minute frame between closing time and delivery. shall reduce schedule deviation renewable energies increase stability. also considering grid limitations process. Hence sensitivities trading partners on are considered matching Therefore, co-simulation which includes energy...
High energy and electricity prices, coupled with high price volatility, increase the value of demand response side management. Energy management systems that are predictive exchange-price oriented can help to leverage flexibility while lowering costs. In this paper, is assessed in two scenarios low prices. To end, a self-learning home system introduced takes into account new volatility stock market The proposed approach compared baseline system, which typical household self-consumption...