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Scheduling of energy storage.
Stan Zachary1, Simon H Tindemans2,3, Michael P Evans4
1School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK.
Summary
Optimally scheduling diverse energy storage systems, considering their unique constraints, minimizes electricity grid imbalance. These strategies remain effective even with unpredictable energy supply and demand fluctuations.
Area of Science:
- Energy Systems Engineering
- Operations Research
- Applied Mathematics
Background:
- Growing integration of renewable energy sources necessitates advanced grid balancing solutions.
- Electricity systems face increasing complexity due to variable generation and demand.
Purpose of the Study:
- To develop optimal scheduling strategies for heterogeneous energy storage systems.
- To minimize unserved energy (imbalance) in future electricity grids.
- To ensure scheduling policy robustness in stochastic environments.
Main Methods:
- Mathematical modeling of heterogeneous energy storage systems with capacity and rate constraints.
- Optimization algorithms to determine near-optimal scheduling policies.
- Analysis of policy independence from future system states.
Main Results:
- Demonstrated methods for optimal or near-optimal scheduling of diverse storage capacities and rates.
- Quantified the minimization of total imbalance (unserved energy) over specified periods.
- Identified that optimal decisions are often independent of future supply-demand dynamics.
Conclusions:
- Heterogeneous energy storage scheduling is crucial for balancing future renewable-heavy electricity systems.
- Developed policies offer robust grid balancing, effective even under uncertainty.
- The findings contribute to the mathematical understanding of energy system management.
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