Optimal coordination of renewable sources and storage in energy-constrained power systems
Doctoral thesis
Permanent lenke
https://hdl.handle.net/11250/3005664Utgivelsesdato
2022Metadata
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- Institutt for elkraftteknikk [2569]
Sammendrag
Integrating high levels of variable renewable energy sources (VRESs) in power systems imperils the security of supply. Energy storage systems (ESSs) contribute both to cost reduction through increased and improved utilization of VRESs, as well as to securing the supply in periods with low generation from VRESs.
The work in this thesis has considered the modeling of microgrids (MGs), small scale power systems, with a high level of VRESs and ESSs and limited dispatchable generation capacity where VRESs and ESSs contribute to the security of supply. Although the presented work focuses on MGs, the findings are also relevant for larger systems. Since these systems rely on ESSs, where the ability to deliver power depends on a sufficiently high state-of-charge (SOC), they are vulnerable to persistent low generation from VRESs. Future generation and demand should therefore be considered in operation planning models with sufficient foresight, and for a broad range of possible scenarios.
The implemented methods include:
• A detailed non-linear battery optimization model representing the battery cell voltage and the converter efficiency with spline function based on empirical battery data. The model is capable of operating closer to the operational limits of the battery compared to existing simpler optimization models.
• A linear multi-stage stochastic power system model using stochastic dual dynamic programming (SDDP) considering degradation due to cyclic and SOC dependent calendar degradation. The model can increase the expected lifetime of a battery by more than four years. The model results also show that it is advantageous to consider battery degradation in coherence with stochastic optimization.
• A stochastic power system model using SDDP considering both short-term uncertainty within weather forecast horizon and long-term uncertainty for infinite foresight. Whereas rule-based operation and deterministic optimization causes significant load shedding in critical periods, the implemented method is superior at keeping the load shedding very low while still retaining low generation costs.
The solution of stochastic dynamic programming based methods also has a useful representation with respect to valuating stored energy for systems of any size dominated by VRESs. The value of stored energy changes in time due to variations in future expected generation and demand, and it also changes with the SOC for itself and all other ESSs in the system. The value of stored energy is a useful quantity for valuating the stored energy in detailed models, for real-time operation, and for bidding into competitive markets.
Består av
Paper 1: Aaslid, Per; Belsnes, Michael Martin; Fosso, Olav B. Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming. I: 2019 International Conference on Smart Energy Systems and Technologies - SEST. IEEE 2019 https://doi.org/10.1109/SEST.2019.8849150Paper 2: Aaslid, Per; Geth, Frederik; Korpås, Magnus; Belsnes, Michael Martin; Fosso, Olav B. Non-linear charge-based battery storage optimization model with bi-variate cubic spline constraints. Journal of Energy Storage 2020 ;Volum 32. https://doi.org/10.1016/j.est.2020.101979 - This is an open access article under the CC BY license
Paper 3: Aaslid, Per; Korpås, Magnus; Belsnes, Michael Martin; Fosso, Olav B. Pricing electricity in constrained networks dominated by stochastic renewable generation and electric energy storage. Electric power systems research 2021 ;Volum 197 https://doi.org/10.1016/j.epsr.2021.107169 - This is an open access article under the CC BY license
Paper 4: Aaslid, Per; Korpås, Magnus; Belsnes, Michael Martin; Fosso, Olav B. Stochastic Optimization of Microgrid Operation With Renewable Generation and Energy Storages. IEEE Transactions on Sustainable Energy 2022 ;Volum 13.(3) https://doi.org/10.1109/TSTE.2022.3156069
Paper 5: Aaslid, Per; Korpås, Magnus; Belsnes, Michael Martin; Fosso, Olav B. Stochastic operation of energy constrained microgrids considering battery degradation. - The final published version is available in Electric power systems research 2022 ;Volum 212. https://doi.org/10.1016/j.epsr.2022.108462 - This is an open access article under the CC BY license