Towards a Sustainable Power Grid: Stochastic Hierarchical Planning for High Renewable Integration
Semih Atakan, Harsha Gangammanavar, and Suvrajeet Sen

TL;DR
This paper introduces a stochastic hierarchical planning framework for power systems with high renewable energy integration, addressing uncertainty at multiple timescales to improve reliability, sustainability, and economics.
Contribution
It presents an integrated stochastic hierarchical planning approach that models interactions across different operational timescales, advancing beyond previous isolated stochastic optimizations.
Findings
Operational improvements under high renewable penetration
Enhanced system reliability and sustainability
Economic benefits from adopting SHP
Abstract
Driven by ambitious renewable portfolio standards, large-scale inclusion of variable energy resources (such as wind and solar) are expected to introduce unprecedented levels of uncertainty into power system operations. The current practice of operations planning with deterministic optimization models may be ill-suited for a future with abundant uncertainty. To overcome the potential reliability and economic challenges, we present a stochastic hierarchical planning (SHP) framework. This framework captures operations at day-ahead, short-term and hour-ahead timescales, along with the interactions between the stochastic processes and decisions. In contrast to earlier studies where stochastic optimization of individual problems (e.g., unit commitment, economic dispatch) have been studied, this paper studies an integrated framework of \emph{planning under uncertainty}, where stochastic…
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Taxonomy
TopicsElectric Power System Optimization · Optimal Power Flow Distribution · Power System Reliability and Maintenance
