Abstract
This paper proposes a model to determine the optimasize of an energy storage facility from a strategic investor’s perspective. This investor seeks to maximize its profit through making strategic planning, i.e., storage sizing, and strategic operational, i.e., offering and bidding, decisions. We consider the uncertainties associated with rival generators’ offering strategies and future load levels in the proposed model. The strategic investment decisions include the sizes of charging device, discharging device and energy reservoir. The proposed model is a stochastic bi-level optimization problem; the planning and operation decisions are made in the upper-level, and market clearing is modeled in the lower-level under different operating scenarios. To make the proposed model computationally tractable, an
iterative solution technique based on Benders’ decomposition is implemented. This provides a master problem and a set of subproblems for each scenario. Each subproblem is recast as an
Mathematical Programs with Equilibrium Constraints (MPEC). Numerical results based on real-life market data from Alberta’s electricity market are provided.
iterative solution technique based on Benders’ decomposition is implemented. This provides a master problem and a set of subproblems for each scenario. Each subproblem is recast as an
Mathematical Programs with Equilibrium Constraints (MPEC). Numerical results based on real-life market data from Alberta’s electricity market are provided.
Original language | English |
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Journal | IEEE Transactions on Sustainable Energy |
Volume | 7 |
Issue number | 4 |
Pages (from-to) | 1462-1472 |
Number of pages | 11 |
ISSN | 1949-3029 |
DOIs | |
Publication status | Published - 2016 |
Keywords
- Energy Storage
- Planning
- Bidding strategy
- Benders’ decomposition
- Mathematical Programs with Equilibrium Constraints (MPEC)