Technology Category
Reasoning under Uncertainty: Stochastic OptimizationPlanning, Routing, and Scheduling: Scheduling under UncertaintySearch and Optimization: Mixed Discrete/Continuous Search
The Theory of Storage in a Power System with Stochastic Demand
🤖 AI Summary
This paper addresses the joint optimization of energy storage system (ESS) capacity sizing and operational scheduling under stochastic electricity demand. Methodologically, it proposes a price-duration-curve-based analytical framework integrating stochastic modeling, optimization theory, and financial hedging principles. Demand uncertainty is modeled via an i.i.d. stochastic sequence; the equilibrium condition linking ESS investment and dispatch decisions is derived analytically and visualized geometrically to characterize its boundary properties. Key contributions include: (i) the first systematic characterization of the fundamental determinants of optimal ESS capacity and their explicit analytical relationship with the electricity price distribution; (ii) closed-form joint solutions for real-time dispatch and long-term capacity planning; and (iii) an optimal financial hedging contract structure explicitly tailored to stochastic demand characteristics. The framework provides an interpretable, computationally tractable theoretical foundation for ESS planning and risk management in highly volatile electricity markets.
Technology Category
Application Category
📝 Abstract
Electric power systems are increasingly turning to energy storage systems to balance supply and demand. But how much storage is required? What is the optimal volume of storage in a power system and on what does it depend? In addition, what form of hedge contracts do storage facilities require? We answer these questions in the special case in which the uncertainty in the power system involves successive draws of an independent, identically-distributed random variable. We characterize the conditions for the optimal operation of, and investment in, storage and show how these conditions can be understood graphically using price-duration curves. We also characterize the optimal hedge contracts for storage units.
Problem
Research questions and friction points this paper is trying to address.
Determining optimal energy storage volume in power systems
Identifying factors influencing storage investment and operation decisions
Designing optimal hedge contracts for energy storage facilities
Innovation
Methods, ideas, or system contributions that make the work stand out.
Optimal storage volume determined by stochastic demand
Graphical analysis using price-duration curves
Optimal hedge contracts characterized for storage units
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