Abstract
High penetrations of intermittent renewable energy resources in the power system require large balancing reserves for reliable operations. Aggregated and coordinated behind-the-meter loads can provide these fast reserves, but represent energy-constrained and uncertain reserves (in their energy state and capacity). To optimally dispatch uncertain, energy-constrained reserves, optimization-based techniques allow one to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. Therefore, this paper investigates the uncertainty associated with energy-constrained aggregations of flexible, behind-the-meter distributed energy resources (DERs). The uncertainty studied herein is associated with estimating the state of charge and the capacity of an aggregation of DERs (i.e., a virtual energy storage system or VESS). To that effect, a risk-based chance constrained control strategy is developed that optimizes the operational risk of unexpectedly saturating the VESS against deviating generators from their scheduled set-points. The controller coordinates energy-constrained VESSs to minimize unscheduled participation of and overcome ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. To illustrate the effectiveness of the proposed method, simulation-based analysis is carried out on an augmented IEEE RTS-96 network with uncertain energy resources and temperature-based dynamic line ratings.
Highlights
Conventional generators, such as fast-ramping gas generators, have provided reliable balancing reserves to meet the variability of traditional demand
This paper presents a general virtual energy storage system (VESS) model with uncertainty in both the estimate of the state of charge and the prediction of energy capacities and incorporates this uncertain VESS into a stochastic, multi-period optimal power flow (OPF) framework; (ii) by integrating uncertain energy resources with the electro-thermal coordination of line temperature dynamics, we are able to leverage the inertia and the complementary time-scales for control of both energy storage and line limits to effectively manage uncertainty and grid constraints over multiple time-steps; and (iii) with an analytical reformulation, we present a risk-based, chance-constrained model predictive control (MPC) (RB-chance constrained MPC (CC-MPC)) approach that co-optimizes the delivery of responsive VESS resources against the operational risk inherent to the VESSs’ uncertain energy capacities and states of charge
The plant model is the AC network, with line temperature computed based on the non-linear thermodynamic IEEE Standard 738 conductor temperature model to accurately capture the effects of implementing the MPC actions
Summary
Conventional generators, such as fast-ramping gas generators, have provided reliable balancing reserves to meet the variability of traditional demand. The contributions of this manuscript are the following: (i) as far as the authors are aware, prior work on stochastic optimal power flow (OPF) methods focuses mainly on the uncertainty of power injections (e.g., wind and demand), which temporally decouples the OPF problem and avoids the challenges of multiperiod optimization under uncertainty, e.g., [26, 27] Unlike those works, this paper presents a general VESS model with uncertainty in both the estimate of the state of charge and the prediction of energy capacities and incorporates this uncertain VESS into a stochastic, multi-period OPF framework; (ii) by integrating uncertain energy resources with the electro-thermal coordination of line temperature dynamics, we are able to leverage the inertia and the complementary time-scales for control of both energy storage and line limits to effectively manage uncertainty and grid constraints over multiple time-steps; and (iii) with an analytical reformulation, we present a risk-based, chance-constrained MPC (RB-CC-MPC) approach that co-optimizes the delivery of responsive VESS resources against the operational risk inherent to the VESSs’ uncertain energy capacities and states of charge.
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