3,064 research outputs found
A Convex Cycle-based Degradation Model for Battery Energy Storage Planning and Operation
A vital aspect in energy storage planning and operation is to accurately
model its operational cost, which mainly comes from the battery cell
degradation. Battery degradation can be viewed as a complex material fatigue
process that based on stress cycles. Rainflow algorithm is a popular way for
cycle identification in material fatigue process, and has been extensively used
in battery degradation assessment. However, the rainflow algorithm does not
have a closed form, which makes the major difficulty to include it in
optimization. In this paper, we prove the rainflow cycle-based cost is convex.
Convexity enables the proposed degradation model to be incorporated in
different battery optimization problems and guarantees the solution quality. We
provide a subgradient algorithm to solve the problem. A case study on PJM
regulation market demonstrates the effectiveness of the proposed degradation
model in maximizing the battery operating profits as well as extending its
lifetime
Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains
We consider using a battery storage system simultaneously for peak shaving
and frequency regulation through a joint optimization framework which captures
battery degradation, operational constraints and uncertainties in customer load
and regulation signals. Under this framework, using real data we show the
electricity bill of users can be reduced by up to 15\%. Furthermore, we
demonstrate that the saving from joint optimization is often larger than the
sum of the optimal savings when the battery is used for the two individual
applications. A simple threshold real-time algorithm is proposed and achieves
this super-linear gain. Compared to prior works that focused on using battery
storage systems for single applications, our results suggest that batteries can
achieve much larger economic benefits than previously thought if they jointly
provide multiple services.Comment: To Appear in IEEE Transaction on Power System
Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets
When participating in electricity markets, owners of battery energy storage
systems must bid in such a way that their revenues will at least cover their
true cost of operation. Since cycle aging of battery cells represents a
substantial part of this operating cost, the cost of battery degradation must
be factored in these bids. However, existing models of battery degradation
either do not fit market clearing software or do not reflect the actual battery
aging mechanism. In this paper we model battery cycle aging using a piecewise
linear cost function, an approach that provides a close approximation of the
cycle aging mechanism of electrochemical batteries and can be incorporated
easily into existing market dispatch programs. By defining the marginal aging
cost of each battery cycle, we can assess the actual operating profitability of
batteries. A case study demonstrates the effectiveness of the proposed model in
maximizing the operating profit of a battery energy storage system taking part
in the ISO New England energy and reserve markets
Optimal Regulation Response of Batteries Under Cycle Aging Mechanisms
When providing frequency regulation in a pay-for-performance market,
batteries need to carefully balance the trade-off between following regulation
signals and their degradation costs in real-time. Existing battery control
strategies either do not consider mismatch penalties in pay-for-performance
markets, or cannot accurately account for battery cycle aging mechanism during
operation. This paper derives an online control policy that minimizes a battery
owner's operating cost for providing frequency regulation in a
pay-for-performance market. The proposed policy considers an accurate
electrochemical battery cycle aging model, and is applicable to most types of
battery cells. It has a threshold structure, and achieves near-optimal
performance with respect to an offline controller that has complete future
information. We explicitly characterize this gap and show it is independent of
the duration of operation. Simulation results with both synthetic and real
regulation traces are conducted to illustrate the theoretical results
Techno-Economic Analysis and Optimal Control of Battery Storage for Frequency Control Services, Applied to the German Market
Optimal investment in battery energy storage systems, taking into account
degradation, sizing and control, is crucial for the deployment of battery
storage, of which providing frequency control is one of the major applications.
In this paper, we present a holistic, data-driven framework to determine the
optimal investment, size and controller of a battery storage system providing
frequency control. We optimised the controller towards minimum degradation and
electricity costs over its lifetime, while ensuring the delivery of frequency
control services compliant with regulatory requirements. We adopted a detailed
battery model, considering the dynamics and degradation when exposed to actual
frequency data. Further, we used a stochastic optimisation objective while
constraining the probability on unavailability to deliver the frequency control
service. Through a thorough analysis, we were able to decrease the amount of
data needed and thereby decrease the execution time while keeping the
approximation error within limits. Using the proposed framework, we performed a
techno-economic analysis of a battery providing 1 MW capacity in the German
primary frequency control market. Results showed that a battery rated at 1.6
MW, 1.6 MWh has the highest net present value, yet this configuration is only
profitable if costs are low enough or in case future frequency control prices
do not decline too much. It transpires that calendar ageing drives battery
degradation, whereas cycle ageing has less impact.Comment: Submitted to Applied Energ
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