3,133 research outputs found
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
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
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How do Aspects of Chain Restaurants Affect the Overall Rating: Trip-Advisor Multi-dimensional Rating System Analysis
In this study, we analyze the aspect ratings and overall ratings of chain restaurants retrieved from the TripAdvisor multi-dimensional rating system. We gain aspect ratings including food aspect rating, value aspect rating, service aspect rating, and atmosphere aspect rating and their corresponding overall restaurant rating from individual reviews and each restaurant. We build three econometric models to examine how overall rating is affected and found that the food aspect has a significant positive impact on the overall rating. Another interesting finding of our analysis is that the service aspect negatively affects the overall rating. This is explainable under the chain restaurant domain because when these restaurants share the standard menu, close price range, and other similar features, service becomes the most diverse aspect for restaurants under the same brand name. When receiving good service, customers would expect other aspects of this restaurant perceived are of the same quality as the service. However, this is hard to achieve because of the similar evaluation of other aspects from the same chain. Therefore, the overall rating would decrease. In addition, we understand and interpret the value aspect of the chain restaurants. Service, food, and atmosphere ratings influence the value aspect ratings significantly and positively
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