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Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage using Approximate Dynamic Programming
There is growing interest in the use of grid-level storage to smooth
variations in supply that are likely to arise with increased use of wind and
solar energy. Energy arbitrage, the process of buying, storing, and selling
electricity to exploit variations in electricity spot prices, is becoming an
important way of paying for expensive investments into grid-level storage.
Independent system operators such as the NYISO (New York Independent System
Operator) require that battery storage operators place bids into an hour-ahead
market (although settlements may occur in increments as small as 5 minutes,
which is considered near "real-time"). The operator has to place these bids
without knowing the energy level in the battery at the beginning of the hour,
while simultaneously accounting for the value of leftover energy at the end of
the hour. The problem is formulated as a dynamic program. We describe and
employ a convergent approximate dynamic programming (ADP) algorithm that
exploits monotonicity of the value function to find a revenue-generating
bidding policy; using optimal benchmarks, we empirically show the computational
benefits of the algorithm. Furthermore, we propose a distribution-free variant
of the ADP algorithm that does not require any knowledge of the distribution of
the price process (and makes no assumptions regarding a specific real-time
price model). We demonstrate that a policy trained on historical real-time
price data from the NYISO using this distribution-free approach is indeed
effective.Comment: 28 pages, 11 figure
Kleinberg Navigation in Fractal Small World Networks
We study the Kleinberg problem of navigation in Small World networks when the
underlying lattice is a fractal consisting of N>>1 nodes. Our extensive
numerical simulations confirm the prediction that most efficient navigation is
attained when the length r of long-range links is taken from the distribution
P(r)~r^{-alpha}, where alpha=d_f, the fractal dimension of the underlying
lattice. We find finite-size corrections to the exponent alpha, proportional to
1/(ln N)^2
Measurements of admittances and characteristic combustion times of reactive gaseous propellant coaxial injectors
The results of an experimental investigation that was concerned with the quantitative determination of the capabilities of combustion processes associated with coaxial injectors to amplify and sustain combustor oscillations was described. The driving provided by the combustion process was determined by employing the modified standing-wave method utilizing coaxial injectors and air-acetylene mixtures. Analyses of the measured data indicate that the investigated injectors are capable of initiating and amplifying combustion instabilities under favorable conditions of injector-combustion coupling and over certain frequency ranges. These frequency ranges and the frequency at which an injector's driving capacity is maximum are observed to depend upon the equivalence ratio, the pressure drop across the injector orifices and the number of injector elements. The characteristic combustion times of coaxial injectors were determined from steady state temperature measurements
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