635 research outputs found
An Approximately Optimal Algorithm for Scheduling Phasor Data Transmissions in Smart Grid Networks
In this paper, we devise a scheduling algorithm for ordering transmission of
synchrophasor data from the substation to the control center in as short a time
frame as possible, within the realtime hierarchical communications
infrastructure in the electric grid. The problem is cast in the framework of
the classic job scheduling with precedence constraints. The optimization setup
comprises the number of phasor measurement units (PMUs) to be installed on the
grid, a weight associated with each PMU, processing time at the control center
for the PMUs, and precedence constraints between the PMUs. The solution to the
PMU placement problem yields the optimum number of PMUs to be installed on the
grid, while the processing times are picked uniformly at random from a
predefined set. The weight associated with each PMU and the precedence
constraints are both assumed known. The scheduling problem is provably NP-hard,
so we resort to approximation algorithms which provide solutions that are
suboptimal yet possessing polynomial time complexity. A lower bound on the
optimal schedule is derived using branch and bound techniques, and its
performance evaluated using standard IEEE test bus systems. The scheduling
policy is power grid-centric, since it takes into account the electrical
properties of the network under consideration.Comment: 8 pages, published in IEEE Transactions on Smart Grid, October 201
Signal Reconstruction via H-infinity Sampled-Data Control Theory: Beyond the Shannon Paradigm
This paper presents a new method for signal reconstruction by leveraging
sampled-data control theory. We formulate the signal reconstruction problem in
terms of an analog performance optimization problem using a stable
discrete-time filter. The proposed H-infinity performance criterion naturally
takes intersample behavior into account, reflecting the energy distributions of
the signal. We present methods for computing optimal solutions which are
guaranteed to be stable and causal. Detailed comparisons to alternative methods
are provided. We discuss some applications in sound and image reconstruction
Online Algorithms for Dynamic Matching Markets in Power Distribution Systems
This paper proposes online algorithms for dynamic matching markets in power
distribution systems, which at any real-time operation instance decides about
matching -- or delaying the supply of -- flexible loads with available
renewable generation with the objective of maximizing the social welfare of the
exchange in the system. More specifically, two online matching algorithms are
proposed for the following generation-load scenarios: (i) when the mean of
renewable generation is greater than the mean of the flexible load, and (ii)
when the condition (i) is reversed. With the intuition that the performance of
such algorithms degrades with increasing randomness of the supply and demand,
two properties are proposed for assessing the performance of the algorithms.
First property is convergence to optimality (CO) as the underlying randomness
of renewable generation and customer loads goes to zero. The second property is
deviation from optimality, is measured as a function of the standard deviation
of the underlying randomness of renewable generation and customer loads. The
algorithm proposed for the first scenario is shown to satisfy CO and a
deviation from optimal that varies linearly with the variation in the standard
deviation. But the same algorithm is shown to not satisfy CO for the second
scenario. We then show that the algorithm proposed for the second scenario
satisfies CO and a deviation from optimal that varies linearly with the
variation in standard deviation plus an offset
A Minimal Incentive-based Demand Response Program With Self Reported Baseline Mechanism
In this paper, we propose a novel incentive based Demand Response (DR)
program with a self reported baseline mechanism. The System Operator (SO)
managing the DR program recruits consumers or aggregators of DR resources. The
recruited consumers are required to only report their baseline, which is the
minimal information necessary for any DR program. During a DR event, a set of
consumers, from this pool of recruited consumers, are randomly selected. The
consumers are selected such that the required load reduction is delivered. The
selected consumers, who reduce their load, are rewarded for their services and
other recruited consumers, who deviate from their reported baseline, are
penalized. The randomization in selection and penalty ensure that the baseline
inflation is controlled. We also justify that the selection probability can be
simultaneously used to control SO's cost. This allows the SO to design the
mechanism such that its cost is almost optimal when there are no recruitment
costs or at least significantly reduced otherwise. Finally, we also show that
the proposed method of self-reported baseline outperforms other baseline
estimation methods commonly used in practice
Analysis of Solar Energy Aggregation under Various Billing Mechanisms
Ongoing reductions in the cost of solar photovoltaic (PV) systems are driving
their increased installations by residential households. Various incentive
programs such as feed-in tariff, net metering, net purchase and sale that allow
the prosumers to sell their generated electricity to the grid are also powering
this trend. In this paper, we investigate sharing of PV systems among a
community of households, who can also benefit further by pooling their
production. Using cooperative game theory, we find conditions under which such
sharing decreases their net total cost. We also develop allocation rules such
that the joint net electricity consumption cost is allocated to the
participants. These cost allocations are based on the cost causation principle.
The allocations also satisfy the standalone cost principle and promote PV solar
aggregation. We also perform a comparative analytical study on the benefit of
sharing under the mechanisms favorable for sharing, namely net metering, and
net purchase and sale. The results are illustrated in a case study using real
consumption data from a residential community in Austin, Texas.Comment: 12 page
Computational Modeling of Channelrhodopsin-2 Photocurrent Characteristics in Relation to Neural Signaling
Channelrhodopsins-2 (ChR2) are a class of light sensitive proteins that offer
the ability to use light stimulation to regulate neural activity with
millisecond precision. In order to address the limitations in the efficacy of
the wild-type ChR2 (ChRwt) to achieve this objective, new variants of ChR2 that
exhibit fast mono-exponential photocurrent decay characteristics have been
recently developed and validated. In this paper, we investigate whether the
framework of transition rate model with 4 states, primarily developed to mimic
the bi-exponential photocurrent decay kinetics of ChRwt, as opposed to the low
complexity 3 state model, is warranted to mimic the mono-exponential
photocurrent decay kinetics of the newly developed fast ChR2 variants: ChETA
(Gunaydin et al., Nature Neurosci, 13:387-392, 2010) and ChRET/TC (Berndt et
al., PNAS, 108:7595-7600, 2011). We begin by estimating the parameters for the
3-state and 4-state models from experimental data on the photocurrent kinetics
of ChRwt, ChETA and ChRET/TC. We then incorporate these models into a
fast-spiking interneuron model (Wang and Buzsaki., J Neurosci,
16:6402-6413,1996) and a hippocampal pyramidal cell model (Golomb et al., J
Neurophysiol, 96:1912-1926, 2006) and investigate the extent to which the
experimentally observed neural response to various optostimulation protocols
can be captured by these models. We demonstrate that for all ChR2 variants
investigated, the 4 state model implementation is better able to capture neural
response consistent with experiments across wide range of optostimulation
protocol. We conclude by analytically investigating the conditions under which
the characteristic specific to the 3-state model, namely the mono-exponential
photocurrent decay of the newly developed variants of ChR2, can occurs in the
framework of the 4-state model.Comment: 10 figure
- …