Multiple Timescale Dispatch and Scheduling for Stochastic Reliability in Smart Grids with Wind Generation Integration

Integrating volatile renewable energy resources into the bulk power grid is challenging, due to the reliability requirement that at each instant the load and generation in the system remain balanced. In this study, we tackle this challenge for smart grid with integrated wind generation, by leveraging multi-timescale dispatch and scheduling. Specifically, we consider smart grids with two classes of energy users - traditional energy users and opportunistic energy users (e.g., smart meters or smart appliances), and investigate pricing and dispatch at two timescales, via day-ahead scheduling and realtime scheduling. In day-ahead scheduling, with the statistical information on wind generation and energy demands, we characterize the optimal procurement of the energy supply and the day-ahead retail price for the traditional energy users; in realtime scheduling, with the realization of wind generation and the load of traditional energy users, we optimize real-time prices to manage the opportunistic energy users so as to achieve systemwide reliability. More specifically, when the opportunistic users are non-persistent, i.e., a subset of them leave the power market when the real-time price is not acceptable, we obtain closedform solutions to the two-level scheduling problem. For the persistent case, we treat the scheduling problem as a multitimescale Markov decision process. We show that it can be recast, explicitly, as a classic Markov decision process with continuous state and action spaces, the solution to which can be found via standard techniques. We conclude that the proposed multi-scale dispatch and scheduling with real-time pricing can effectively address the volatility and uncertainty of wind generation and energy demand, and has the potential to improve the penetration of renewable energy into smart grids.Comment: Submitted to IEEE Infocom 2011. Contains 10 pages and 4 figures. Replaces the previous arXiv submission (dated Aug-23-2010) with the same titl

Scheduling of Multicast and Unicast Services under Limited Feedback by using Rateless Codes

Many opportunistic scheduling techniques are impractical because they require accurate channel state information (CSI) at the transmitter. In this paper, we investigate the scheduling of unicast and multicast services in a downlink network with a very limited amount of feedback information. Specifically, unicast users send imperfect (or no) CSI and infrequent acknowledgements (ACKs) to a base station, and multicast users only report infrequent ACKs to avoid feedback implosion. We consider the use of physical-layer rateless codes, which not only combats channel uncertainty, but also reduces the overhead of ACK feedback. A joint scheduling and power allocation scheme is developed to realize multiuser diversity gain for unicast service and multicast gain for multicast service. We prove that our scheme achieves a near-optimal throughput region. Our simulation results show that our scheme significantly improves the network throughput over schemes employing fixed-rate codes or using only unicast communications

Energy-Optimal Scheduling in Low Duty Cycle Sensor Networks

Energy consumption of a wireless sensor node mainly depends on the amount of time the node spends in each of the high power active (e.g., transmit, receive) and low power sleep modes. It has been well established that in order to prolong node's lifetime the duty-cycle of the node should be low. However, low power sleep modes usually have low current draw but high energy cost while switching to the active mode with a higher current draw. In this work, we investigate a MaxWeightlike opportunistic sleep-active scheduling algorithm that takes into account time- varying channel and traffic conditions. We show that our algorithm is energy optimal in the sense that the proposed ESS algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Simulation studies are provided to confirm the theoretical results

Exploiting Spatial Interference Alignment and Opportunistic Scheduling in the Downlink of Interference Limited Systems

In this paper we analyze the performance of single stream and multi-stream spatial multiplexing (SM) systems employing opportunistic scheduling in the presence of interference. In the proposed downlink framework, every active user reports the post-processing signal-to-interference-plus-noise-power-ratio (post-SINR) or the receiver specific mutual information (MI) to its own transmitter using a feedback channel. The combination of scheduling and multi-antenna receiver processing leads to substantial interference suppression gain. Specifically, we show that opportunistic scheduling exploits spatial interference alignment (SIA) property inherent to a multi-user system for effective interference mitigation. We obtain bounds for the outage probability and the sum outage capacity for single stream and multi stream SM employing real or complex encoding for a symmetric interference channel model. The techniques considered in this paper are optimal in different operating regimes. We show that the sum outage capacity can be maximized by reducing the SM rate to a value less than the maximum allowed value. The optimum SM rate depends on the number of interferers and the number of available active users. In particular, we show that the generalized multi-user SM (MU SM) method employing real-valued encoding provides a performance that is either comparable, or significantly higher than that of MU SM employing complex encoding. A combination of analysis and simulation is used to describe the trade-off between the multiplexing rate and sum outage capacity for different antenna configurations

Opportunistic Interference Mitigation Achieves Optimal Degrees-of-Freedom in Wireless Multi-cell Uplink Networks

We introduce an opportunistic interference mitigation (OIM) protocol, where a user scheduling strategy is utilized in $K$-cell uplink networks with time-invariant channel coefficients and base stations (BSs) having $M$ antennas. Each BS opportunistically selects a set of users who generate the minimum interference to the other BSs. Two OIM protocols are shown according to the number $S$ of simultaneously transmitting users per cell: opportunistic interference nulling (OIN) and opportunistic interference alignment (OIA). Then, their performance is analyzed in terms of degrees-of-freedom (DoFs). As our main result, it is shown that $KM$ DoFs are achievable under the OIN protocol with $M$ selected users per cell, if the total number $N$ of users in a cell scales at least as $\text{SNR}^{(K-1)M}$. Similarly, it turns out that the OIA scheme with $S$($<M$) selected users achieves $KS$ DoFs, if $N$ scales faster than $\text{SNR}^{(K-1)S}$. These results indicate that there exists a trade-off between the achievable DoFs and the minimum required $N$. By deriving the corresponding upper bound on the DoFs, it is shown that the OIN scheme is DoF optimal. Finally, numerical evaluation, a two-step scheduling method, and the extension to multi-carrier scenarios are shown.Comment: 18 pages, 3 figures, Submitted to IEEE Transactions on Communication