852665
Location-based scheduling and pricing for energy and reserves: a responsive reserve market proposal
It is well known that given a network that can become constrained on voltage or real power flows, reserves must also be spatially located in order to handle all credible contingencies. However, to date, there is no credible science-based method for assigning and pricing reserves in this way. Presented in this paper is a responsive-reserve scheduling algorithm incorporating constraints imposed by grid security considerations, which include one base case (intact system) and a list of credible contingencies (line out, unit lost, and load growth) of the system. By following a cost-minimizing co-optimization procedure, both power and reserves are allocated spatially for the combined energy and reserve markets. With the Lagrange multipliers obtained, the scheduling algorithm also reveals the locational shadow prices for the reserve and energy requirements. Unlike other pricing and scheduling methods in use, which are usually ad hoc and are based on engineering judgment and experience, this proposed formulation is likely to perform better in restructured markets when market power is a potential problem. An illustrative example of a modified IEEE 30-bus system is used to introduce concepts and present results.
6798576
Locational pricing and scheduling for an integrated energy-reserve market
It is well known that given a network that can become constrained on voltage or real power flows, reserves must also be spatially located in order to handle all credible contingencies. However, to date, there is no credible science-based method for assigning and pricing reserves in this way. Presented in this paper is a new scheduling algorithm incorporating constraints imposed by grid security considerations, which include one base case (intact system) and a list of possible contingencies (line-out, unit-lost, and load-growth) of the system. By following a cost-minimizing co-optimization procedure, both power and reserve are allocated spatially for the combined energy and reserve markets. With the Lagrange multipliers (dual variables) obtained, the scheduling algorithm also reveals the locational shadow prices for the reserve and energy requirements. Unlike other pricing and scheduling methods in use, which are usually ad-hoc and are based on engineering judgment and experience, this proposed formulation is likely to perform better in restructured markets when market power is a potential problem. An illustrative example of a modified IEEE 30-bus system is used to introduce concepts and present results.
35963439
A counter-example to a clustering heuristic
40634947
Experiments Study on a Dynamic Priority Scheduling for Wireless Sensor Networks
Wireless Sensors Networks (WSNs) represent a new generation of embedded systems, which deploy wireless ad hoc communication mechanisms to route a sensory data from the originator sensor node to the base station. One of the most important issues in wireless sensor networks is to support real-time QoS, which is fundamentally a challenging problem. In this paper, we introduce EDBP scheduling algorithm for sensor network along with a MAC protocol based on the dynamic priority assignment EDBP. Two different platforms based experiment projects are designed to test our proposal.
26523507
MeSwarm: memetic particle swarm optimization
In this paper, a novel variant of particle swarm optimization (PSO), named memetic particle swarm optimization algorithm (MeSwarm), is proposed for tackling the overshooting problem in the motion behavior of PSO. The overshooting problem is a phenomenon in PSO due to the velocity update mechanism of PSO. While the overshooting problem occurs, particles may be led to wrong or opposite directions against the direction to the global optimum. As a result, MeSwarm integrates the standard PSO with the Solis and Wets local search strategy to avoid the overshooting problem and that is based on the recent probability of success to efficiently generate a new candidate solution around the current particle. Thus, six test functions and a real-world optimization problem, the flexible protein-ligand docking problem are used to validate the performance of MeSwarm. The experimental results indicate that MeSwarm outperforms the standard PSO and several evolutionary algorithms in terms of solution quality.
12533129
Procrastination for leakage-aware rate-monotonic scheduling on a dynamic voltage scaling processor
As the dynamic voltage scaling (DVS) technique provides system engineers the flexibility to trade-off the performance and the energy consumption, DVS has been adopted in many computing systems. However, the longer a job executes, the more energy in the leakage current the device/processor consumes for the job. To reduce the energy consumption resulting from the leakage current, a system might enter the dormant mode. This paper targets energy-efficient rate-monotonic scheduling for periodic real-time tasks on a uniprocessor DVS system with non-negligible leakage power consumption. An on-line simulated scheduling strategy and a virtually blocking time strategy are developed for procrastination scheduling to reduce energy consumption. The proposed algorithms derive a feasible schedule for real-time tasks with worst-case guarantees for any input instance. Experimental results show that our proposed algorithms could derive energy-efficient solutions.
10853556
A robust watermarking method based on wavelet and Zernike transform
As watermarking is increasingly applied for a variety of applications, various properties of watermarks, such as how they respond to common signal transformations or deliberate attacks, have become important concerns. In this paper, we propose a new approach to embed a watermark that is to modify the block average in wavelet domain. If the watermarked image has been attacked by geometric ways, we can figure it out by Zernike transform and then retrieve it. Experiments prove that the method is not only robust to geometric attacks, but also to JPEG and Checkmark attacks.