| Title | Negotiation-Based Task Scheduling and Storage Control Algorithm to Minimize User’s Electric Bills under Dynamic Prices |
| Author | Ji Li, Yanzhi Wang, Xue Lin, Shahin Nazarian, *Massoud Pedram (USC, U.S.A.) |
| Page | pp. 261 - 266 |
| Keyword | Smart Grid, Dynamic Pricing, Energy Storage, Optimization, Task Scheduling |
| Abstract | Dynamic energy pricing is a promising technique in the Smart Grid to alleviate the mismatch between electricity generation and consumption. Energy consumers are incentivized to shape their power demands, or more specifically, schedule their electricity-consuming applications (tasks) more prudently to minimize their electric bills. This has become a particularly interesting problem with the availability of residential photovoltaic (PV) power generation facilities and controllable energy storage systems. This paper addresses the problem of joint task scheduling and energy storage control for energy consumers with PV and energy storage facilities, in order to minimize the electricity bill. A general type of dynamic pricing scenario is assumed where the energy price is both time-of-use and power-dependent, and various energy loss components are considered including power dissipation in the power conversion circuitries as well as the rate capacity effect in the storage system. A negotiation-based iterative approach has been proposed for joint residential task scheduling and energy storage control that is inspired by the state-of-the-art Field-Programmable Gate Array (FPGA) routing algorithms. In each iteration, it rips-up and re-schedules all tasks under a fixed storage control scheme, and then derives a new charging/discharging scheme for the energy storage based on the latest task scheduling. The concept of congestion is introduced to dynamically adjust the schedule of each task based on the historical results as well as the current scheduling status, and a near-optimal storage control algorithm is effectively implemented by solving convex optimization problem(s) with polynomial time complexity. Experimental results demonstrate the proposed algorithm achieves up to 64.22% in the total energy cost reduction compared with the baseline methods. |
| Slides |
| Title | Many-to-Many Active Cell Balancing Strategy Design |
| Author | *Matthias Kauer, Swaminathan Narayanaswamy, Sebastian Steinhorst, Martin Lukasiewycz (TUM CREATE, Singapore), Samarjit Chakraborty (TU Munich, Germany) |
| Page | pp. 267 - 272 |
| Keyword | electromobility, cell balancing, battery management, balancing strategy |
| Abstract | In the context of active cell balancing of electric vehicle battery cells, we deal with circuit architectures for inductor-based charge transfer and the corresponding high-level modeling and strategy development.
In this work, we introduce a circuit architecture to transfer charge between arbitrarily many source and destination cells (many-to-many) for the first time and analyze the advantages over one-to-one transfer.
Balancing simulation with numerical solvers remains challenging because of non-differentiable PWM signals, while the search space for high-level strategy design -- crucial for time and energy efficiency -- becomes even larger.
Consequently, we develop a closed-form charge transfer model that extends state-of-the-art approaches and is three orders of magnitude faster than step-size controlled simulation.
With an initial algorithm design based on experimentally derived rules, we demonstrate that many-to-many transfer dominates neighbor-only approaches in speed and efficiency even though it requires only one additional switch per circuit module. |
| Title | Intra-Vehicle Network Routing Algorithm for Wiring Weight and Wireless Transmit Power Minimization |
| Author | *Ta-Yang Huang, Chia-Jui Chang (National Cheng Kung University, Taiwan), Chung-Wei Lin (University of California at Berkeley, U.S.A.), Sudip Roy (National Cheng Kung University, Taiwan), Tsung-Yi Ho (National Chiao Tung University, Taiwan) |
| Page | pp. 273 - 278 |
| Keyword | In-Vehicle Network, Routing, Power Consumption |
| Abstract | As the complexity of vehicle distributed systems increases rapidly, several hundreds of devices (sensors, actuators, etc.) are being placed in a modern automotive system.
With the increase in wiring cables connecting these devices, the weight of a car increases significantly, which degrades the fuel efficiency in driving.
In order to reduce the weight of the car, wireless communication has been introduced to replace wiring cables among some devices.
However, the extra energy consumption for packet transmissions among wireless devices requires the frequent maintenances, e.g., recharging of batteries.
In this paper, we propose an intra-vehicle network routing algorithm to simultaneously minimize the wiring weight and the transmission power for wireless communication.
Experimental results of a set of test cases show that the proposed method can effectively minimize the wiring weight and the transmit power for wireless communication. |