Cooperative Power Management Research Articles

Cooperative power management for range extended electric vehicle based on internet of vehicles

Cooperative power management for range extended electric vehicle based on internet of vehicles

Optimal Cooperative Power Management Framework for Smart Buildings Using Bidirectional Electric Vehicle Modes

The high potential for implementing demand management approaches across multiple objectives has been significantly enhanced. This study proposes a cooperative energy management strategy based on the end-user sharing of energy. The proposed method promotes the intelligent charging and discharging of EVs to achieve vehicle-to-anything (V2X) and anything-to-vehicle (X2V) operating modes for both integrated and nonrenewable residential applications. These sharing modes have already been discussed, but resolution approaches are applicable to a specific use case. Other application cases may require additional metrics to plan the fleet of electric vehicles. To avoid that problem, this study proposes the MIP method using a robust Gurobi optimiser based on a generic framework for cooperative power management (CPM). Moreover, the CPM ensures an overall target state of charge (SoC) at leaving time for all the vehicles without generating a rebound peak in total grid power, even without introducing photovoltaic power. Two different methods are proposed based on the flow direction of the EV power. The first method only includes the one-way power flow, while the second increases the two-way power flow between vehicles, operating in vehicle-to-vehicle or vehicle-to-loads modes. A thorough analysis of the findings of the proposed model was conducted to demonstrate the robustness and efficiency of the charging and discharging schedule of several EVs, favouring a sharing economy concept, reducing peak power, and increasing user comfort.

Cooperative Power Management in Energy Harvesting Communication Systems in Presence of a Helper

We investigate end-to-end throughput maximization problem for an energy harvesting (EH) single user channel in presence of an energy cooperating helper. The EH helper transfers energy to the EH battery-limited transmitter and receiver nodes. These nodes impose energy causality and energy saving constraints on the power consumption. Both of the transmitter and the receiver harvest energy from nature, and also from the helper via energy cooperation links. The EH receiver requires energy for message decoding process which is called the decoding cost. Then, based on status of the batteries at the transmitter and the receiver, five scenarios are investigated. To maximize the achievable throughput, we propose iterative directional waterfilling algorithms based on minimum and maximum constraint violations. Then as a general model, a backward iterative algorithm (based on combination of optimization in feasibility tunnel and directional waterfilling with variable minimum constraints) is presented. Finally, numerical results are presented to highlight the advantages of energy cooperating helper.

MEMCOP: memory-aware co-operative power management governor for mobile games

Modern mobile heterogeneous platforms have GPUs integrated with multicore processors to enable execution of high-end graphics-intensive games. However, these gaming applications consume significant power due to heavy utilization of CPU---GPU resources, which drains battery resources that are critical for mobile devices. While dynamic voltage and frequency scaling (DVFS) techniques have been exploited previously for dynamic power management, contemporary techniques do not fully exploit the memory access footprint for graphics-intensive gaming applications, missing opportunities for energy efficiency. In this paper, we present MEMCOP, a memory-aware cooperative CPU---GPU DVFS governor that considers both the memory access footprint as well as the CPU/GPU frequency to improve energy efficiency of high-end mobile game workloads. Our experimental results on real games and synthetic game workloads show that our MEMCOP game governor achieves on average 18 and 9% improvement of energy efficiency with minor degradation of performance compared to default governors and state-of-the-art game governors.