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5. Rank-Aware Dynamic Migrations and Adaptive Demotions for DRAM Power Management

Author

Lu, Yanchao, Wu, Donghong, He, Bingsheng, Tang, Xueyan, Xu, Jianliang, and Guo, Minyi

Subjects
Computer Science - Performance, Computer Science - Hardware Architecture, Computer Science - Operating Systems, B.3.2
Abstract

Modern DRAM architectures allow a number of low-power states on individual memory ranks for advanced power management. Many previous studies have taken advantage of demotions on low-power states for energy saving. However, most of the demotion schemes are statically performed on a limited number of pre-selected low-power states, and are suboptimal for different workloads and memory architectures. Even worse, the idle periods are often too short for effective power state transitions, especially for memory intensive applications. Wrong decisions on power state transition incur significant energy and delay penalties. In this paper, we propose a novel memory system design named RAMZzz with rank-aware energy saving optimizations including dynamic page migrations and adaptive demotions. Specifically, we group the pages with similar access locality into the same rank with dynamic page migrations. Ranks have their hotness: hot ranks are kept busy for high utilization and cold ranks can have more lengthy idle periods for power state transitions. We further develop adaptive state demotions by considering all low-power states for each rank and a prediction model to estimate the power-down timeout among states. We experimentally compare our algorithm with other energy saving policies with cycle-accurate simulation. Experiments with benchmark workloads show that RAMZzz achieves significant improvement on energy-delay2 and energy consumption over other energy saving techniques., Comment: 19 pages

Published
2014

8. A comprehensive energy system optimization method considering variable operating condition characteristics of equipment

Author

Wang Yongli, Yao Suhang, Tao Siyi, Ma Yuze, and Lu Yanchao

Subjects
Environmental sciences, GE1-350
Abstract

The economy of the Regional Integrated Energy System (RIES) scheduling scheme is affected by the parameter accuracy of different energy conversion equipment models. The traditional static energy hub (EH) model regards the equipment efficiency as a constant and ignores the variable condition characteristics of the equipment efficiency changing with the load rate. This paper presents an optimal scheduling method of RIES considering the characteristics of equipment under variable operating conditions. Firstly, the architecture of the integrated energy system is analyzed. Secondly, based on the DEH model, an optimal scheduling method of RIES was proposed considering the characteristics of equipment under variable operating conditions. Finally, an optimal scheduling analysis is performed for a typical RIs. The results show that the proposed method can improve the accuracy of the equipment model and reduce the cost prediction error by considering the variable operating conditions of the equipment, thus providing a more economical scheduling scheme for Ries.

Published
2021
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9. Forecast of Power Grid Investment Scale Based on Support Vector Machine

Author

Wang Yongli, Lu Yanchao, Wang Jingyan, Wang Xiaohui, Wang Shuo, and Xue Lu

Subjects
Environmental sciences, GE1-350
Abstract

Economic transformation creates a new environment for grid investment. In the situation of high quality development, the traditional investment scale prediction model is no longer applicable. Aiming at the problems of single parameter of grid-driven investment scale prediction model and poor linear fitting accuracy, a provincial medium- and long-term investment scale prediction model based on support vector machine was proposed. Aiming at the single parameter and poor line fitting accuracy of the grid-driven investment scale prediction model under the new situation, the new environment, new directions and new requirements for grid investment are analyzed. Based on the support vector machine algorithm, a medium-and long-term investment scale prediction model for provincial grids based on support vector machines is proposed. The scale of provincial grid investment is expected from 2019 to 2022. The empirical results show that the prediction model constructed in this paper is effective and feasible. It is of great significance to explore the prediction model of medium and long-term investment scale of power grid enterprises in the new situation.

Published
2020
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15. Coordinated Optimization Model of Planning and Operation of Integrated Energy System Based on Mixed Integer Programming

Author

Yaqiong Liu, Lu Yanchao, Xiaohui Wang, and Xu Nan

Subjects
Mathematical optimization, Computer science, Integrated energy system, Integer programming
Abstract

In recent years, the planning and operation of integrated energy system has received extensive attention. The traditional two-stage nonlinear model of planning and operation has problems such as inability to reach the global optimum and low solution efficiency. By linearizing the nonlinear constraints, this paper introduces a coordinated optimization model of planning and operation of integrated energy system based on mixed integer programming, which takes the minimum annual cost as the objective function and considers the coupling characteristics of electrical, thermal, and cooling load. The model achieves the optimal capacity configuration and operating scheme at the same time. Results of the testing data verify the effectiveness of the model.

Published
2020

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