With the integration of distributed renewable energy to the distribution network and the development of multiterminal flexible DC transmission technology, multiterminal flexible DC distribution network has broad application prospects. At the same time, with the rapid development of new energy vehicles, the echelon utilization of power battery has become a research hotspot. By analyzing the characteristics of flexible DC distribution network and echelon utilization battery, the structure and control strategy of modular multilevel converter (MMC), DC solid-state transformer, photovoltaic power generation, wind power generation, and echelon utilization battery energy storage system are established, respectively, in this paper. To achieve a DC network connection of various types of power supply and load, this paper proposes a starting method of multiterminal flexible DC distribution network and a cooperative control strategy of the wind-solar-storage system. A six-terminal ring-shape DC distribution network model is built in real-time digital simulation (RTDS) platform. The simulation results show that the modeling methods and control strategies of each component in the real-time simulation model meet the operation requirements of the multiterminal flexible DC distribution network, which provides a reference for the construction and research of the flexible DC distribution network.

Modern embedded processors provide hardware support for cache locking, a mechanism used to facilitate the WCET (Worst-Case Execution Time) calculation of a task. We investigate the problem of integrating task scheduling and cache locking for a set of preemptible tasks with individual release times and deadlines on a multi-core processor with two-level caches. We propose a novel integrated approach that schedules the task set and allocates the locked cache contents of each task to the local caches (L1 caches) and the level-two cache (L2 cache). Our approach consists of three major components, the task scheduler, the L1 cache allocator, and the L2 cache allocator. The task scheduler aims at minimizing the number of task preemptions. The L1 cache allocator converts the interference graph of all the tasks scheduled on each core into a DAG by considering the preemptions between tasks and allocates the L1 cache space to each task. The L2 cache allocator converts the interference graph of all the tasks into a DAG by using a k-longest-path-based graph orientation algorithm and allocates the L2 cache space to each task. Both cache allocators significantly improve the cache utilization for all the caches due to the efficient use of the interference graphs of tasks. We have implemented our approach and compared it with the extended version of the preemption tree-based approach and the static analysis approach without cache locking by using a set of benchmarks from the MRTC WCET benchmark suite and SNU real-time benchmarks. Compared to the extended version of the preemption tree-based approach, the maximum WCRT (Worst Case Response Time) improvement of our approach is 15%. Compared to the static analysis approach, the maximum WCRT improvement of our approach is 37%.

Caches have been extensively used to bridge the increasing speed gap between processors and off-chip memory. However, caches make it much harder to compute the WCET (Worst-Case Execution Time) of a program. Cache locking is an effective technique for overcoming the unpredictability problem of caches. We investigate the WCET aware D-cache locking problem for a single task, and propose two dynamic cache locking approaches. The first approach formulates the problem as a global ILP (Integer Linear Programming) problem that simultaneously selects a near-optimal set of variables as the locked cache contents and allocates them to the D-cache. The second one iteratively constructs a subgraph of the CFG of the task where the lengths of all the paths are close to the longest path length, and uses an ILP formulation to select a near-optimal set of variables in the subgraph as the locked cache contents and allocate them to the D-cache. For both approaches, we propose a novel, efficient D-cache allocation algorithm. We have implemented both approaches and compared them with the longest path-based, dynamic cache locking approach proposed in [22] and the static WCET analysis approach without cache locking proposed in [14] by using a set of benchmarks from the Mälardalen WCET benchmark suite, SNU real-time benchmarks and the benchmarks used in [27]. Compared to the static WCET analysis approach, the average WCET improvements of the first approach range between 11.3% and 31.6%, and the average WCET improvements of the second approach range between 12.3% and 32.9%. Compared to the longest path-based, dynamic cache locking approach, the average WCET improvements of the first approach range between 4.7% and 14.3%, and the average WCET improvements of the second approach range between 5.3% and 15.0%.