Proposed Placement Strategy Research Articles

Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems

The high R/X ratio of typical distribution systems makes the system voltage vulnerable to the active power injection from distributed energy resources (DERs). Moreover, the intermittent and uncertain nature of the DER generation brings new challenges to the voltage control. This article proposes a two-stage stochastic optimization strategy to optimally place the photovoltaic (PV) smart inverters with Volt-VAr capability for distribution systems with high PV penetration to mitigate voltage violation issues. The proposed optimization strategy enables a planning-stage guide for upgrading the existing PV inverters while considering the operation-stage characteristics of the Volt-VAr control. One advantage of this planning strategy is that it utilizes the local control capability of the smart inverter that requires no communication, thus avoiding issues related to communication delays and failures. Another advantage is that the Volt-VAr control characteristic is internally integrated into the optimization model as a set of constraints, making placement decisions more accurate. The objective of the optimization is to minimize the upgrading cost and the number of the smart inverters required while maintaining the voltage profile within the acceptable range. Case studies on an actual 12.47 kV, 9-km-long Arizona utility feeder have been conducted using OpenDSS to validate the effectiveness of the proposed placement strategy in both static and dynamic simulations.

Fine-Grained Power Gating Using an MRAM-CMOS Non-Volatile Flip-Flop.

An area-efficient non-volatile flip flop (NVFF) is proposed. Two minimum-sized Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) and two magnetic tunnel junction (MTJ) devices are added on top of a conventional D flip-flop for temporary storage during the power-down. An area overhead of the temporary storage is minimized by reusing a part of the D flip-flop and an energy overhead is reduced by a current-reuse technique. In addition, two optimization strategies of the use of the proposed NVFF are proposed: (1) A module-based placement in a design phase for minimizing the area overhead; and (2) a dynamic write pulse modulation at runtime for reducing the energy overhead. We evaluated the proposed NVFF circuit using a compact MTJ model targeting an implementation in a 10 nm technology node. Results indicate that area overhead is normalized to the conventional flip flop. Compared to the best previously known NVFFs, the proposed circuit succeeded in reducing the area by and the energy by . The proposed placement strategy of the NVFF shows an improvement of nearly a factor of 2–18 in terms of area and energy, and the pulse duration modulation provides a further energy reduction depending on fault tolerance of programs.

Novel iBeacon Placement for Indoor Positioning in IoT

Indoor positioning and location estimation inside the buildings is still challenging in the Internet of Things platform. However, the GPS signals could successfully solve the outdoor localization problem. A recently introduced RSS-based device, named iBeacon , paves the way to estimate the users location inside the buildings. Due to the complexity of indoor RF environments, the positioning accuracy is affected by the placement of the iBeacons. Inadvertently, the concept of iBeacon placement for improving the accuracy remains unattended by the current research. This paper provides a comprehensive analysis and experiments on the importance of iBeacon placement, and factors impacting the beacon signal quality. Moreover, we propose a novel beacon placement strategy, Crystal-shape iBeacon Placement. As another contribution, a customized application for android is developed which is used for recording and analyzing the iBeacon signals. Our proposed placement strategy could achieve 21.7% higher precision than the existing normal iBeacon placement.

The Optimal Memory-Rate Trade-Off for the Non-Uniform Centralized Caching Problem With Two Files Under Uncoded Placement

A new scheme for the problem of centralized coded caching with non-uniform demands is proposed. The distinguishing feature of the proposed placement strategy is that it admits equal sub-packetization for all files while allowing the users to allocate more cache to the files which are more popular. This creates natural broadcasting opportunities in the delivery phase which are simultaneously helpful for the users who have requested files of different popularities. For the case of two files, we propose a new delivery strategy based on interference alignment which enables each user to decode his desired file following a two-layer peeling decoder. Furthermore, we extend the existing converse bounds for uniform demands under uncoded placement to the nonuniform case. To accomplish this, we construct $N!$ auxiliary users, corresponding to all permutations of the $N$ files, each caching carefully selected sub-packets of the files. Each auxiliary user provides a different converse bound. The overall converse bound is the maximum of all these $N!$ bounds. We prove that our achievable delivery rate for the case of two files meets this converse, thereby establishing the optimal expected memory-rate trade-off for the case of $K$ users and two files with arbitrary popularities under uncoded placement.

A distributed parallel genetic algorithm of placement strategy for virtual machines deployment on cloud platform.

The cloud platform provides various services to users. More and more cloud centers provide infrastructure as the main way of operating. To improve the utilization rate of the cloud center and to decrease the operating cost, the cloud center provides services according to requirements of users by sharding the resources with virtualization. Considering both QoS for users and cost saving for cloud computing providers, we try to maximize performance and minimize energy cost as well. In this paper, we propose a distributed parallel genetic algorithm (DPGA) of placement strategy for virtual machines deployment on cloud platform. It executes the genetic algorithm parallelly and distributedly on several selected physical hosts in the first stage. Then it continues to execute the genetic algorithm of the second stage with solutions obtained from the first stage as the initial population. The solution calculated by the genetic algorithm of the second stage is the optimal one of the proposed approach. The experimental results show that the proposed placement strategy of VM deployment can ensure QoS for users and it is more effective and more energy efficient than other placement strategies on the cloud platform.

A Cost-Effective Strategy for Road-Side Unit Placement in Vehicular Networks

In this paper, we study the Roadside Unit (RSU) placement problem in vehicular networks. We focus on the highway-like scenario in which there may be multiple lanes with exits or intersections along the road. In our model, each vehicle can access RSUs in two ways: 1) direct delivery, which occurs when the vehicle is in the transmission range of the RSUs, and 2) multi-hop relaying, which takes place when the vehicle is out of RSU transmission range. We account for both access patterns in our placement strategy and formulate this placement problem via an integer linear programming model such that the aggregate throughput in the network can be maximized. We also take into account the impact of wireless interference, vehicle population distribution, and vehicle speeds in the formulation. The performance of the proposed placement strategy is evaluated via ns-2 simulations together with VanetMobisim to generate vehicle mobility patterns. The results show that our strategy leads to the best performance as compared with the uniformly distributed placement and the hot spot placement. More importantly, our solution needs the least number of RSUs to achieve the maximal aggregate throughput in the network, indicating that our scheme is indeed a cost effective yet highly efficient placement strategy for vehicular networks.

A Force-Directed-Based Optimization Scheme for Thermal Placement Design of MCMs

Thermal management becomes exceptionally critical to both the reliability and operation performance of electronic packages, particularly for multichip modules (MCMs), as packaging and power densities continue increase while packaging dimension continues decrease. The underlying goal of the study is to pursue the minimum system temperature design of MCMs containing a number of chips of equal and/or unequal power through the optimal chip placement design. To deal with the thermal design problems, an effective indirect optimization approach that integrates a modified force-directed (FD) thermal model, a finite-element (FE) technique and an exterior penalty method (EPM) is proposed. In the modified FD thermal model, a novel representation of the repulsive and attractive forces is proposed, and the sum of these forces in the design system, representing the total system chip junction temperature, constructs the objective of the optimization problems. Together with some geometry constraints, the constrained optimization problems are formed, and furthermore, transformed into unconstrained optimization problems using an EPM. The solution of the optimization problems is sought through a direct, iterative search scheme with two proposed placement strategies. The alternative goal of the study is to address the feature and feasibility of these two proposed placement strategies for the current problems. The applicability of the proposed optimization approach is demonstrated through several design applications, and their results are extensively compared against the published data. It turns out that the current optimization approach can be very effective and robust in providing thermal optimal design of MCMs with a minimal total chip junction temperature through optimal chip placement

Simple technique for placement of meters for estimation of harmonics in electric power system

A new and simple meter-placement strategy for monitoring power system harmonic sources is proposed. The technique is easily implementable and suitable even when only a few harmonic metering locations are to be selected. The performance of the strategy in terms of estimation error has been evaluated on the IEEE 14-bus system. It is found that the estimation error of the monitored sources is small and the estimation accuracy is good. The method is also capable of identifying the presence of a new harmonic source that has not been previously present in the system. The extra, new harmonic sources are identified using a combined static state-estimation and minimum-variance technique which uses the line harmonic current measurements from the meters placed by the proposed placement strategy.