{"title":"Smart Village Load Planning Simulations in Support of Digital Energy Management for Off-grid Rural Community Microgrids","authors":"G. Prinsloo, R. Dobson, A. Mammoli","doi":"10.2174/2405463102666171122161858","DOIUrl":null,"url":null,"abstract":"In isolated rural village electrification, renewable energy resources are often the only alternative to provide sustainable energy to economically deprived isolated rural communities. In support of current alternative energy system developments, engineers use smart village based computer model design approaches. This includes desktop computer simulation modelling for renewable energy systems and smartgrid energy management systems to plan and scope village energy projects for particular technology configurations. This approach also supports design site component option appraisals before physical installation at targeted pilot sites. Disaggregated demand load data from advanced metering infrastructure is however hardly available to assist with the technical planning and design optimization for planned rural energy systems at remote rural villages. This means that logical demand load profiles for traditional rural villages have to be computer simulated. In this paper we describe the basic principles around discrete time device disaggregated rural village electrical load profile simulations suitable for experimentation with smart microgrid design, economic optimization and critical demand response analysis. The engineering simulation model incorporates physical appliance energy ratings and device-use behaviour patterns as basis for synthesising disaggregated archetypal load profiles. The simulated disaggregated load category archetypes reflect realistic disaggregated energy consumption patterns for devices in typical isolated rural villages. Computer generated rural village load time-series datasets are output in formats suitable for demand load data direct exports and imports into custom or commercial energy modelling software simulation platforms such as TRNSYS, HomerEnergy, EnergyPlan and ∗Corresponding author Email address: gerroprinsloo@sun.ac.za (Gerro Prinsloo ) Preprint submitted to Journal for Current Alternative Energy May 1, 2017 EnergyPlus. The simulated rural village demand load data can thus be used to validate numerical simulation models for newly planned smart rural village energy systems, or experimentation with economic optimization and demand response for multi-priority load control in rural smart microgrid environments.","PeriodicalId":335045,"journal":{"name":"Current Alternative Energy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Alternative Energy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/2405463102666171122161858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
In isolated rural village electrification, renewable energy resources are often the only alternative to provide sustainable energy to economically deprived isolated rural communities. In support of current alternative energy system developments, engineers use smart village based computer model design approaches. This includes desktop computer simulation modelling for renewable energy systems and smartgrid energy management systems to plan and scope village energy projects for particular technology configurations. This approach also supports design site component option appraisals before physical installation at targeted pilot sites. Disaggregated demand load data from advanced metering infrastructure is however hardly available to assist with the technical planning and design optimization for planned rural energy systems at remote rural villages. This means that logical demand load profiles for traditional rural villages have to be computer simulated. In this paper we describe the basic principles around discrete time device disaggregated rural village electrical load profile simulations suitable for experimentation with smart microgrid design, economic optimization and critical demand response analysis. The engineering simulation model incorporates physical appliance energy ratings and device-use behaviour patterns as basis for synthesising disaggregated archetypal load profiles. The simulated disaggregated load category archetypes reflect realistic disaggregated energy consumption patterns for devices in typical isolated rural villages. Computer generated rural village load time-series datasets are output in formats suitable for demand load data direct exports and imports into custom or commercial energy modelling software simulation platforms such as TRNSYS, HomerEnergy, EnergyPlan and ∗Corresponding author Email address: gerroprinsloo@sun.ac.za (Gerro Prinsloo ) Preprint submitted to Journal for Current Alternative Energy May 1, 2017 EnergyPlus. The simulated rural village demand load data can thus be used to validate numerical simulation models for newly planned smart rural village energy systems, or experimentation with economic optimization and demand response for multi-priority load control in rural smart microgrid environments.
在偏远农村电气化中,可再生能源往往是向经济贫困的偏远农村社区提供可持续能源的唯一选择。为了支持当前替代能源系统的发展,工程师们使用基于智能村庄的计算机模型设计方法。这包括可再生能源系统和智能电网能源管理系统的桌面计算机模拟建模,以规划和确定特定技术配置的村庄能源项目。该方法还支持在目标试验点物理安装之前对设计站点组件选项进行评估。然而,来自先进计量基础设施的分类需求负荷数据很难用于协助偏远农村规划的农村能源系统的技术规划和设计优化。这意味着传统农村的逻辑需求负荷概况必须通过计算机模拟。在本文中,我们描述了离散时间设备分解农村村庄电力负荷剖面模拟的基本原理,适用于智能微电网设计,经济优化和关键需求响应分析的实验。工程仿真模型结合了物理设备能量等级和设备使用行为模式,作为综合分解原型负载概况的基础。模拟的分解负荷类别原型反映了典型孤立农村设备的实际分解能耗模式。计算机生成的农村负荷时间序列数据集以适合需求负荷数据的格式输出,直接导出和导入自定义或商业能源建模软件仿真平台,如TRNSYS, HomerEnergy, EnergyPlan和*。通讯作者电子邮件地址:gerroprinsloo@sun.ac.za (Gerro Prinsloo)预印本提交给Journal for Current Alternative energy 2017年5月1日EnergyPlus。因此,模拟的农村需求负荷数据可用于验证新规划的智能农村能源系统的数值模拟模型,或用于农村智能微电网环境下多优先级负荷控制的经济优化和需求响应实验。