Computational tools for design, analysis, and management of residential energy systems
Introduction
Power generation, transmission, distribution, and the management of current power systems has been experiencing a significant change in recent years. Both aggregated and non-aggregated renewable-energy based power generators are replacing the bulky thermal power stations. At the same time transmission and distribution systems are becoming more complex, integrating distributed energy sources and grid-connected micro grids. Various non-conventional loads and sources like electric vehicles (EVs), and battery energy-storage systems (BESSs) are becoming a common part of the grid [1], [2], [3], [4]. The future grid, alternatively known as the internet of energy (IoE), will facilitate plug-and-play features to integrate small-scale energy sources [4]. IoE customers, alternatively known as prosumers, will play the role of consumers and sellers simultaneously. Prosumers will utilize off-peak hours to store energy and sell it back during peak-load hours to optimize the electricity cost.
To get the full advantage of the energy devices and their plug-and-play capability, a robust energy-management system is necessary. Otherwise, uncontrolled loads and distributed energy sources may introduce power-quality degradation and instability to the grid. As power systems are becoming more disaggregated, it is important to manage the grid from the customers’ premises. For example, customers in a high-rise building have a higher energy demand, which can be minimized by introducing building-attached renewable sources with battery storages, thereby optimizing the power consumption. Any effective energy management at the consumer point has a benefit for both consumers and the utility. Therefore, researches in residential energy systems, their economy, management and optimization are getting significant for power systems.
In residential-energy-systems research, the most common areas are load modeling and control, renewable energy integration, energy optimization, energy cost analysis, power quality analysis, home-to-grid (H2G) bidirectional energy transfer analysis, and electrical protection systems analysis. It is important to analyze the energy modeling and management concept before its real implementation. However, the plethora of simulation software in the past decade has made it difficult for researchers to choose a particular tool appropriate to their research objective. Many researchers have reviewed the use of computational tools for various applications. These broadly cover the following: integration of renewable energy into various energy systems [1], integration of EV to grid [2], [3], design and analysis of power systems [4], and hybrid renewable-energy systems [5]. However, none of the research focused on the tools related to residential energy systems. Residential energy management plays a pivotal role in power quality management, power regulation, load management, and grid efficiency enhancement, in power systems.
Therefore, this paper provides an overview of the computational tools for the design, analysis, and management of residential energy systems. All the tools are systemically categorized based on their applications, functional capability, strengths, and limitations. A case study covering the overall areas of residential energy management has been carried out to show the strengths and limitations of a certain simulation tool. In this case study, the residential load is managed using battery-energy-storage systems and electric vehicles (EVs). The charging-discharging of the battery and EVs is controlled based on the load and the photovoltaic (PV) power generation to reduce the grid power demand. The pre-heating and pre-cooling demand is managed using the PV power, and the thermal-comfort satisfaction and dis-satisfaction index is analyzed based on that energy management. Additionally, the overall building design is optimized to enhance the energy efficiency. In this case study, it is observed that residential energy management is a wide area covering electrical loads, energy sources, renewable integration, HVAC, and the architectural design, and all these factors’ effects should be considered for efficient energy management. However, none of the tools covers all these areas, as each tool has its own strengths and limitations. Therefore, in this paper, all the tools are categorized and analyzed based on their availability, applications, strengths, and limitations on the basis of both traditional and future smart-grid architecture. The goal of the paper is to help researchers to an easy selection of a specific tool appropriate to their research objective in the residential energy management domain.
Section snippets
List of residential energy systems tools
The simulation tools that are related to residential energy systems for modeling and analysis, optimization, management, economic analysis, and renewable energy integration are listed in Table 1, Table 2, Table 3, Table 4, Table 5. Although the tools cover a wide range of applications, they are listed in separate tables because of their strength in a certain area. Each table is further segmented into tools’ names, sources, availability, and common applications. Typical applications include load
Distributed energy resources integration to home
It is expected that the future smart grid, or internet of energy (IoE) [166], will be more automated and disaggregated by including small-scale energy devices. Users will be known as prosumers where they will connect energy devices through a plug-and-play facility, and transfer energy in a bidirectional way. Customers will use various energy storages and renewable sources to reduce their dependency on the grid. In this section various renewable-energy integration to the grid are discussed.
Description of simulation tools
Some selected simulation tools from Table 1, Table 2, Table 3, Table 4, Table 5, based on their wide range of applications in the residential energy systems are described in this section. Each description contains tool’s features, applications, and internal functionalities.
Case studies
In this section, a case study has been carried out to manage residential energy systems. From the tools listed in Table 1, Table 2, Table 3, Table 4, Table 5, GridLAB-D is selected for the energy-management simulation, as it is open-source software and has a wider range of applications in residential energy systems.
Conclusion
This paper provides an insight on the available software tools for conducting studies on residential energy-management systems. The existing software tools are divided into several groups based on their suitability for different types of applications. The aim is to assist users to easily select the right software tool for a specific application. The strengths and limitations of each tool are discussed in detail so that users are aware of the types of analyses that can be performed. A case study
Acknowledgement
Authors are thankful to Dr. Keith Imrie for the proofreading.
References (184)
- et al.
A review of computer tools for analysing the integration of renewable energy into various energy systems
Appl Energy
(2010) - et al.
A review of computer tools for modeling electric vehicle energy requirements and their impact on power distribution networks
Appl Energy
(2016) - et al.
Review of software tools for hybrid renewable energy systems
Renew Sustain Energy Rev
(2014) - et al.
Energy and economic evaluation of cooling, heating, and power systems based on primary energy
Appl Therm Eng
(2009) - et al.
Analysis of building energy consumption parameters and energy savings measurement and verification by applying eQUEST software
Energy Build
(2013) - et al.
Analysis of energy efficiency retrofit scheme for hotel buildings using eQuest software: a case study from Tianjin, China
Energy Build
(2015) WINSHADE: a computer design tool for solar control
Build Environ
(1998)- et al.
Simulation of a VAV air conditioning system in an existing building for the cooling mode
Energy Build
(2009) - et al.
Simulation and experimental validation of the variable-refrigerant-volume (VRV) air-conditioning system in EnergyPlus
Energy Build
(2008) - et al.
The use of performance-based simulation tools for building design and evaluation—a Singapore perspective
Build Environ
(2000)
Inter-comparison of North American residential energy analysis tools
Energy Build
A test plan for an on-line whole building energy calculator
Build Environ
Contrasting the capabilities of building energy performance simulation programs
Build Environ
Barriers and opportunities for labels for highly energy-efficient houses
Energy Policy
Photovoltaics in buildings: a case study for rural England and Malaysia
Renew Energy
Evaluation of the impact of the surrounding urban morphology on building energy consumption
Sol Energy
Perspectives of double skin façade systems in buildings and energy saving
Renew Sustain Energy Rev
Energy retrofit analysis toolkits for commercial buildings: a review
Energy
Large variations in specific final energy use in Swedish apartment buildings: causes and solutions
Energy Build
Predicting thermal performance in occupied dwellings
Energy Build
Description of ParaSol v3. 0 and comparison with measurements
Energy Build
Overview of HVAC system simulation
Autom Constr
Managing energy smart homes according to energy prices: analysis of a building energy management system
Energy Build
Optimum, technical and energy efficiency design of residential building in Mediterranean region
Energy Build
A comprehensive study of the impact of green roofs on building energy performance
Renew Energy
Modeling seasonal solar thermal energy storage in a large urban residential building using TRNSYS 16
Energy Build
Hospital CHCP system optimization assisted by TRNSYS building energy simulation tool
Appl Therm Eng
5.6 Energy management softwares and tools
Software tools overview: process integration, modelling and optimisation for energy saving and pollution reduction
Asia-Pac J Chem Eng
Comparision and analysis of lighting calculation software Dialux & Agi32
China Illuminating Eng J
A comparison of EnergyPlus and eQUEST whole building energy simulation results for a medium sized office building
Study on the analysis method of energy consumption of building with eQUEST software
J Zhejiang Univ Technol
Agent-based modeling of occupants and their impact on energy use in commercial buildings
J Comput Civil Eng
Review of building energy simulation tools that include moisture storage in building materials and HVAC systems
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