Assessment of tools for urban energy planning

Ferrari, Simone; Zagarella, Federica; Caputo, Paola; Bonomolo, Marina

doi:10.1016/j.energy.2019.04.054

Cited by 89 publications

(33 citation statements)

References 30 publications

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“…Out of 41 software tools mentioned in [74] viz. HYBRID 2 [75], RETScreen [76], iHOGA [77], TRNSYS [78], and IPSYS; and 6 user-friendly tools [79]; HOMER (Hybrid Optimization of Multiple Electric Renewables) software is the most frequently used and highly recommended in various research studies. HOMER is a robust techno-economic optimization tool [45] which allows adaptability to analyze and simulate techno-economic models and design optimization of HRES units [45].…”

Section: Optimal Sizing and Economic Analysis Using Homer Promentioning

confidence: 99%

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

et al. 2020

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Microgrids being an important entity in the distribution system, and to get their full advantages by incorporating maximum distributed generation, standalone hybrid renewable energy systems (HRESs), being environmentally-safe and economically-efficient, are considered as the promising solution to electrify remote areas where the grid power is not available. In this work, a techno-economic investigation with an optimal design of HRES is presented to fulfill the domestic electricity need for a residential area of the Sherani district in the Province of Baluchistan, Pakistan. Nine case studies based on PV/wind/diesel/battery are analyzed based on net present cost (NPC), cost of energy (COE), and emission to decide the feasible solution. HOMER tool is utilized to accomplish modeling and simulation for economic analysis and optimal sizing. Simulation results demonstrated that HRES with PV-wind-battery is the most viable option for the specified area, and the optimal sizing of components are also obtained with $ 28,620 NPC and $ 0.311/kWh COE which shows 81.65 % reduction in cost and 100 % preserving in toxic emission while fulfilling 100 % energy demand with 67.3 % of excess energy. Furthermore, MATLAB/Simulink modeling for the optimally designed system is built for technical analysis while its effectiveness is proved by keeping dc and ac buses voltage constant, safe operating range of battery state of charge (SOC) with active power balance between HRES components, as well as efficient ac voltage quality, regardless of generation disturbances and load fluctuations. The output signal has total harmonic distortion (THD) of 0.30 % as compared to 5.44 % with the conventional control scheme. The novelty lies in the sequential application of both HOMER and MATLAB simulations of the proposed HRES model and validation of the proposition for the studied area; by using and implementing model predictive control (MPC) of a reconfigurable inverter. WT

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Section: Optimal Sizing and Economic Analysis Using Homer Promentioning

confidence: 99%

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

et al. 2020

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“…The comparison of different optimal sizing tools is described in [67], while these tools are used in the research studies for the sizing of HRES models. Out multiple available tools [68], [69]- [73], HOMER (Hybrid Optimization of Multiple Electric Renewables) tools are the best often applied and extremely commended in different literature works.…”

Section: Techno-economic Investigation Using Homermentioning

confidence: 99%

Optimal Design and Model Predictive Control of Standalone HRES: A Real Case Study for Residential Demand Side Management

et al. 2020

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Conventional electricity generation is one of the greatest sources of CO 2 emissions. For a successful transformation of conventional energy systems into non-polluting and renewable energy systems, technology-focused traditional systems and economics must be combined for a more accurate holistic viewpoint with consideration of socio-political, technical, economic and environmental factors. Hybrid energy systems are considered the most feasible solution to the stochastic nature of renewable energy resources (RERs). Different renewable sources such as wind, solar, and hydrogen fuel cells can be integrated to form hybrid systems. An energy management strategy (EMS) is a strategy for power flow coordination among different components, by considering power demand and other constraints. The choice for an accurate EMS is the key element of a hybrid system as it is instrumental in providing an optimum solution of the hybrid system design and operation management. The objective of the optimization is to find suitable configurations for cost-effective solutions. Optimization and EMS must be treated as one entity to completely understand the system design. This study focuses on a techno-economic analysis with an optimized sizing of a hybrid renewable energy system (HRES) components to meet the residential load demand of a specific area in Pakistan. Nine different scenarios based on the PV-wind-diesel-BSS-converter system are investigated in terms of total net present cost (TNPC), Levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions to find the optimal system design. HOMER Pro software is used to develop the HRES model and for simulation analysis, with optimal sizing of each component for an economical solution. Simulation studies established that PV-wind-BSS-converter is the best suitable choice for the given location, and the optimal component sizes were determined. The TNPC of this system is $ 47,398 and the LCOE is $ 0.309/kWh. This represents an 81.7 % decrease in overall cost, compared to the base case (diesel only) and a 100% reduction in harmful gases while satisfying 100 % of the energy requirement with a 63.9 % of the surplus. MATLAB/Simulink model is developed for the optimum HRES system design. Its validity is tested by maintaining bus voltages (dc and ac), the secure operation range of storage SOC and real power balance among different components of the hybrid renewable energy system (HRES), and an effective ac voltage, irrespective of external perturbations. Model predictive control (MPC) is regarded as a high-performing algorithm. Since power converters are largely applied in microgrids (MGs), the problem formulation with MPC for a reconfigurable bidirectional voltage source converter (VSC) is applied in this work for hybrid MG. The inevitable fluctuations due to the linear and non-linear loads and the nature of renewable sources are addressed. The regulation of ac voltage is implemented through a finite control set model predictive control (FCS-MPC) based active front end (AFE) rectifier, while...

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“…Among them, six user-friendly tools were identified (energyPRO, HOMER, iHOGA, EnergyPLAN, SIREN, and WebOpt) that can provide hourly energy calculations and can be considered viable for widespread use. Ferrari, Zagarella, Caputo, and Bonomolo (2019) reviewed methods and tools for estimating hourly energy demand profiles at the district level. Frayssinet et al (2018) conducted an overview of city energy simulation models capturing short (hourly or sub-hourly) energy dynamics and reviewed the related modeling techniques using detailed approaches.…”

Section: Introductionmentioning

confidence: 99%

Ten questions on urban building energy modeling

Hong

Chen

Luo

et al. 2020

Building and Environment

294

121

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Buildings in cities consume up to 70% of all primary energy. To achieve cities' energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings. Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers. This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.

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Assessment of tools for urban energy planning

Cited by 89 publications

References 30 publications

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

Optimal Design and Model Predictive Control of Standalone HRES: A Real Case Study for Residential Demand Side Management

Ten questions on urban building energy modeling

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