scholarly journals Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6223
Author(s):  
Bin Ye ◽  
Minhua Zhou ◽  
Dan Yan ◽  
Yin Li
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Energy Systems ◽  
Energy System ◽  
Energy Utilization ◽  
Target Area ◽  
Renewable Energy Systems ◽  
Multi Objective ◽  
Hybrid Renewable Energy Systems ◽  
Hybrid Renewable Energy

The application of renewable energy has become increasingly widespread worldwide because of its advantages of resource abundance and environmental friendliness. However, the deployment of hybrid renewable energy systems (HRESs) varies greatly from city to city due to large differences in economic endurance, social acceptance and renewable energy endowment. Urban policymakers thus face great challenges in promoting local clean renewable energy utilization. To address these issues, this paper proposes a combined multi-objective optimization method, and the specific process of this method is described as follows. The Hybrid Optimization Model for electric energy was first used to examine five different scenarios of renewable energy systems. Then, the Technique for Order Preference by Similarity to an Ideal Solution was applied using eleven comprehensive indicators to determine the best option for the target area using three different weights. To verify the feasibility of this method, Xiongan New District (XND) was selected as an example to illustrate the process of selecting the optimal HRES. The empirical results of simulation tools and multi-objective decision-making show that the Photovoltaic-Diesel-Battery off-grid energy system (option III) and PV-Diesel-Hydrogen-Battery off-grid energy system (option V) are two highly feasible schemes for an HRES in XND. The cost of energy for these two options is 0.203 and 0.209 $/kWh, respectively, and the carbon dioxide emissions are 14,473 t/yr and 345 t/yr, respectively. Our results provide a reference for policymakers in deploying an HRES in the XND area.

scholarly journals Optimisation of hybrid renewable energy systems on islands: A review

2021 ◽  
Author(s):  
James Morales Lassalle ◽  
Dante Figueroa Martínez ◽  
Luis Vergara Fernández
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Meteorological Data ◽  
Energy Systems ◽  
Energy System ◽  
Fundamental Aspect ◽  
Power Relationship ◽  
Renewable Energy Systems ◽  
Hybrid Renewable Energy Systems ◽  
Hybrid Renewable Energy

Access to energy services is recognised as a fundamental aspect of economic and social development. This is particularly important for isolated areas, where electrical supply is not guaranteed. Because of their inherent geographic characteristics, islands are prominent cases of isolated areas that must import and burn fossil fuels, with environmental and economic consequences. In this context, Hybrid Renewable Energy Systems (HRES) emerge as an alternative to traditional generation to reduce energy costs and environmental issues. This study aims to demonstrate the feasibility of implementing HRES on islands, based on energy optimisation. We present an extensive review of HRES optimisations across 73 island cases, collecting information about energy demand, energy system sizes, and optimisation methodologies. The most commonly proposed HRES components are identified, and a significant power relationship is found between population and annual energy demand on islands. Further, we identify islands with higher-than-expected and lower-than-expected consumption and the underlying causes. The main limitations of the reviewed studies are discussed, particularly with regards to availability and quality of hourly demand data and/or meteorological data required for renewable energy assessments. Several approaches to fill these gaps in information are reviewed here, concluding with a discussion of emergent methods and technologies.

Stochastic Optimization of Hybrid Renewable Energy Systems

2015 ◽  
Author(s):  
Masoud Sharafi ◽  
Tarek Y. ElMekkawy
Keyword(s):  
Renewable Energy ◽  
Stochastic Optimization ◽  
Performance Metrics ◽  
Energy Systems ◽  
Solar Irradiation ◽  
Optimization Approach ◽  
Renewable Energy Systems ◽  
Multi Objective ◽  
Hybrid Renewable Energy Systems ◽  
Hybrid Renewable Energy

The stochastic nature of energy demand and renewable energy (RE) resources make the design of hybrid renewable energy systems as a complex problem. In this paper, an innovative stochastic optimization approach is proposed for optimal sizing of hybrid renewable energy systems (HRES) incorporating existing uncertainties in RE resources and energy load. The design problem is formulated based on multiobjective optimization framework with three objective functions including minimize total net present cost (NPC), maximize renewable energy ratio (RER), and minimize fuel emission. The reliability index named loss of load probability (LLP) is considered as a constraint with a desirable level. The Pareto front (PF) of developed multi-objective optimization problem is approximated with the help of the integration of dynamic multi-objective particle swarm optimization (DMOPSO) algorithm, simulation module, and sampling average method. Synthetic data generation approaches are applied to tackle the randomness in wind speed, solar irradiation, ambient temperature, and energy load. A building located in Canada is used as the case study to assess the performance of the developed model. Finally, the obtained PF by the stochastic optimization approach is examined against the deterministic PF using the most famous performance metrics.

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