Matching indices taking the dynamic hybrid electrical and thermal grids information into account for the decision-making of nZEB on-site renewable energy systems

2015 ◽  
Vol 101 ◽  
pp. 423-441 ◽  
Author(s):  
Sunliang Cao ◽  
Kai Sirén
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Energy Systems ◽  
Renewable Energy Systems ◽  
Dynamic Hybrid

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 MULTI-CRITERIA DECISION-MAKING FOR SELECTION OF RENEWABLE ENERGY SYSTEMS

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Milica Stojanovic
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Analytical Hierarchy Process ◽  
Energy Systems ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Suitable Alternative ◽  
Renewable Energy Systems ◽  
Multi Criteria Analysis ◽  
Hierarchy Process

Multi-criteria analysis involves defining each criterion using attributes, based on a suitable alternative for achieving objectives. The method used in multi-criteria analysis is Analytical Hierarchy Process. Analytical hierarchical process (AHP) is a tool in the analysis of decision making, created in order to assist decision-makers in solving complex decision problems involving large number of decision makers, large number of criteria and in multiple time periods. AHP method is used for selecting the best renewable energy systems. The aim is to, by using the method of AHP, demonstrate which of the analyzed renewable sources of energy is the most convenient to be used in a sustainable system. Key words:energy, multi-criteria decision making, analytical hierarchy process

scholarly journals Multi-Objective Particle Swarm Optimization-Based Decision Support Model for Integrating Renewable Energy Systems in a Korean Campus Building

2021 ◽  
Vol 13 (15) ◽  
pp. 8660
Author(s):  
Minjeong Sim ◽  
Dongjun Suh ◽  
Marc-Oliver Otto
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Renewable Energy ◽  
Energy Savings ◽  
Energy Systems ◽  
Energy Policies ◽  
Swarm Optimization ◽  
Renewable Energy Systems ◽  
Multi Objective ◽  
Proposed Model

Renewable energy systems are an alternative to existing systems to achieve energy savings and carbon dioxide emission reduction. Subsequently, preventing the reckless installation of renewable energy systems and formulating appropriate energy policies, including sales strategies, is critical. Thus, this study aimed to achieve energy reduction through optimal selection of the capacity and lifetime of solar thermal (ST) and ground source heat pump (GSHP) systems that can reduce the thermal energy of buildings including the most widely used photovoltaic (PV) systems. Additionally, this study explored decision-making for optimal PV, ST, and GSHP installation considering economic and environmental factors such as energy sales strategy and electricity price according to energy policies. Therefore, an optimization model based on multi-objective particle swarm optimization was proposed to maximize lifecycle cost and energy savings based on the target energy savings according to PV capacity. Furthermore, the proposed model was verified through a case study on campus buildings in Korea: PV 60 kW and ST 32 m2 GSHP10 kW with a lifetime of 50 years were found to be the optimal combination and capacity. The proposed model guarantees economic optimization, is scalable, and can be used as a decision-making model to install renewable energy systems in buildings worldwide.

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