Introduction: Energy Systems Modelling for Decision-Making

Sustainability of energy systems is a common priority that involves key issues such as security of energy supply, mitigation of environmental impacts - the energy sector is currently responsible for 80% of all EU greenhouse gas emissions (European Environment Agency, 2007), contributing heavily to the overall emissions of local air pollutants - and energy affordability. In this framework, energy planning and decision making processes can be supported at different stages and spatial scales (regional, national, pan-European, etc.) by the use of comprehensive models in order to manage the large complexity of energy systems and to define multi-objective strategies on the medium-long term. This Chapter is aimed to outline the value of model-based decision support systems in addressing current challenges aimed to carry out sustainable energy systems and to diffuse the use of strategic energy-environmental planning methods based on the use of partial equilibrium models. The proposed methodology, aimed to derive cost-effective strategies for a sustainable resource management, is based on the experiences gathered in the framework of the IEA-ETSAP program and under several national and international projects.

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

Energies ◽

10.3390/en13236223 ◽

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.

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A new hybrid multi-criteria decision-making approach for developing integrated energy systems in industrial parks

Journal of Cleaner Production ◽

10.1016/j.jclepro.2020.122119 ◽

2020 ◽

Vol 270 ◽

pp. 122119 ◽

Cited By ~ 1

Author(s):

Jiahang Yuan ◽

Yun Li ◽

Xinggang Luo ◽

Zhongliang Zhang ◽

Yuanpeng Ruan ◽

...

Keyword(s):

Decision Making ◽

Energy Systems ◽

Multi Criteria Decision Making ◽

Integrated Energy Systems ◽

Industrial Parks

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Backbone—An Adaptable Energy Systems Modelling Framework

Energies ◽

10.3390/en12173388 ◽

2019 ◽

Vol 12 (17) ◽

pp. 3388 ◽

Cited By ~ 5

Author(s):

Niina Helistö ◽

Juha Kiviluoma ◽

Jussi Ikäheimo ◽

Topi Rasku ◽

Erkka Rinne ◽

...

Keyword(s):

Power Plants ◽

Large Scale ◽

Unit Commitment ◽

Energy Systems ◽

Mixed Integer ◽

Investment Planning ◽

Planning And Scheduling ◽

Modelling Framework ◽

Wide Range ◽

Systems Modelling

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

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