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• Energy planning needs multi-objective decision making and uncertainty integration. • The most suitable planning methods needs to be identified for optimal outcomes. • The optimization models lead to similar results but different computational times. • When cost and impact uncertainty increases, suitability of renewables decreases. • Robust optimization technique has high potential when planning under uncertainty. Distributed energy systems renewable energy are one solution to the environmental and economic concerns of energy use. While energy planning and optimization have been conducted mainly as a mathematical exercise, practical approaches that incorporate the engineering realities and uncertainties are limited. Decision makers find challenges in community energy planning due to the lack of expertise, planning tools, and information. While a multitude of models and tools are currently available, there are no means of identifying the most appropriate or accurate methods, especially considering uncertainty. The main objective of this study is to compare and identify the strengths and limitations of various mathematical modelling techniques used in energy planning for grid connected renewable energy systems. As a case study demonstration, different multi-objective optimization techniques with and without uncertainty consideration (i.e. robust optimization, linear optimization, Taguchi Orthogonal Array method, and Monte Carlo simulation) were applied on a selected neighborhood in British Columbia. The optimization outcomes and the time and effort for evaluation were compared for the different methods. The findings indicate that robust optimization can be used to develop an uncertainty-based decision model. It significantly reduces evaluation time compared to the other methods. Although the presence of uncertainties can change the optimal configuration of a planned energy system, the assessment method itself does not significantly impact the outcomes. The findings of this study will enable the energy planners and researchers to compare different multi-objective optimization techniques, and to select the best for planning renewable energy projects, especially during the pre-project planning stage. [ABSTRACT FROM AUTHOR]

Recent studies have shown that Canada will not achieve its 2030 emission reduction targets outlined in the Paris Agreement. Canadian energy decision makers are now at a crossroad between making sound fiscal decisions and ramping up efforts to meet emission reduction commitments. Approximately 195,000 people are living in off-grid Canadian communities, with most of these communities relying on fossil-fuel based energy generation. Hybrid renewable energy systems provide a novel solution to address the high costs of off-grid energy and Canada's emission reduction targets. To address the competing stakeholder priorities in off-grid energy planning (e.g., economic, environmental, and system performance), the authors of this paper employed a generalizable combinatorial-based alternative ranking method. Alternative energy technology combinations were simulated to calculate key performance indicator values. The framework allows decision makers to identify the most feasible energy system based on their priorities. A case study was performed with the developed framework for a small off-grid community in British Columbia, Canada. The results show that feasibility of energy system configurations vary greatly based on differing decision-making priorities. The case study also confirmed that hybrid renewable energy systems have better environmental performance compared to their fossil fuel counter parts, but at a significantly higher cost. The study further confirms that the balance between environmental and economic performance of off-grid energy systems can be improved through proper component sizing, management practices, and the integration of energy storage. • Life cycle impacts need to be considered in off-grid hybrid renewable energy systems planning. • Hybrid renewable energy systems incur lower environmental impacts at higher costs. • Combining fossil fuel generators and battery banks reduces emissions at a lower cost. • Decision makers' priorities has a high impact in the ranking of energy system configurations. • The developed method accounts for different priorities in energy system feasibility assessment. [ABSTRACT FROM AUTHOR]

The ever-increasing anthropogenic greenhouse gas (GHG) emissions worldwide make it quite challenging to meet country-specific Nationally Determined Contributions (NDC) targets. Therefore, it is evident that the existing emissions abatement measures need to be taken a step further. Internationally Transferred Mitigation Outcomes (ITMOs) are allowed in Article 6.2 of the Paris Agreement as a cooperative approach to achieving NDC goals. There is a potential to create ITMOs between Canada and China by replacing coal use in China with British Columbia (BC)'s liquefied natural gas (LNG) supply. Replacing coal with LNG in energy generation applications is a promising approach to mitigate emissions. With global and national pressures to reduce emissions, China has created a market for LNG imports to cater to its rising natural gas (NG) consumption due to the coal-to-gas source switching strategy. However, the terms under Article 6.2 requires generated ITMOs to ensure environmental integrity, support sustainable development goals, and have a robust accounting system. Therefore, the current study aims to quantify the life cycle environmental outcomes of generating ITMOs by exporting LNG from BC to Chinese end-users while integrating uncertainties and to provide policy recommendations in adherence with the requirements of Article 6.2. Different LNG export scenarios were generated in the study and environmental impacts of each scenario were assessed and compared using a life cycle assessment (LCA) framework developed by the authors. Sensitivity and uncertainty analyses were conducted to understand the impacts created by the data uncertainties in the final result. By replacing conventional coal with NG, approximately 40–45% and 26%–32% emissions reductions can be obtainable for Chinese textile and chemical industries, respectively. The highest emissions reduction of approximately 60% was observed when coal is replaced with NG for district heating. The life cycle emissions (LCE) quantification framework provided in the study provides stakeholders with a systematic approach to determine the total GHG emissions and emissions reduction potential of different LNG export scenarios. [ABSTRACT FROM AUTHOR]