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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]

• A retrofit selection strategy employing economic and environmental decision criteria was proposed. • Building energy retrofits were evaluated through a life cycle thinking approach. • Retrofits with operational emissions savings may not be beneficial when considering life cycle impacts. • Energy mix and the heating system of the house greatly impact the effectiveness. • Retrofit selection changes with stakeholder priorities on environment and economics. Improving the energy performance of buildings has been a much-discussed topic over the past few decades. With the current focus on climate change mitigation, emissions reduction has also come to the forefront of this discussion. Retrofitting is an option to improve the energy and emissions performance of buildings. However, in the residential building stock, retrofit planning for existing buildings faces many complexities due to variations in climatic conditions and macro-environment as well as the presence of multiple stakeholder groups. Thus, in identifying solutions, it is necessary to take a holistic perspective that covers these different dimensions. In this paper, commonly used building energy retrofits were evaluated through a life cycle thinking approach. The performance of various retrofit options applicable for single family detached housing were evaluated using the HOT2000 energy simulation software package under the varying climatic conditions and energy supply scenarios across Canada. The retrofits were evaluated in terms of the additional investment, energy use and cost reduction achieved over the life cycle, and life cycle emissions reduction. The findings indicate that the provincial energy mix and the heating system of the house (i.e. electric or natural gas) play a major role in determining the effectiveness of a retrofit, and this "effectiveness" changes at different stakeholder levels. However, not all retrofits that reduce emissions make economic sense and vice versa when life cycle thinking comes into play. The findings will be useful for building owners and occupants as well as for policy developers and other decision makers interested in demand side management. [ABSTRACT FROM AUTHOR]

Planning decentralised community-level hybrid energy systems has emerged as a solution to the various environmental and economic issues associated with conventional centralised energy supply systems. However, the optimal planning of community energy systems is a challenging issue due to the complexities, uncertainties, conflicting objectives, and high computational times in analysis. This study introduces a new multi-objective model based on weighted goal programming and grey pairwise comparison to assess renewable energy-based strategies in the case of net-zero energy communities. The problem was formulated to determine the optimal energy mix based on minimization of life cycle impacts and costs and maximization of renewable contributions and operational energy savings. To this end, binary integer and continues variables were applied on the code developed in a CPLEX environment. A pairwise comparison based on grey numbers was used to find the impacts of the goals in the objective function of the model under uncertainty. In addition to the grey-based weighting scenario, different weighting scenarios were employed to consider the importance of all goals on the system. These weighting scenarios were used to investigate the effects of changing decision priorities on the outcomes and on stakeholder interests at different levels. The developed goal-programming model was applied to the data of a case example and solved based on the weighting scenarios. Results indicated that the model is capable of finding the best possible strategies with the lowest total undesirable deviations from the desired levels of the goals compared to the literature of the decision-making techniques. The integration of maximum renewable energy (RE) supply in the energy mix with the locally available energy resources can deliver considerable benefits in terms of energy supply cost reduction as well as in mitigating life cycle environmental impacts. When environmental goals are prioritized, integrating low emissions RE as much as possible and excluding waste-to-energy technologies makes best sense, while under a pro-economic perspective, solar integration is comparatively discouraged. The findings of the study are expected to assist community developers and other decision makers involved in regional energy planning. The developed method will also be of use for those who are interested in the use of goal programming to solve complex planning issues involving numerous uncertain parameters. • Energy planning involves multiple decision dimensions and requires multi-objective optimization. • Goal programming can be used to reduce computational time in complex optimization problems. • Optimal energy mix in community energy systems change based on decision priorities. • RE integration can deliver life cycle economic and environmental benefits for communities. [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]

Supplying the energy needs of a community through renewable energy sources is a vital aspect in developing sustainable communities. Many variations and uncertainties affect the development of a renewable-powered net-zero energy system. Community developers face challenges in making the investment decisions when planning community-level renewable energy (RE) projects. This study aims to address the need for reliable methods to assess RE project deployment strategies. To achieve this, the key decision variables were identified and dynamic project performance was assessed for a Canadian RE case study. A framework was developed using system dynamics for rating renewable energy project deployment scenarios. A fuzzy logic-based optimization process was used to identify the optimal system capacities and energy mix. The optimal energy supply mix was identified as follows for the case study: grid electricity- 56%, solar PV – 28%, biomass – 11%, and waste-to-energy– 5%. The results of the system dynamics based rating indicated that stage-by-stage construction that also accounts for community growth in facility capacity sizing provides the best outcomes for the community, with 42.8% of the community's energy demand supplied with renewables. The developed model can help community developers to identify the best energy choices and investment strategies when planning community energy systems. • Energy planning involved technical, economic, and environmental dimensions. • Planning hybrid RE systems at community level supports net-zero development. • Multi-objective optimization is used to identify the optimal energy supply mix. • System dynamics modelling is used to evaluate long-term RE project performance. • Phased development with capacity growth is a better choice for community RE. [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]