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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]