Abstract
•Energy and cost oriented methodology is developed.•A representative benchmark including 96 all-electric houses in Norway is created.•Three grid rent business models are investigated and expected energy-cost saving is calculated.•Required space-heating load shift is determined.•The effectiveness of the three dynamic pricing tariffs are compared.
There is a need for methodologies that integrate energy simulation and cost calculation to assess grid rent business models as incentive for demand-side management (DSM) in buildings. Despite the proliferation of energy simulation and cost calculation tools, there are no tool (e.g., software program) with appropriate methodology that caters specifically for the assessment of business models based on aggregation of dynamic pricing tariffs. Furthermore, the majority of existing methodologies focus on evaluating the supply-side management (SSM) of energy grids, and largely overlook the issue of influencing the customer to make good choices when it comes to DSM and/or design/renovation actions. This paper introduces energy and cost oriented methodology that provides informative support for utility companies and electric-grid customers including households’ occupants to assess the economic incentives of different energy and power dynamic pricing tariffs. A physical model-based building simulation tool (IDA-ICE) is used to assess the energy performance of a representative residential benchmark including 96 all-electric houses in Norway with and without renewable energy technology. A business model-based cost calculator is developed and linked with the energy simulation's outputs to assess the effectiveness of three dynamic pricing tariffs, suggested recently by the Norwegian Water Resources and Energy Directorate (NVE). The effectiveness of the three pricing tariffs is compared (improving building's energy efficiency vs enhancing grid's demand side load shifting). Overall, results indicate that the Tiered Rate tariff is the most effective business strategy for customers to reduce the electric-based heating load during high demand periods. However, the methodology generated a comprehensive suite of scenarios analysis that allow customers, utility companies and policy makers to accurately address several building renovation variations and demand side management strategies to make the right decision upfront.