Microgrid Economic Viability Assessment Using Stochastic Cost Modeling
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Solution Overview
Problem
The high investment costs and uncertainty in assessing economic benefits hinder the widespread deployment of microgrids, as existing methods struggle to accurately evaluate the viability of microgrid deployments due to complex and uncertain data related to reliability improvements and energy costs.
Innovation Solution
A method and system for evaluating the economic viability of microgrids by selecting candidate distributed energy resources, determining their investment and operation costs, and comparing these costs to the cost of drawing power from the main grid, while accounting for uncertainty factors, to identify when microgrid deployment is economically viable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If microgrid deployment is pursued to improve reliability and resilience, then grid resilience and reliability are improved, but investment costs increase
Solution Approach 1:
The patent changes the parameter of economic assessment from traditional deterministic methods to stochastic programming that incorporates uncertainty parameters. This allows for more accurate calculation of net present value and equivalent annual cost by considering probabilistic scenarios of energy prices, load demands, and renewable generation, thereby providing a more reliable basis for investment decision-making in microgrid deployments
Solution Approach 2:
The patent introduces an intermediary economic assessment model that acts as a mediator between the technical microgrid configuration and the investment decision. This model uses stochastic programming to translate uncertain operational parameters into economically meaningful metrics (NPV, EAC), enabling stakeholders to evaluate reliability improvements against investment costs in a standardized manner
2Ease of manufacture
If traditional economic assessment methods are used, then assessment process is simple, but accuracy of economic benefit evaluation deteriorates due to uncertain data
Solution Approach 1:
The patent transforms the static economic assessment into a dynamic stochastic model that adapts to uncertain parameters. The assessment dynamically adjusts calculations based on probabilistic scenarios of energy prices, load demands, and renewable generation, maintaining measurement precision while managing complexity through structured uncertainty representation
Solution Approach 2:
The patent replaces traditional deterministic mechanical calculation methods with stochastic programming approaches. This substitution introduces probability distributions and optimization algorithms that better capture the inherent uncertainty in microgrid economic benefits, significantly improving evaluation accuracy despite increased computational complexity
3Reliability
If reliability improvements are represented in supply availability terms, then reliability metric is clear, but customer comprehension deteriorates
Solution Approach 1:
The patent introduces economic metrics (NPV, EAC) as intermediary representations that bridge the gap between technical reliability measures and customer understanding. These economic indicators serve as translators that convert abstract supply availability statistics into financially meaningful terms that customers can directly comprehend and use for decision-making
Data Source
AI summary
Methods and systems for evaluating economic viability of a proposed microgrid, including uncertain variables are disclosed. One or more candidate distributed energy resources can be selected for use within a proposed microgrid. An investment cost and an operation cost of the one or more candidate distributed energy resources can be determined. A cost of drawing power from a main power grid can be compared to a sum of the investment cost and the operation cost of the one or more candidate distributed energy resources. The proposed microgrid can be identified for installation when the sum of the investment cost and the operation cost is less than the cost of drawing power from the main power grid.


