Optimizing Power for Remote Grids with Diesel, Wind, Solar, and Batteries
This patent describes a computer-based method for designing and operating independent power systems, called micro-grids, to balance cost, reliability, and environmental impact using a mix of diesel generators, wind turbines, solar panels, and energy storage batteries.
Original patent title: “Optimization method for independent micro-grid system”
This patent describes a computer-based method for designing and operating independent power systems, called micro-grids, to balance cost, reliability, and environmental impact using a mix of diesel generators, wind turbines, solar panels, and energy storage batteries. Granted to Electric Power Research Institute of State Grid Zhejiang Electric Power Co in 2018 with 8 claims, and it is expected to expire in 2033.
Coverage
What does this patent actually cover?
The patent outlines a method for optimizing an independent micro-grid system, which includes diesel generators, wind generators, a photovoltaic array, and an energy storage battery. It works by first gathering device parameters for all these components. Then, a computer system uses a multi-objective genetic algorithm to find the best setup. This algorithm considers three main goals: minimizing total cost over the system's lifetime, reducing the chance of power outages (loss of load capacity), and lowering pollution levels. The method also uses a 'quasi-steady state simulation strategy' with two modes: a 'hard charging strategy' where diesel generators can charge the battery, and a 'power smooth strategy' where the battery only helps when diesel alone isn't enough. For example, it calculates how many diesel generators are needed at any moment, considering the current power demand, available renewable energy, and the battery's charge/discharge limits (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1).
The gap
What does this patent NOT cover?
- Does not cover optimization methods that use algorithms other than a multi-objective genetic algorithm, specifically one based on NSGA-II.
- Does not cover micro-grid systems that rely on different primary energy sources, such as hydropower or geothermal, instead of the specified diesel, wind, and photovoltaic combination.
- Does not cover control strategies for energy storage batteries that do not include both a 'hard charging strategy' and a 'power smooth strategy' as defined.
- Does not cover systems that fail to account for a 'preset spare capacity' to ensure the micro-grid's stability.
- Does not cover optimization models that do not simultaneously consider the three specific objectives: total cost, loss of load capacity, and pollution level.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is the integrated multi-objective optimization using a genetic algorithm. It simultaneously balances conflicting goals—like saving money, keeping the lights on, and protecting the environment—while also factoring in complex operational details like diesel generator start-up modes and battery charging strategies, along with system stability requirements.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Remote village power systems in developing countries
Island communities relying on local generation
Military bases in isolated locations
Off-grid industrial facilities
Emergency backup power for critical infrastructure
Why it matters
The bigger picture
Independent micro-grids are crucial for providing reliable power to remote areas, islands, or military bases where connecting to a large central grid is impractical or too expensive. This patent offers a systematic way to design these systems, ensuring they are not only cost-effective but also reliable and less polluting. By optimizing the mix of renewable sources and traditional generators, it helps make off-grid power solutions more sustainable and widely deployable, especially in regions with limited infrastructure.
Filed
October 14, 2013
Granted
May 29, 2018
Market context
Who's building on this
Companies in this space
The assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, Electric Power Research Institute of State Grid Zhejiang Electric Power Co Ltd, is a research arm of a major Chinese state-owned utility. They, along with other national grid operators and energy research institutions globally, continue to develop and implement advanced optimization techniques for distributed energy resources and micro-grids. Companies like Siemens, ABB, and Schneider Electric, as well as numerous startups in the distributed energy sector, are actively working on similar solutions.
Market impact
This patent contributes to the ongoing evolution of micro-grid design and management. While it hasn't triggered specific lawsuits or created a new product category on its own, it represents a foundational approach to making micro-grids more efficient and reliable. Its focus on multi-objective optimization helps drive the adoption of hybrid renewable energy systems by addressing key concerns like cost, environmental impact, and power stability, which are critical for expanding access to electricity in underserved areas and enhancing grid resilience.
Claim 1 — Plain English
What this patent covers
The patent outlines a method for optimizing an independent micro-grid system, which includes diesel generators, wind generators, a photovoltaic array, and an energy storage battery. It works by first gathering device parameters for all these components. Then, a computer system uses a multi-objective genetic algorithm to find the best setup. This algorithm considers three main goals: minimizing total cost over the system's lifetime, reducing the chance of power outages (loss of load capacity), and lowering pollution levels. The method also uses a 'quasi-steady state simulation strategy' with two modes: a 'hard charging strategy' where diesel generators can charge the battery, and a 'power smooth strategy' where the battery only helps when diesel alone isn't enough. For example, it calculates how many diesel generators are needed at any moment, considering the current power demand, available renewable energy, and the battery's charge/discharge limits (Claim 1).
The clever bit
The clever part is the integrated multi-objective optimization using a genetic algorithm. It simultaneously balances conflicting goals—like saving money, keeping the lights on, and protecting the environment—while also factoring in complex operational details like diesel generator start-up modes and battery charging strategies, along with system stability requirements.
What it does not cover
- Does not cover optimization methods that use algorithms other than a multi-objective genetic algorithm, specifically one based on NSGA-II.
- Does not cover micro-grid systems that rely on different primary energy sources, such as hydropower or geothermal, instead of the specified diesel, wind, and photovoltaic combination.
- Does not cover control strategies for energy storage batteries that do not include both a 'hard charging strategy' and a 'power smooth strategy' as defined.
- Does not cover systems that fail to account for a 'preset spare capacity' to ensure the micro-grid's stability.
- Does not cover optimization models that do not simultaneously consider the three specific objectives: total cost, loss of load capacity, and pollution level.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Limited data
Citation count
0/40
No citations yet
Claim breadth
5/20
Moderate scope
Recency
10/20
Granted 5–10 years ago
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$21K – $67K
Midpoint $42K · 7.2 yr remaining · industry ×1.4
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
8 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Li, P., Chen, J., GE, X., Zhou, J., Zhang, X., & Zhao, B. (2018). Optimizing Power for Remote Grids with Diesel, Wind, Solar, and Batteries (U.S. Patent No. 9,985,438). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/9985438/optimization-method-for-independent-micro-grid-system
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does Optimizing Power for Remote Grids with Diesel, Wind, Solar, and Batteries cover?
This patent describes a computer-based method for designing and operating independent power systems, called micro-grids, to balance cost, reliability, and environmental impact using a mix of diesel generators, wind turbines, solar panels, and energy storage batteries.
Who owns patent US 9985438?
Electric Power Research Institute of State Grid Zhejiang Electric Power Co owns this patent, granted in 2018.
When does this patent expire?
This patent is expected to expire on October 14, 2033, when the invention enters the public domain.
What problem does this patent solve?
Independent micro-grids are crucial for providing reliable power to remote areas, islands, or military bases where connecting to a large central grid is impractical or too expensive. This patent offers a systematic way to design these systems, ensuring they are not only cost-effective but also reliable and less polluting. By optimizing the mix of renewable sources and traditional generators, it helps make off-grid power solutions more sustainable and widely deployable, especially in regions with limited infrastructure.
What does this patent NOT cover?
Does not cover optimization methods that use algorithms other than a multi-objective genetic algorithm, specifically one based on NSGA-II.
Patent monitoring