–Creating a sustainable smart ecosystem and pioneering a framework that integrates distributed green energy with AI computing power, the green energy and computing power RWA model design is a must-read!

–Green energy and AI computing power RWA satisfies all your ideas and fantasies, but we bet you won’t be able to read or understand it word for word~~~

In the previous article, “‘Green Energy + DePIN + AI’ is the Best RWA Asset”, we discussed the ecosystem framework supported by DePIN for green energy + AI. We argued that: while the financial foundation of the past two decades has been “land + real estate,” the financial foundation of the next two decades will be “green energy + computing power + DePIN.”

Recently, new RWA projects have continuously validated this idea, especially the issuance of compliant RWA projects in Hong Kong, mostly centered around green energy and computing power. The second part of the framework is the “Green Energy + Computing Power + Smart Devices (DePIN)” new impossible triangle, which delves into green energy computing assets, RWA models, new financial systems, and smart devices.

High computing power requires high energy consumption, essentially posing challenges related to energy supply and carbon emissions. To achieve higher computing power, we need more energy, which likely leads to higher carbon emissions. Consider the following data: In 2023, Amazon announced that the total power purchase under its corporate power purchase agreements (PPAs) reached 8.8 GW; Meta also disclosed its 3GW power purchase agreements; In May 2024, Microsoft signed over $10 billion in clean energy purchase agreements; Apple’s product launch video at the beginning of the year focused on its zero-carbon path; and OpenAI’s CEO Sam Altman publicly stated, “The two currencies of the future will be computing power and energy, and AI technology depends on breakthroughs in energy.”

Ultimately, the challenge for green computing power is carbon efficiency. We must focus on the higher energy consumption of computing power and consider the carbon emissions from computing power (whether it’s greener).

1. Underlying Assets: Distributed Green Computing Power Yield Assets

The understanding of green energy computing assets is often constrained by traditional frameworks and needs to be unpacked layer by layer.

Standalone computing power assets are relatively easy to understand, primarily focused on AI computing power (which is now divided into various categories, such as smart computing, supercomputing, etc., based on the type of computing devices), with special mention of Bitcoin computing power. While the oil-dollar system is crumbling, energy remains a core foundation, but there’s a trend towards energy transformation, moving towards green energy. The uniqueness of Bitcoin computing power lies in the fact that Bitcoin may become a reserve asset for the U.S. or more countries, even serving as a partial anchor for currencies and national bonds, meaning that large amounts of foundational assets will need to be tied to Bitcoin. The most direct link is Bitcoin computing power.

Standalone green energy assets are also relatively easy to understand. Green energy is the core energy of the Earth, primarily derived from solar power, and the assets surrounding green energy may include various renewable energy generation assets (mainly solar power), energy storage assets, new energy vehicles and charging facilities, green energy certificates (REC), and carbon credit assets. Particularly in the areas of solar storage and green energy certificates/carbon credits, there are already large amounts of distributed assets for households or end-users (2C). The ultimate goal of AI is green energy; the ultimate goal of Bitcoin computing power is also green energy; and even the foundations of industries like steel and aluminum also aim for green energy, as they are both high-energy industries that require green emission reductions. In fact, based on home-based distributed energy devices, individuals may eventually become carbon-silicon hybrids: “Brains in a vat” or “brain + robots,” meaning that any industry or individual will operate based on “green energy + AI computing power.”

In the previous article, we discussed green energy P2P trading and VPP microgrids. Whether in China, where insufficient market conditions prevent grid-based power trading, or in fully developed markets in Europe and the U.S., where P2P trading is possible, there’s one core issue: most VPP microgrids are grid-connected and cannot escape dependence on public power distribution networks. Currently, true off-grid solutions can only be achieved in localized areas, such as large mining farms, industrial parks, or factories, where they can achieve complete independence using solar power and other renewable energy sources. This is the only way to enable true VPP and P2P trading. However, for grid-connected VPPs and P2P, the only viable model is: “Green Energy + AI Computing Power + Smart Devices (DePIN).”

This brings us back to the consensus: “Green Energy > Electricity > Computing Power > Basic Models > Applications.” The key to solving the grid connection and P2P trading problem is to work backwards, starting from applications and basic models. The best trading asset is not green energy itself, nor a simple combination of green energy assets + computing power assets, but rather green energy computing yield assets. By combining green energy and AI computing power, these assets can be used by large models or application models for distributed pre-training, inference, rendering, and other applications.

Green Computing Power Yield Assets

Yield assets refer to the usage and income rights of green computing power assets, rather than ownership. The holder of the transaction can use the green computing power assets and receive the income within the agreed period but does not need to own the assets themselves. Due to physical or legal limitations, green energy cannot be directly transmitted from point to point, and yield asset trading offers the usage rights of green energy and AI computing power. Through green computing power, specific computational tasks are completed, and clients receive the computation results, enjoying the value of using green computing power, rather than owning the green energy or AI computing power assets themselves. This aligns with the model of AI computing power services, where clients enjoy the right to use computing power assets.

Since green computing power yield assets have dissipative characteristics and are time-bound, such as GPU hours or green GPU hours, the smart contracts for yield asset transactions need to clearly define the duration, scope, pricing method, income model, task verification methods, and other parameters of the usage rights for green computing power assets. This helps facilitate smooth transactions.

Therefore, the core underlying asset is the green computing power yield asset, no longer distributed energy resources (DER), but rather DGCR (De Green Computing Re), distributed green computing resources. This resolves the core issues of VPP and P2P trading, moving beyond grid-connected green energy to off-grid DGCR. Moreover, AI computing power and distributed model optimization can provide solutions for optimizing green energy management, dynamically configuring green computing power resources, and efficiently utilizing green computing power resources.

This section also touches on the development of Distributed Artificial Intelligence (DAI), also referred to as decentralized AI computing power. It avoids the large-scale, high-energy consumption of centralized smart computing supercomputing centers and instead uses distributed green computing or edge computing to implement a new approach that can reconstruct how distributed green energy infrastructure interacts with the environment, physical devices, computing power, and end users. The development of distributed computing also drives new technologies like edge computing to build pre-training or inference gateways, enabling distributed decomposition and edge computing of large model pre-training or inference tasks.

On this basis, as a dissipative asset with time attributes, green computing power yield assets can receive distributed computing tasks via the network and complete transactions. Some centralized green computing power centers with underutilized computing power can also participate in providing liquidity for green computing power yield assets, by staking idle computing power into pools on an hourly basis. The liquidity AMM algorithm of the green computing power trading platform can then directly optimize the configuration. This achieves marketization of issues like uneven demand for green computing power, time-sensitive tasks, on-demand computation, and non-time-sensitive computation, while also combining edge computing with personal scenarios and data, potentially unlocking further derivative value.

Green computing power yield assets require a new consensus, which we call the “PoGCS” Consensus. On-chain, there is a mechanism for green energy computing power assets to enter the pool, which can be done either by separately pooling green energy and computing power or by binding them together through a common DePIN smart device. The on-chain asset confirmation, location (unique distributed location addresses and rights), and coordination conditions for entering the pool (staking, random entry, limited condition entry, etc.) must also be defined. The smart device can also apply to operate as a green computing power light node on the chain, enabling a BaaS (Blockchain as a Service) for green computing power.

The best model for bringing green computing power assets on-chain is not to put devices and data on the blockchain, but for smart devices supported by DePIN to directly become distributed light nodes on the green computing power chain. The key question is: what type of smart devices will your green computing power RWA project design?

2. Green Computing Power RWA Model

Green computing power RWA (Real-World Asset) is not limited to green computing power yield assets; it also includes different asset package designs for both green energy and AI computing power assets, as well as REC green energy certificates and carbon credit assets. RWA underlying assets correspond to asset pools on the blockchain, such as green energy asset pools, computing power asset pools, and even green computing power asset pools based on blockchain node smart devices. In terms of expected income and operating cash flow, it includes long-term contracts for computing tasks, random distributed inference tasks, operating income from green energy assets like solar-storage-charging, etc.

Due to the green low-carbon concept of green energy, green computing centers can issue traditional green bonds for new infrastructure computing centers or green ABS (Asset-Backed Securities). If it’s a green computing cluster or a group of green computing centers with scheduling operations, a virtual green computing power asset pool can be created and packaged into a green computing power yield asset package to issue green computing power fixed-income bonds or establish a green computing power guiding fund. The former’s green computing power ABS and the latter’s green computing power yield asset packages both require the establishment of reasonable mezzanine SPV or trust structures.

Green computing power RWA needs to fully learn and adapt the models of real estate finance to establish a green computing power capital model.

The green computing power capital model divides green computing power assets into different categories and development stages, establishing various green computing power funds or crypto funds. These could involve publicly listed companies in traditional financial markets, issuing RWA tokenized asset packages in different models, and combining liquidity pools and trading platforms to issue liquidity NFTs (digital asset securitization/equity certificates).

Based on RWA asset pledges, stablecoins for green computing power can be issued, further generating a green computing power crypto fund and a PayFi system for the green computing power industry’s payment settlement and investment.

Based on RWA asset pledges and PayFi applications, green computing power platform tokens (crypto asset stocks) can be issued on a compliant regulatory basis in locations like Singapore or Dubai. These tokens can be used to submit proposals, make decisions, and raise funds.

A Future Crypto Fund can be established, using green computing power tokens to acquire new green computing power assets and issue new RWA asset packages.

Additionally, based on REC green certificates and carbon credit assets, carbon asset NFTs and carbon coins can be issued, and a green computing power ESG investment fund based on carbon coins can be established around the narrative of carbon assets and green computing power communities.

Standard Investment Model for RWA

The standard investment model for green computing power RWA is based on the green energy ecosystem, with an added AI computing power component, resulting in three standard investment models. These standardized models often correspond to standardized smart devices:

1. Green Smart Energy Station: A 2B model of integrated solar-storage-charging smart energy stations, with rooftop solar power + AI computing power, supporting charging, entertainment, regional AI inference and rendering tasks, peak shaving and valley filling for electricity price arbitrage, and other green computing applications. This model forms a typical standardized green smart energy node, which can precisely calculate the overall input, actual output, and return-on-investment cycle of the node.
2. Green Smart Charging and Storage Piles: A 2B model green energy (solar/nuclear) charging piles with energy storage and AI computing power, distributed across multiple charging and storage pile stations with power distribution equipment and AI computing power devices. This forms a regional green energy computing power center, another typical standardized green smart charging and storage node.
3. Green Smart Home Solar-Charge-Storage-Compute Integration: A 2C model standard green home investment model. Some homes in Europe and the U.S. follow a farm model, which is similar to small-scale 2B industrial charging-storage-computing integration. If based on standardized smart integrated devices, a green smart home with “roof solar panels + home storage + new energy vehicles + home AI computing power center + robots/VR/gaming” can also be developed into a standard green smart home solar-storage-charging-computing investment model.

Green Computing Power RWA Product Agreements

Common RWA product agreements are typically based on fixed-income rights derived from expected income and operating cash flow, so both green energy and computing power assets can have their own fixed-income RWA products.

For example, green energy RWA products can include bonds for charging pile income rights, bonds for energy storage on the generation side, and bonds for industrial storage income rights on the consumption side. AI computing power RWA can include bonds for AI computing power rental income rights, or ABS (asset-backed securities) backed by AI computing devices with stable cash flow.

Of course, the core innovation is still in the green computing power yield asset RWA. With the support of smart device nodes, green energy and computing power assets can form a virtual green computing power asset pool, leading to a series of innovative green computing power yield asset RWA agreements.

Green computing power virtual asset pools use smart device nodes to bring green energy and AI computing power yield assets into a transparent and controllable green computing power asset pool, categorized by device type, through an asset pooling algorithm protocol. Based on the PoGCS consensus, the pooled assets can be staked to issue green computing power RWA yield assets (which can be rented or traded), with platform tokens staked into the liquidity pool. Green computing power demand-side users can stake to issue computing power demand contracts into the liquidity pool, detailing specific AI task requirements (such as model training, inference, and rendering), and stake tokens as incentives for task completion. The liquidity pool uses decentralized green computing power yield asset trading algorithms—such as Automated Market Maker (AMM) mechanisms and AI algorithms—to achieve dynamic trading and optimization of green computing power yield assets, with improved dynamic algorithms optimizing asset trading prices and liquidity distribution.

The improved AMM algorithm adds a polling time dimension (hours) based on the dissipative asset properties of green energy and AI computing power. It polls whether the green computing power yield assets are online, ongoing, or exiting the liquidity pool, ensuring smooth green computing power yield asset transactions. Task completion can be verified using recursive zero-knowledge proofs or other technologies to validate the completion of each node’s green computing power task.

The RWA protocol issues RWA asset packages for staked green computing power yield assets, open to secondary market investors (LP investors in the liquidity pool). Additionally, based on computing power demand contracts and asset transactions, the RWA protocol generates position NFTs for pledged computing power assets. Holding a position NFT entitles the holder to token income and incentives from the computing power contract’s completion. These position NFTs can be directly exchanged in the liquidity pool or traded in secondary markets, without affecting the execution of the computing power demand contract. They can also be staked for loans to gain token liquidity, further investing in green computing power assets.

This liquidity trading algorithm and liquidity pool form the core of an RWA exchange and can also be expanded into a vertical green computing power RWA trading platform.

Based on green computing power yield asset RWA products, further development can include financial products such as staking loans, insurance, and options, providing diverse investment choices for equipment providers and liquidity providers. Using the green computing power assets in the virtual asset pool as reserve assets, a stablecoin pegged to green computing power can be issued as a value-stabilizing tool based on green computing power assets. Furthermore, a green computing power index can be developed to provide price anchoring for the stablecoin.

Stablecoins can be used for payments, collateral, and settlement related to green energy and AI computing power, enhancing the market liquidity of green computing power assets.

Green Computing Power RWA Multi-Layer Market Design

Drawing from the U.S. Treasury Bill (T-Bill) model, the capital market design for Green Computing Power RWA (Real-World Assets) can be divided into four layers:

First Layer: Green Computing Power RWA products are issued in the form of traditional debt on licensed and compliant exchanges, such as licensed brokers and exchanges in Hong Kong or licensed institutions in Singapore. This completes the private placement issuance and primary market of green computing power RWA products.

Second Layer: Similar to the T-Bill model, tokenized securities products of compliant Green Computing Power RWA assets are issued based on compliant regulatory frameworks in Singapore or Dubai. This involves staking to issue second-layer green computing power governance or platform tokens, listing them on licensed exchanges in Singapore or Dubai, and forming a secondary market supported by green computing power RWA underlying assets. In this layer, green computing power stablecoins are issued based on the compliance framework.

Third Layer: On this foundation, a green computing power liquidity pool is formed by combining ATS (Alternative Trading System) and offshore exchanges. This pool integrates green computing power RWA underlying assets, governance or platform tokens, and stablecoins. It can also expand into a Green Computing Power RWA exchange and further develop DeFi products such as green computing power lending, insurance, futures, options, TRS (Total Return Swaps), etc.

Fourth Layer: As the green computing power ecosystem expands, green energy certificates (REC) and carbon credit assets in various industry sectors and scenarios, especially in 2C household green computing power smart devices, can be issued as carbon coins. These act as a tokenized intermediary to bridge carbon reduction credits (CCER) in China and carbon reduction certificates (CER) in Europe, based on the compliance framework in Singapore.

3. The New Financial System of Green Computing Power

The underlying infrastructure for the next generation of finance in the next 20 years will be “Green Energy + Computing Power + DePIN”, just as the financial infrastructure in the past two decades has been based on “Land + Real Estate”.

At the asset level, the most critical elements are green energy assets and computing power assets. Energy strategies will shift toward green energy, while computing power assets will include mainstream AI computing power and specialized BTC computing power. Green energy and computing power assets will be integrated into distributed VA (Virtual Asset) pools through DePIN (Decentralized Physical Infrastructure Networks) protocols and smart devices. Other FA (Financial Asset) and alternative assets will also enter the pool via various infrastructure, sidechains, or DePIN technology.

The key to DePIN distributed protocols and smart devices is their ability to run lightweight nodes on the blockchain based on physical device proof of work, thus enabling the RWA infrastructure for the new financial system, i.e., BaaS (Blockchain as a Service).

Distributed VA asset pools are crucial for pooling and controlling assets, and they will require the establishment of an asset oracle mechanism. Building on this, staking models will form different controllable and usable virtual asset pools, such as virtual green energy pools, virtual computing power pools, and virtual green computing power yield asset pools, with nodes combining into DAO mechanisms.

Third Layer: Through asset pooling algorithms, dynamic pricing, and liquidity trading algorithms, the pooling, control, and trust of green computing power yield assets will be achieved, further enabling the tokenization of RWA. If standardized, this will be an RWA protocol product; if non-standard, it will be specific RWA investment banking service projects.

On the basis of liquidity pools and liquidity trading algorithms, diverse market participants will be introduced, including buyers, sellers, liquidity providers (LP), market makers (MM), and arbitrage speculative investors. A trading market will be created by combining decentralized exchanges, liquidity exchange pools, and ATS dark pools.

Fourth Layer: Based on green computing power yield assets, equity-like, crypto stock-like, and T-REITs (Real Estate Investment Trusts) RWA products will be issued. In the second layer, based on staking, new crypto-financial products such as green computing power lending, options, futures, insurance, TRS synthetic assets, etc., will be derived. The most important development will be the further issuance of green computing power stablecoins and green computing power indices.

Finally, at the application layer, users and investors can use green computing power stablecoins and consumption cards, hold or trade green energy certificates (REC) and carbon credit assets, and engage in smart arbitrage scenarios for household green computing power.

4. The New Smart Devices in Green Computing Power

The core assets of green computing power, Green Computing Power RWA, and the new financial system all revolve around the “Green Energy + AI Computing Power + Smart Devices” new Impossible Triangle. As illustrated below:

(Illustration of the “Green Energy + AI Computing Power + Smart Devices” Impossible Triangle)

In this green computing power Impossible Triangle, AI computing power represents larger scale (centralization) and greater energy consumption (carbon reduction), green energy signifies a greener and more low-carbon approach, while smart devices based on DePIN (Decentralized Physical Infrastructure Networks) represent more distributed systems, often on a smaller scale, even down to household distribution.

Within this model, smart devices, combined with DePIN distributed protocols and PoGCS consensus lightweight nodes, will become intelligent terminal nodes in the virtual green computing matrix. These devices are the core infrastructure of distributed green computing power assets and serve as smart mining machines for green computing power or carbon assets. However, in the context of real-world assets, they are tangible smart devices, such as solar-storage-charging-computing devices. (So, have you ever thought about what your smart device would look like?)

Green computing power smart devices take two forms:

• 2B (Business Model): This could be a distributed green energy smart energy station or an intelligent charging pile with storage and computing power.
• 2C (Consumer Model): This could be a zero-carbon household smart energy-storage-charging-computing integrated device.

These smart hardware devices function as mining machines, with green energy and computing power usage akin to mining. Smart devices in the 2B model can operate or be upgraded to become green computing power regional nodes or regional computing power centers, connecting distributed household nodes for distributed inference rendering or edge computing.

Distributed zero-carbon household smart energy-storage-charging-computing devices will carry forward more social responsibility and grand narratives within the cryptocurrency world. These devices could enable real-world applications like AI-driven dynamic electricity price arbitrage, household robots and VR-powered smart devices forming a computing power center, and in the crypto world, distributed green mining machines, AI agents, and UBI (Universal Basic Income) systems. The smart device could create a “roof-top photovoltaic panel - energy storage - charging pile - intelligent computing center - household smart robot - super space entertainment system,” which, under specific conditions, could achieve a completely off-grid green intelligent computing ecosystem and a zero-carbon lifestyle. We can imagine a future with family smart robots or embodied intelligent robots, as seen in sci-fi films. Future households will require a green lifestyle intelligent computing center: real-time embodied intelligent computing by household robots, local rendering for game entertainment like Black Myth, predictive and management of family green energy and smart appliances, AI-driven family data, consumption, health calculations, and more.

Conclusion

The concept of the Impossible Triangle of “Green Energy + Computing Power + Smart Devices” integrates green energy, AI computing capabilities, and distributed smart devices to construct an efficient, low-carbon, and sustainable intelligent ecosystem. This ecosystem drives the green transformation of energy and computing and lays a solid foundation for future smart homes and smart communities. With proper system design, innovative business models, and effective financing strategies, we can turn this forward-looking concept into reality, facilitating the deep integration of green computing power and smart devices to achieve a win-win scenario of economic and environmental benefits.

ARAW Always RWA Always Win! To promote orderly market development, we plan to recruit partners for a private board of directors and launch practical private board workshops for RWA project issuance, cultivating RWA channel partners and RWA investment advisors. Business owners and talented young individuals are welcome to contact us privately.

We will also gradually conduct AMA discussions and workshops on various industry tracks and themes. Feel free to join our WeChat group, YekaiMeta, to participate in RWA industry discussions and product track deliberations.

This article was submitted by a contributor and does not necessarily represent the views of BlockBeats.

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