We aim for a decarbonized energy future. As the Energy Web Foundation states on their website: "Digitalized ‘proof of impact’ platforms can address existing market pain points and catalyze demand among buyers—multinational corporations, small- and medium-sized enterprises, electric vehicle fleets, decentralized blockchain networks—for impactful renewable energy investments... Energy Web is accelerating a low-carbon, customer-centric electricity system by enabling any energy asset owned by any customer to participate in any energy market."
As we enter the era of the data economy we see a lot of innovative solutions buing built on decentralized platforms like The Energy Web. Ocean protocol is the first mover in this field by tokenizing data assets and building service portfolios around datasets like compute-to-data and automated market making using the Balancer protocol.
Our solution is based on the premise that we can bridge both protocols for the sake of strengthening either one of them. The Energy Web is building trust leveraging verifiable certificates of renewable energy production using an SSI infrastructure whereas Ocean focuses on data assets at the center of their value proposition.
An excellent use case for the proposed bridge is the balancing of power, according to natural flows of electricity. You need to consume power the moment it is generated, therefore the energy grid is architected around energy planning partners. They have the responsibility for balancing consumption and production of power at each hour of the day. Renewable energy sources are challenging in this case because of the intermittency of power generation. To aim for decarbonization we need a near-realtime production forecast. Needless to say, the availability of reliable realtime data is key to this.
For this purpose we are going to use the trust network of EnergyWeb to identify renewable energy producing devices and verify their production certificates (EACs) and leverage the data infrastructure of Ocean to curate and verify production data of these devices. A simulation model shows the effects of this integration.