Hjalmar Turesson

Marek Laskowski, Michael Zargham, Hjalmar Turesson et al.

We present a methodology for evidence based design of cryptoeconomic systems, and elucidate a real-world example of how this methodology was used in the design of a blockchain network. This work provides a rare insight into the application of Data Science and Stochastic Simulation and Modelling to Token Engineering. We demonstrate how the described process has the ability to uncover previously unexpected system level behaviors. Furthermore, it is observed that the process itself creates opportunities for the discovery of new knowledge and business understanding while developing the system from a high level specification to one precise enough to be executed as a computational model. Discovery of performance issues during design time can spare costly emergency interventions that would be necessary if issues instead became apparent in a production network. For this reason, network designers are increasingly adopting evidence-based design practices, such as the one described herein.

Hjalmar Turesson, Henry M. Kim, Marek Laskowski et al.

Blockchains rely on a consensus among participants to achieve decentralization and security. However, reaching consensus in an online, digital world where identities are not tied to physical users is a challenging problem. Proof-of-work provides a solution by linking representation to a valuable, physical resource. While this has worked well, it uses a tremendous amount of specialized hardware and energy, with no utility beyond blockchain security. Here, we propose an alternative consensus scheme that directs the computational resources to the optimization of machine learning (ML) models, a task with more general utility. This is achieved by a hybrid consensus scheme relying on three parties: data providers, miners, and a committee. The data provider makes data available and provides payment in return for the best model, miners compete about the payment and access to the committee by producing ML optimized models, and the committee controls the ML competition.

Shivam Saxena, Hany Farag, Hjalmar Turesson et al.

Transactive Energy Systems (TES) are modern mechanisms in electric power systems that allow disparate control agents to utilize distributed generation units (DGs) to engage in energy transactions and provide ancillary services to the grid. Although voltage regulation is a crucial ancillary service within active distribution networks (ADNs), previous work has not adequately explored how this service can be offered in terms of its incentivization, contract auditability and enforcement. Blockchain technology shows promise in being a key enabler of TES, allowing agents to engage in trustless, persistent transactions that are both enforceable and auditable. To that end, this paper proposes a blockchain based TES that enables agents to receive incentives for providing voltage regulation services by i) maintaining an auditable reputation rating for each agent that is increased proportionately with each mitigation of a voltage violation, ii) utilizing smart contracts to enforce the validity of each transaction and penalize reputation ratings in case of a mitigation failure and iii) automating the negotiation and bidding of agent services by implementing the contract net protocol (CNP) as a smart contract. Experimental results on both simulated and real-world ADNs are executed to demonstrate the efficacy of the proposed system.