Decentralized P2P Energy Trading under Network Constraints in a Low-Voltage Network (1809.06976v1)

Abstract: The increasing uptake of distributed energy resources (DERs) in distribution systems and the rapid advance of technology have established new scenarios in the operation of low-voltage networks. In particular, recent trends in cryptocurrencies and blockchain have led to a proliferation of peer-to-peer (P2P) energy trading schemes, which allow the exchange of energy between the neighbors without any intervention of a conventional intermediary in the transactions. Nevertheless, far too little attention has been paid to the technical constraints of the network under this scenario. A major challenge to implementing P2P energy trading is that of ensuring that network constraints are not violated during the energy exchange. This paper proposes a methodology based on sensitivity analysis to assess the impact of P2P transactions on the network and to guarantee an exchange of energy that does not violate network constraints. The proposed method is tested on a typical UK low-voltage network. The results show that our method ensures that energy is exchanged between users under the P2P scheme without violating the network constraints, and that users can still capture the economic benefits of the P2P architecture.

• The paper presents a novel method combining voltage sensitivity coefficients, PTDFs, and LSFs to manage network constraints during energy trades.
• A continuous double auction with ZIP traders on a UK low-voltage network demonstrates increased prosumer revenues and reduced energy spillages.
• The study offers a scalable framework for integrating distributed energy resources into smart grids, paving the way for advanced decentralized energy systems.

Decentralized P2P Energy Trading under Network Constraints in a Low-Voltage Network

The paper proposes a pioneering methodology for implementing decentralized peer-to-peer (P2P) energy trading in low-voltage networks while adhering to network constraints. The increasing adoption of distributed energy resources (DERs) and advancements in blockchain technology have made it feasible for households to trade energy directly. However, a major impediment lies in ensuring that such energy exchanges do not contravene network limitations, such as voltage or capacity constraints.

Methodology and Framework

The authors introduce a methodology based on sensitivity analysis, which integrates the technical operation of the network with P2P energy trading. This novel approach employs several analytical tools:

• Voltage Sensitivity Coefficients (VSCs): These coefficients are utilized to estimate changes in voltage that result from power shifts in the network due to energy transactions.
• Power Transfer Distribution Factors (PTDFs): PTDFs determine how power flow through the network lines is affected by specific energy transactions.
• Loss Sensitivity Factors (LSFs): These factors quantify the additional losses in the network due to energy exchanges between participants.

By applying these tools, the paper presents a model that allows participants to trade energy, ensuring that network constraints such as voltage limits and line capacities are not violated. Moreover, the model accounts for the attributed costs related to these constraints, making the mechanism financially viable for stakeholders.

Implementation and Results

The methodology is tested on a prototypical UK low-voltage network featuring a mix of consumers and prosumers with installed photovoltaic systems and storage units. A continuous double auction (CDA) matches supply and demand, leveraging blockchain technology to ensure transparency and decentralization. A central component of this process is the involvement of Zero Intelligence Plus (ZIP) traders in the CDA to emulate realistic trading scenarios without overly complex strategies.

The methodology subdivides the trading process into distinct steps: receiving energy bids, calculating the network impact, permitting trades that do not breach constraints, and charging costs appropriately. The paper demonstrates through simulations that this method allows efficient energy exchange while respecting the operational bounds of the network.

Comparative Evaluation

For validation, the proposed method is compared against several curtailment-based network management schemes. These include static capping of exported power, straight tripping once voltage thresholds are breached, and advanced droop-based curtailment strategies. Notably, the P2P framework shows superior economic benefits, highlighting increased revenues for prosumers and reduced energy spillages.

Implications and Future Directions

The research delineates a concrete strategy to enable decentralized energy trading, facilitating greater integration of DERs in urban energy systems. Practically, it promises reduced energy losses, optimized use of locally generated renewable energy, and enhanced consumer participation. Theoretically, it advances the discourse on decentralized energy systems and smart grids by providing a robust model for integrating network constraints with market mechanisms.

Future research directions may include exploring dynamic pricing models, incorporating multi-agent system simulations for enhanced strategy evaluation, and addressing data privacy concerns in the energy network’s digital infrastructure. Integrating more sophisticated AI-driven forecasting for consumer behavior and real-time energy usage patterns could further refine the P2P trading strategies under network constraints.

Overall, this paper lays foundational work for more adaptive and scalable decentralized P2P energy systems within the constraints of existing electrical networks, marking a significant stride in the evolution of smart grid technologies.