No abstract

Peer-to-peer (P2P) energy trading is a mechanism that allows people to share locally the energy they have generated from distributed renewable resources (DER), to generate profit form the unused resources and to reduce the cost for electricity for the household and in the community itself. This calls for the design of new energy markets, accompanied with the development of comprehensive exchange strategies, which reflect both the consumer?s preferences and the heterogeneity of the renewable sources. The paper presents a study of the behavior patterns of individual prosumers using bidding strategies based on the State-of-Charge of the battery and two different pricing algorithm, one with fixed prices and one based on the battery price of each standalone system as well as the effect such patterns have on a local energy market with solar panels, fuels cells and batteries. The evaluation is achieved by the use of a prototype based on the Open Energy Systems (OES), a community in Okinawa, Japan, made of 19 interconnected houses with residential storage, photovoltaic cells and AC grid connection. In order to simulate heterogeneity, a fuel cell, modeled after Ene-Farm, is added to the original configuration. Each house has a power flow management system, which uses a priority-based algorithm to maintain demand-response efficiency, capable of scheduling the operating hours of the available fuels cells. The energy market is based on Zaraba, a continuous double auction algorithm used by the Japanese Stock Exchange, in which prosumer can bid for a desired amount and price of electricity for a 30-minutes time slot in the future The preliminary numerical evaluation is based on the results from several simulations using different versions of the bidding agent.

The study presented in this paper aims to show the impact of introducing a priority-based internal power flow management system on the local energy market of prosumers with solar panels, fuels cells and batteries. The community used for the study is based on the Open Energy Systems (OES), in which 19 autonomous subsystems, equipped with batteries, solar panels and AC grid connection are interconnected via a DC power bus. For the simulation purposes, fuel cell, modeled after Ene-Farm, is added to the original configuration. Each standalone system has internal, priority-based, agent, capable of scheduling the operating hours of the fuels cell to maximize the utilization of the generation and minimize curtailment. The energy market is based on a simplified version of the Zaraba, a continuous double auction algorithm used by the Japanese Stock Exchange, in which prosumer can submit a bid for a future timeslot. The preliminary numerical evaluation is based on the results from several simulations using different versions of the internal management system.