  ALEX (Autonomous Local Energy eXchange) is an economy-driven, transactive
local energy market where each participating building is represented by a
rational agent. Relying solely on building-level information, this agent
minimizes its electricity bill by automating distributed energy resource
utilization and trading. This study examines ALEX's capabilities to align
participant and grid-stakeholder interests and assesses ALEX's impact on short-
and long-term intermittence using a set of community net-load metrics, such as
ramping rate, load factor, and peak load. The policies for ALEX's rational
agents are generated using dynamic programming through value iteration in
conjunction with iterative best response. This facilitates comparing ALEX and a
benchmark energy management system, which optimizes building-level
self-consumption, ramping rate, and peak net load. Simulations are performed
using the open-source CityLearn2022 dataset to provide a pathway for
benchmarking by future studies. The experiments demonstrate that ALEX enables
the coordination of distributed energy resources across the community.
Remarkably, this community-level coordination occurs even though the system is
populated by agents who only access building-level information and selfishly
maximize their own relative profit. Compared to the benchmark energy management
system, ALEX improves across all metrics.
