Worksite Microgrid Dispatch for Electric Machine Charging
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Solution Overview
Problem
Powering large electric work machines at remote job sites with limited or non-existent utility grid infrastructure is challenging, requiring efficient management of diverse energy assets and machine scheduling to minimize charging times and costs while maximizing productivity.
Innovation Solution
A microgrid system with a site controller that calculates energy demand, generates charging and power dispatch schedules, and optimizes the operation of energy assets and machines to balance supply and demand, considering factors like battery degradation and utility pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a microgrid system is constructed to provide energy at remote job sites with limited utility grid infrastructure, then energy availability and productivity are improved, but system complexity and operating cost increase
Solution Approach 1:
The microgrid system is segmented into multiple independent energy assets (generators, battery energy storage systems, photovoltaic sources, wind turbines, fuel cells) that can operate autonomously or in coordination. The site controller divides the scheduling problem into separate optimization tasks for each asset type, managing complexity through modular control while maintaining overall system productivity
Solution Approach 2:
The system employs dynamic scheduling that adapts to real-time conditions by optimizing asset activation and power apportionment based on current energy demand, pricing signals, and asset availability. The controller dynamically adjusts charging schedules and asset operation to balance productivity requirements with operating cost minimization
2Reliability
If energy assets are activated to meet energy demand, then energy supply is improved, but operating cost increases
Solution Approach 1:
The system performs preliminary optimization by pre-scheduling energy asset activation and power apportionment to meet forecasted energy demand. The site controller calculates optimal schedules in advance, considering future pricing signals and demand patterns, allowing the system to prepare cost-effective energy supply strategies before actual demand occurs
Solution Approach 2:
The optimizer adjusts operational parameters of energy assets (activation states, power levels) based on changing economic and operational conditions. By dynamically modifying these parameters in response to pricing signals and demand variations, the system maintains reliable energy supply while minimizing operating costs through optimal parameter selection
3Loss of time
If charging schedules are optimized to minimize charging times, then machine availability is improved, but energy demand peak increases
Solution Approach 1:
The charging schedule is structured as a periodic optimization problem where the site controller determines optimal charging windows and power levels for each machine over a scheduling horizon. By distributing charging across multiple time periods and adjusting power levels periodically, the system minimizes total charging time while avoiding excessive peak demand through rhythmic charge-discharge cycles of battery assets
Data Source
AI summary
A method of controlling a work site includes calculating energy demand by work machines to perform work over a predetermined time window; generating a charging schedule for the predetermined time window, wherein the charging schedule pairs chargers to the work machines and includes charging wait times for charging the work machines; generating a power dispatch schedule of activating, deactivating, apportioning power levels of energy assets of a microgrid system of the work site to supply the calculated energy demand during the predetermined time window; determining a difference between energy to be supplied by the energy assets and the energy demand for the predetermined time window; and operating the energy assets according to the power dispatch schedule and the chargers according to the charging schedule, and activating one or more energy storage systems of the microgrid system according to the determined difference between the energy demand and the energy supplied.