Linear energy storage and flexibility model with ramp rate, ramping, deadline and capacity constraints

TL;DR

This paper introduces a linear model for energy storage and flexibility that incorporates ramp rate, capacity, and deadline constraints, enabling efficient optimization and better representation of asset capabilities in power networks.

Contribution

It presents a novel linear programming model that accurately captures ramp rate and capacity constraints for energy assets, with an online repository for benchmarking and application.

Findings

Ramp rate constraints significantly impact profit margins.

Assets with slow ramp rates still achieve high arbitrage value.

The model is computationally efficient and suitable for practical use.

Abstract

The power networks are evolving with increased active components such as energy storage and flexibility derived from loads such as electric vehicles, heat pumps, industrial processes, etc. Better models are needed to accurately represent these assets; otherwise, their true capabilities might be over or under-estimated. In this work, we propose a new energy storage and flexibility arbitrage model that accounts for both ramp (power) and capacity (energy) limits, while accurately modelling the ramp rate constraint. The proposed models are linear in structure and efficiently solved using off-the-shelf solvers as a linear programming problem. We also provide an online repository for wider application and benchmarking. Finally, numerical case studies are performed to quantify the sensitivity of ramp rate constraint on the operational goal of profit maximization for energy storage and flexibility. The results are encouraging for assets with a slow ramp rate limit. We observe that for resources with a ramp rate limit of 10% of the maximum ramp limit, the marginal value of performing energy arbitrage using such resources exceeds 65% and up to 90% of the maximum profit compared to the case with no ramp rate limitations.