[Paper Review] Optimal sizing of solar photovoltaic and lithium battery storage to reduce grid electricity reliance in buildings

Han Kun Ren, Malcolm McCulloch+1 more|arXiv (Cornell University)|Jun 6, 2023

Smart Grid Energy Management4 citations

TL;DR

This study proposes a hybrid analytical-iterative method to optimally size solar photovoltaic (PV) and lithium-ion battery storage systems for buildings in Oxford, UK, minimizing grid electricity reliance and levelized cost of electricity. Results show solar PV is already economically viable, but lithium storage remains costly; despite declining prices, grid reliance persists due to system flexibility and cost constraints.

ABSTRACT

In alignment with the Paris Agreement, the city of Oxford in the UK aims to become carbon neutral by 2040. Renewable energy help achieve this target by reducing the reliance on carbon-intensive grid electricity. This research seeks to optimally size solar photovoltaic and lithium battery storage systems, reducing Oxford's grid electricity reliance in buildings. The analysis starts with modeling the electricity demand. The model uses Elexon electricity settlement profiles, and assembles them into the demand profile according to the quantity and types of buildings in Oxford. Then, solar generation is modeled using Pfenninger and Staffell's method. Solar photovoltaic and lithium storage systems are sized using a hybridized analytical and iterative method. First, the method calculates the solar system size search range, then iterates through the range. At each solar size, the method calculates and iterates through the storage system size search range. Within each iteration, the renewable system is simulated using demand and generation data with a simplified system set-up and the conventional operation strategy. The method outputs combinations of solar system capacity, storage system capacity, and grid electricity import. Each combination's levelized cost of electricity is calculated, and the lowest cost combination is the optimal sizing. Solar and storage system costs are projected from 2019 to 2100, and the optimal sizing is calculated for each year. The result shows that solar photovoltaic is economically competitive, but lithium storage cost is still too high. As solar and storage prices continue to drop, they will take up greater portions of the energy system. However, there will always be a need for the grid, as it provides flexibility and can meet demands that are too costly for solar and storage

Motivation & Objective

• To reduce grid electricity reliance in Oxford buildings to support the city’s 2040 carbon neutrality goal.
• To address the economic and technical challenges of integrating solar PV and battery storage in urban building energy systems.
• To determine the optimal combination of solar PV and battery storage capacity that minimizes the levelized cost of electricity (LCOE) over time.
• To project optimal system sizing from 2019 to 2100 under evolving solar and storage cost trends.
• To evaluate the long-term role of the grid in meeting energy demands when solar and storage are deployed at scale.

Proposed method

• Constructs building-specific electricity demand profiles using Elexon settlement data, aggregated by building type and quantity in Oxford.
• Models solar PV generation using Pfenninger and Staffell’s method to simulate hourly solar irradiance and output.
• Employs a hybridized analytical-iterative approach: first defines solar capacity search ranges, then iterates through storage capacity ranges at each solar size.
• Simulates each system configuration using simplified operation rules and historical demand and generation data to compute grid import.
• Calculates the levelized cost of electricity (LCOE) for each configuration to identify the optimal combination.
• Projects solar and battery costs from 2019 to 2100 to assess long-term economic viability and optimal sizing trends.

Experimental results

Research questions

• RQ1 What is the optimal combination of solar PV and lithium-ion battery storage capacity that minimizes grid electricity reliance in Oxford buildings?
• RQ2 How does the levelized cost of electricity (LCOE) vary with different solar and storage system sizes over time?
• RQ3 At what point do solar PV and battery storage become economically viable for widespread deployment in urban buildings?
• RQ4 To what extent can solar and storage systems eliminate the need for grid electricity, and what role does the grid retain in the long term?
• RQ5 How do projected cost reductions in solar and battery technologies influence optimal system sizing through 2100?

Key findings

• Solar photovoltaic systems are already economically competitive for reducing grid electricity reliance in Oxford buildings.
• Lithium-ion battery storage remains too expensive to be cost-competitive at scale, despite projected price declines.
• As solar and storage costs continue to fall, their share in the energy mix is expected to grow significantly over time.
• Despite high solar and storage deployment, the grid will remain necessary due to its role in providing system flexibility and meeting high-cost demand peaks.
• The optimal sizing of solar and storage systems evolves over time, with the most cost-effective configurations shifting as technology prices change.
• The hybrid analytical-iterative method successfully identifies the lowest LCOE configuration for each year from 2019 to 2100, enabling long-term planning under dynamic cost conditions.