Dual Battery Energy Storage Systems Offer Optimal Cost and Performance in Renewable-Integrated Grids

Why It Matters

As renewable energy sources become more prevalent, managing grid stability and efficiency becomes critical. This research demonstrates that a carefully planned, multi-point BESS deployment can effectively mitigate issues like voltage instability and power losses, leading to a more robust and cost-effective energy infrastructure.

Key Finding

The study found that using two Battery Energy Storage Systems (BESSs) in a renewable energy grid is the most cost-effective solution, outperforming single or multiple BESS setups. The proposed optimization method, COA, was effective in finding these optimal placements and sizes, leading to reduced costs and power losses.

Key Findings

• The optimal locations and capacities for BESS units are technically feasible for real-world deployment.
• The Crayfish Optimization Algorithm (COA) consistently outperforms comparative optimization methods in cost minimization and loss reduction.
• The two-BESS installation scenario provides the most balanced and cost-effective performance compared to one or three BESS units.

Research Evidence

Aim: To determine the optimal number, locations, and capacities of Battery Energy Storage Systems (BESSs) within a renewable energy-integrated distribution network to minimize total system costs, including investment and performance-related expenses.

Method: Optimization Framework using a Metaheuristic Algorithm (Crayfish Optimization Algorithm - COA)

Procedure: An optimization framework was developed using the Crayfish Optimization Algorithm (COA) to identify the best locations and capacities for multiple BESS units in a distribution network with integrated renewable energy sources. The framework aimed to minimize total system costs, considering BESS investment, voltage deviation, transmission loss, and peak power reduction. The framework was tested on a real-world distribution network with photovoltaic (PV) and biomass generation, analyzing scenarios with one, two, and three BESS units.

Context: Distribution networks integrated with renewable energy sources (RESs), specifically a real-world system with 102 buses incorporating photovoltaic (PV) and biomass distributed generation.

Design Principle

Strategic multi-point energy storage deployment optimizes system cost and performance in complex, renewable-integrated grids.

How to Apply

When designing solutions for renewable energy integration in distribution networks, use optimization algorithms to identify the most cost-effective number and placement of BESS units, with a strong consideration for a two-unit configuration.

Limitations

The study's findings are based on a specific real-world case study and may vary for networks with different characteristics, RES penetration levels, or load profiles. The performance of the COA was compared against other metaheuristic algorithms, but a broader comparison with other optimization techniques might yield further insights.

Student Guide (IB Design Technology)

Simple Explanation: Putting two battery storage systems in the right spots in an electricity grid that uses solar and wind power can save the most money and make the grid work better than using just one or more than two.

Why This Matters: This research is important for design projects involving renewable energy systems because it shows how to practically improve grid stability and reduce costs, which are key challenges in modern energy design.

Critical Thinking: How might the 'optimal' number and placement of BESSs change if the primary objective shifts from cost minimization to maximizing grid resilience during extreme weather events?

IA-Ready Paragraph: This research highlights the significant benefits of strategically deploying multiple Battery Energy Storage Systems (BESSs) in renewable energy-integrated distribution networks. The study's findings suggest that a configuration of two BESS units, optimally located and sized using advanced optimization algorithms like the Crayfish Optimization Algorithm (COA), offers the most cost-effective and performance-enhancing solution by minimizing system costs, voltage deviations, and transmission losses, thereby providing a robust model for grid modernization.

Project Tips

• When modeling energy systems, consider the trade-offs between the number of storage units and their individual capacities.
• Explore different optimization algorithms to find the most efficient solution for resource allocation problems.

How to Use in IA

• Reference this study when discussing the optimization of energy storage systems for renewable integration, particularly when justifying the number and placement of BESS units in your design proposal.

Examiner Tips

• Ensure that any optimization performed in a design project is clearly justified and that the chosen algorithm is appropriate for the problem complexity.
• Demonstrate an understanding of the trade-offs involved in selecting the number and capacity of energy storage solutions.

Independent Variable: ["Number of BESS units (1, 2, 3)","Location of BESS units","Capacity of BESS units"]

Dependent Variable: ["Total system costs (BESS investment, voltage deviation, transmission loss, peak power reduction)","Voltage stability","Transmission losses"]

Controlled Variables: ["Distribution network topology","Renewable energy source (RES) generation profiles (PV, biomass)","Load profiles","Optimization algorithm used (COA)"]

Strengths

• Application to a real-world case study provides practical relevance.
• Comparison of multiple BESS installation scenarios (1, 2, 3 units) offers a comprehensive analysis.
• Demonstration of a novel optimization algorithm (COA) outperforming others.

Critical Questions

• What are the specific criteria used to define 'optimal' locations and capacities beyond cost minimization?
• How sensitive are the results to variations in the input data, such as RES generation forecasts or load demand?

Extended Essay Application

• Investigate the economic viability and technical feasibility of implementing a dual-BESS strategy in a local community's microgrid, considering specific renewable energy sources and local grid constraints.

Source

Optimal locations and capacities of multiple BESSs in a RES-integrated distribution network: a real-world case study · Scientific Reports · 2026 · 10.1038/s41598-026-40971-z