Techno-economic Analysis of Photovoltaic Distributed Generation Units, Capacitor Banks, and Electric Vehicle Charging Stations on Distribution Network. A Case Study of the Ashanti Region, Ghana

In many parts of the world, the electricity grid is a fragile thing. It is a vast network of wires carrying power from central plants to homes and businesses, but as demand grows and old infrastructure ages, the system often struggles to keep up. Two problems are particularly common in these stressed networks: the loss of energy as heat while it travels through the wires, and the dropping of voltage, which causes lights to dim and equipment to malfunction. These issues are becoming more urgent as countries try to add new sources of power, like solar panels, and new types of heavy loads, like fast-charging stations for electric vehicles. If these new elements are added without careful planning, they can make the existing problems worse, leading to blackouts or expensive damage. The challenge for engineers is to figure out exactly where to place these new assets and how big they should be so that they fix the grid's weaknesses rather than creating new ones.

This is the precise question a team of researchers from Ghana and the United States set out to answer. They focused on the Ashanti Region of Ghana, a real-world electrical network that is currently under significant strain. The grid there suffers from high energy losses and widespread low voltage, a condition where the electrical pressure drops too low to run devices properly. To solve this, the researchers developed a computer-based planning tool that treats three different technologies as a single, interconnected team: solar power generators, capacitor banks (devices that help stabilize electrical pressure), and fast-charging stations for electric vehicles. Instead of looking at these technologies in isolation, the study asked how they could work together to repair the grid. The team ran thousands of simulations on a digital twin of the actual Ashanti network, testing millions of different combinations of locations and sizes for these devices to find the perfect balance between technical performance and cost.

The results of this simulation were striking. The researchers found that by carefully coordinating the placement of solar panels, capacitors, and charging stations, they could transform the grid's performance. In their most successful scenario, the system reduced the amount of wasted energy by 81 percent. This means that for every unit of electricity generated, far more of it actually reached the customer instead of being lost as heat in the wires. At the same time, the plan eliminated every single instance of low voltage that existed in the original network. Before the changes, nearly thirty locations on the grid had voltage levels that were too low to be safe or reliable; after the optimization, every single bus, or connection point, was restored to a healthy, stable level. The study also showed that this technical repair came with a strong financial upside. Over a fifteen-year period, the savings from reduced energy waste and the revenue from selling solar power and charging services were projected to generate a net profit of approximately 36.69 million US dollars, even after accounting for the 26.60 million US dollars required to build the system.

To reach these conclusions, the researchers used two advanced computer algorithms, which are essentially sets of rules that help a computer search for the best solution among billions of possibilities. One algorithm, which the team improved upon, proved to be significantly more effective than the other. It found a solution that not only fixed the technical problems but also delivered a higher financial return. The study compared this improved method against a standard approach and found that the improved version could cut energy losses by nearly 89 percent on a standard test network, compared to only 62 percent for the standard method. On the real Ashanti network, the difference was even more critical: the improved method reduced losses by 81 percent, while the standard method only managed a 61.5 percent reduction. This suggests that the specific way the researchers programmed their search algorithm matters deeply when dealing with complex, real-world grids.

The study also highlighted the importance of looking at the long-term financial picture, not just the upfront cost. While the most effective plan required a larger initial investment of 26.60 million US dollars, the returns over fifteen years were substantial. The researchers calculated that the money saved by not wasting electricity, combined with the money earned from selling solar energy and charging fees, would pay back the initial cost in just two to three years. After that, the system would continue to generate profit for the remainder of the fifteen-year period. This finding challenges the idea that fixing a broken grid is purely an expense; instead, it shows that with the right mix of technologies, a utility company can turn a struggling network into a profitable asset. The research did not stop at the numbers, however. It also mapped out exactly where these devices should go. For instance, it identified specific buses, or connection points, in the Ashanti region where placing a large solar generator would have the biggest impact on reducing waste, and other specific spots where a capacitor bank would best stabilize the voltage.

One of the key insights from the work is that these three technologies—solar power, capacitors, and charging stations—must be planned together, not separately. If a utility company were to install solar panels in one location and charging stations in another without considering how they affect each other, the result might be a grid that is still inefficient or unstable. The study demonstrated that when these assets are treated as a single, coordinated system, the solar generators and capacitor banks can work in tandem to offset the impact of the charging stations. The solar panels provide active power generation to meet demand, while the capacitor banks supply reactive power to stabilize voltage, effectively counteracting the stress that the electric vehicle charging stations place on the grid as additional loads. This coordinated approach allowed the researchers to eliminate all voltage violations in the network, a feat that neither technology could achieve on its own in this specific context. The study also noted that the electric vehicle charging stations, modeled as additional loads that increase demand, actually contributed to the financial health of the project by providing a steady stream of revenue through charging fees.

The researchers were careful to ground their findings in the reality of the Ghanaian context. They used real data from the Ashanti Regional network, including the actual layout of the wires, the real load of electricity being used, and the specific costs of equipment in that region. They did not rely on idealized conditions or theoretical assumptions that might not hold up in practice. For example, they accounted for the fact that solar panels do not produce power at night and that electric vehicle charging happens at specific times of day. They also factored in the cost of replacing equipment, such as inverters, which are the devices that convert solar power into a form the grid can use. By including these real-world costs and constraints, the study provides a blueprint that utility companies in Ghana and similar regions could actually follow. The results suggest that even in networks that are currently struggling with high losses and low voltage, there is a path to a stable and profitable future, provided the planning is done with precision and coordination.

The study also compared its findings with previous research on similar networks to ensure its methods were sound. When tested on a standard, well-known electrical network used by researchers around the world, the improved algorithm performed better than many existing methods, reducing energy losses more effectively and finding solutions that were closer to the ideal. This gave the researchers confidence that their approach was robust. However, they also acknowledged the limits of their work. The results are based on computer simulations, which are powerful tools for testing ideas before building them, but they are not a guarantee of what will happen in the real world. The actual performance would depend on factors like weather patterns, changes in electricity demand, and the precise behavior of the equipment. Despite these limitations, the study offers a clear and compelling case for a new way of thinking about grid planning. It moves away from the old idea of simply adding more power or fixing one problem at a time, and instead proposes a holistic approach where different technologies are woven together to create a stronger, more efficient whole.

Ultimately, the work serves as a demonstration of how modern planning tools can help developing nations leapfrog older, inefficient stages of grid development. By using advanced algorithms to find the best mix of solar power, capacitors, and charging stations, the researchers showed that it is possible to turn a weak, high-loss network into a reliable and profitable system. The findings are particularly relevant for regions like the Ashanti, where the grid is under pressure from both aging infrastructure and rapid growth in new energy demands. The study suggests that the solution lies not in choosing between different technologies, but in understanding how they can work together. With the right planning, the grid can be rehabilitated, energy waste can be drastically reduced, and the system can generate enough profit to sustain itself for years to come. The path forward, according to this research, is one of coordination, precision, and long-term vision.