Solar Power Expansion Creates New Grid Challenges
The rapid expansion of photovoltaic generation is transforming conventional electricity distribution systems into more active networks. Solar PV units can be installed close to electricity consumers, helping reduce feeder loading, improve voltage profiles, and increase the use of renewable energy.
However, greater solar penetration also creates new operational challenges. Because solar generation varies with sunlight conditions, high levels of PV integration can contribute to reverse power flows, voltage fluctuations, higher network losses, and reduced voltage stability. These challenges make the location and size of solar installations increasingly important for electricity network operators.
Ton's study addresses a limitation found in many existing PV planning approaches. Previous methods often prioritize reducing power losses or improving voltage regulation, while voltage stability is sometimes evaluated only after the optimization process has been completed.
According to the study, a solution that minimizes power losses does not necessarily provide the safest operating condition. A distribution network could still remain close to its voltage stability limit, particularly when electricity demand increases or renewable generation fluctuates.
Three Objectives Combined in One Optimization Framework
To address this issue, Ton developed a multi-objective PV planning framework that considers three factors simultaneously: active power loss, voltage deviation, and voltage stability margin.
The Voltage Stability Margin (VSM) measures how far the current operating condition is from the point at which voltage could collapse. A larger margin indicates that the network has more room to withstand changes in loading and renewable generation while maintaining stable operation.
The framework combines the Multi-Verse Optimizer (MVO) with the Backward/Forward Sweep (BFS) power-flow algorithm. In simple terms, MVO searches for the best combination of PV locations and capacities, while BFS evaluates how each candidate configuration affects the electricity network.
The approach was tested on standard 33-bus and 69-bus radial distribution systems. Three PV units were considered for each system, with individual capacities limited to 1.5 MW. The total PV capacity was restricted to 80 percent of the system's total active load demand. Voltage was maintained between 0.95 and 1.05 p.u., while branch currents were kept within their thermal limits.
The researchers also compared MVO with four other optimization techniques: Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), and Marine Predators Algorithm (MPA).
Power Loss Falls by More Than 66 Percent in the 33-Bus System
The first test used a 33-bus distribution network. Before PV installation, the system recorded 202.67 kW of active power loss.
After optimization using MVO, power loss fell to 67.58 kW, representing a reduction of approximately 66.65 percent.
The optimal PV locations were buses 13, 24, and 30, with capacities of 0.90 MW, 1.12 MW, and 1.18 MW, respectively.
Voltage performance also improved substantially. The minimum bus voltage increased from 0.9131 p.u. to 0.9784 p.u., while the Voltage Deviation Index decreased from 0.1335 to 0.0383, representing an improvement of more than 71 percent.
At the same time, the Voltage Stability Margin increased from 0.681 to 0.872, the highest value among the optimization methods tested.
MVO also completed the optimization in 6.54 seconds, faster than PSO, GWO, HHO, and MPA under the same testing conditions.
The 69-Bus System Shows Similar Improvements
The researchers then tested the proposed approach on a larger 69-bus distribution network. This system has longer feeders and greater electrical impedance, making voltage drops and power losses more significant.
Before optimization, the network recorded 224.98 kW of active power loss and a minimum bus voltage of 0.9092 p.u.
MVO reduced the power loss to 72.43 kW, equivalent to a reduction of approximately 67.81 percent. The optimal PV locations were buses 21, 61, and 64, with capacities of 0.99 MW, 1.16 MW, and 1.25 MW, respectively.
The minimum bus voltage improved from 0.9092 p.u. to 0.9802 p.u., while the Voltage Deviation Index fell from 0.1528 to 0.0408, a reduction of approximately 73 percent.
The Voltage Stability Margin also increased from 0.664 to 0.867, again producing the highest value among the compared optimization methods.
MVO completed the optimization in 7.46 seconds, maintaining its advantage in computational speed.
Implications for Renewable Energy Integration
The findings suggest that solar PV planning should go beyond simply maximizing renewable electricity production or minimizing energy losses. Voltage stability should be incorporated directly into the planning process to ensure that higher renewable penetration does not compromise the security of electricity networks.
For electricity network operators, the approach could provide a decision-making tool for identifying where solar PV units should be installed and how large they should be. Better PV placement can help reduce unnecessary power losses, improve voltage quality, and provide a greater stability margin as renewable energy penetration increases.
The study also highlights an important direction for future research. The current analysis uses fixed load demand and steady-state operating conditions. Future work could incorporate changing solar generation, time-varying electricity demand, battery energy storage systems, reactive power support, and multi-period optimization.
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