Implement plan
Scenario 1: High PV Capacity House
Step 1: Initially, we will construct a model with Microgrid, a high-capacity rooftop PV house integrated with a shared Community Battery Energy Storage System (CBESS) and residential load.
Step 2: Then, we implement an Adaptive Intelligent Fuzzy Logic Controller (AIFLC) and NSGA-11 algorithms for intelligent power flow management .
Step 3: Next, we simulate the model and collect the simulated voltage,current,power and SOC data.
Step 4: Next, we implement multi-objective optimization to detect optimal energy scheduling, battery coordination, and excess solar energy sharing based on collected data.
Step 5: Next, we analyze residential load conditions , energy trading and grid power consumption data.
Step 6: Finally, we plot performance metrics for the following:
6.1: Time vs Voltage (V)
6.2: Time vs Current (A)
6.3: Time vs Power (KW)
6.4: Time vs SOC (%)
Scenario 2: Medium PV Capacity House
Step 1: Initially, we will construct a model with grid, medium-capacity rooftop PV house connected with shared CBESS and community load.
Step 2: Then, we implement an Adaptive Intelligent Fuzzy Logic Controller (AIFLC) and NSGA-11 algorithms for intelligent power flow management .
Step 3: Next, we simulate the model and collect the simulated voltage,current,power and SOC data.
Step 4: Next, we implement multi-objective optimization to detect optimal energy scheduling, battery coordination, and excess solar energy sharing based on collected data.
Step 5: Next, we analyze residential load conditions , energy trading and grid power consumption data.
Step 6: Finally, we plot performance metrics for the following:
6.1: Time vs Voltage (V)
6.2: Time vs Current (A)
6.3: Time vs Power (KW)
6.4: Time vs SOC (%)
Scenario 3: Low PV Capacity House
Step 1: Initially, we will construct a model with a grid, low-capacity rooftop PV house integrated with shared CBESS .
Step 2: Then, we implement an Adaptive Intelligent Fuzzy Logic Controller (AIFLC) and NSGA-11 algorithms for intelligent power flow management .
Step 3: Next, we simulate the model and collect the simulated voltage,current,power and SOC data.
Step 4: Next, we implement multi-objective optimization to detect optimal energy scheduling, battery coordination, and excess solar energy sharing based on collected data.
Step 5: Next, we analyze residential load conditions , energy trading and grid power consumption data.
Step 6: Finally, we plot performance metrics for the following:
6.1: Time vs Voltage (V)
6.2: Time vs Current (A)
6.3: Time vs Power (KW)
6.4: Time vs SOC (%)
1. Development Tool: MATLAB R2024a/Simulink or above
2. Operating System: Windows-10 (64-bit) or above
Note:
1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance. Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
2) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
3) If the plan satisfies your requirement, Please confirm with us.
4) Project based on Simulation only.
