Modeling and Simulink of Energy Trading in Residential Microgrid
Implementation Plan:
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Step 1: Initially, we construct a microgrid with solar, wind, battery, EV, and grid connections .
Step 2: Next, we simulate and collect the simulated microgrid data and assign consumers and prosumers based on collected data.
Step 3: Next, we preprocess and organize the collected data to generate short-term forecasts for load demand and renewable energy availability suitable.
Step 4: Next, we design a dynamic P2P pricing mechanism using the forecasted data to determine fair buying and selling prices for prosumers and consumers based on collected data.
Step 5: Next, we optimize the pricing decisions and maximize economic benefits based on collected data.
Step 6: Next, we analyze all energy trading transactions and financial settlements through a blockchain-based third-party regulatory oversight mechanism to ensure security.
Step 7: Finally, we evaluate system performance using economic metrics, including:
7.1: Electricity cost before vs. after P2P trading
7.2: Prosumer Index vs. Revenue Gain (ZAR)
7.3: Consumer Index vs. Cost Savings (ZAR)
7.4: Trading Iteration Index vs. Economic Efficiency (%)
Software Requirements:
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1. Development Tool: Matlab-R2023a/Simulink or above with python
2. Operating System: Windows-10 (64-bit) or above
Note:
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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.
