Power Plant Network Simulation for Renewable Power Flow Balancing
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Solution Overview
Problem
Renewable energy power plants face challenges in optimizing power flow due to variations in renewable energy source output and demand, requiring a solution to efficiently manage energy distribution between multiple power plants and loads while minimizing waste and transmission losses.
Innovation Solution
A data structure and simulation model that uses a graph database to model power flows between renewable energy sources, energy storage systems, and power grids, allowing for the determination of optimal energy distribution and equipment management across a network of power plants to maximize efficiency and income.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If renewable energy sources are used to supply electricity, then environmental sustainability is improved, but power output stability deteriorates due to weather and time variations
Solution Approach 1:
The system performs preliminary actions by storing energy in advance when renewable energy production is high. The energy storage system accumulates excess energy during periods of high wind or solar output, preparing it for later use when production is low, thus stabilizing power supply without compromising environmental benefits
Solution Approach 2:
The energy storage system acts as an intermediary between renewable energy sources and the electrical grid. It buffers the variability of renewable generation, absorbing excess energy when production exceeds demand and releasing energy when production is insufficient, thereby decoupling the instability of renewable sources from the grid
2Reliability
If energy is stored in the ESS, then power supply reliability is improved, but energy loss increases due to storage and retrieval inefficiency
Solution Approach 1:
The system applies partial action by storing only the excess energy that is not immediately needed, rather than storing all generated energy. This approach ensures that energy is stored only when it would otherwise be wasted, minimizing the impact of storage losses while still improving reliability
Solution Approach 2:
The system dynamically changes operational parameters based on real-time conditions. It adjusts the state of charge, charge/discharge rates, and priority of energy sources according to weather forecasts, grid demand, and economic factors, optimizing the balance between reliability and energy loss minimization
3Quantity of substance
If multiple power plants are operated to meet varying demand, then power supply adequacy is improved, but system complexity increases
Solution Approach 1:
The energy storage system serves multiple functions simultaneously: it stores energy, provides frequency regulation, enables load shifting, and facilitates renewable energy integration. This multi-functionality allows a single system to address multiple power supply needs without requiring separate dedicated systems for each function
Solution Approach 2:
The system implements comprehensive feedback mechanisms that continuously monitor weather conditions, energy production, storage state, grid demand, and economic factors. This real-time feedback enables automated optimization of power flow across multiple plants, reducing the complexity of manual network management while ensuring adequate power supply
Data Source
AI summary
A system for optimizing a network of power plants includes at least one memory storing a network model of a network of power plants including a power plant model for each power plant, each power plant model including one or more equipment models of power plant equipment of a power plant, and plant relationships between the power plant models. The system further includes at least one processor configured to modify an attribute of a first equipment model included in a first power plant model of a first power plant, identify at least one plant relationship between the first power plant model and a second power plant model of a second power plant, determine an expected change in operation of the second power plant based on the modified attribute and the at least one plant relationship, and generate a record including an indication of the expected change.