Multi-Energy Hub Scheduling Under Market Price Risk
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Solution Overview
Problem
Conventional methods for optimizing energy generation in multi-energy hubs fail to effectively manage optimal energy flows and integrate operational complexities, particularly in managing risks associated with market price variability and energy storage.
Innovation Solution
A method and system that compute an optimal energy generation schedule by predicting market prices, calculating expected revenues and costs, and managing risks through a portfolio optimization technique, considering energy conversion, storage, and market price uncertainties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional Mean-Variance Portfolio methods are used to optimize energy generation, then portfolio allocation can be determined, but risk assessment and management considering uncertainties are not covered
Solution Approach 1:
The patent combines Mean-Variance Portfolio optimization with energy hub operations, merging financial portfolio theory with energy system management to simultaneously optimize energy generation schedules and assess market price risks across multiple energy carriers
Solution Approach 2:
The energy hub model serves multiple functions: it optimizes generation scheduling, manages storage operations, performs conversion between energy carriers, and conducts comprehensive risk assessment, making the system universally applicable to various energy optimization scenarios
2Adaptability or versatility
If multiple energy types are integrated in multi-carrier energy systems, then energy supply efficiency and flexibility are improved, but operational integration and managing optimal energy flows become more complex
Solution Approach 1:
The patent segments the energy hub into distinct functional modules for different energy carriers (electricity, heat, hydrogen, natural gas), allowing independent optimization of each carrier while maintaining overall system coordination through unified scheduling
Solution Approach 2:
The energy hub acts as an intermediary that coordinates and integrates multiple energy carriers, managing conversion processes and optimizing flows between different energy types through centralized scheduling and control mechanisms
3Loss of energy
If energy storage systems are utilized to manage demand and surplus, then energy arbitrage opportunities are captured, but system complexity and storage management challenges increase
Solution Approach 1:
The system performs preliminary actions by forecasting energy prices and demand patterns in advance, allowing the energy hub to pre-schedule storage charging and discharging operations to capture arbitrage opportunities before market conditions change
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor storage state-of-charge, market prices, and demand patterns, using this information to dynamically adjust storage operations and optimize arbitrage strategies in real-time
Data Source
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AI summary
Power systems mainly focuses on uncertainties such as load variations, renewable energy sources, electricity price variability etc., but a gap exists in formulating and solving Portfolio Optimization (PO) problem considering inter multi-energy market price vulnerabilities. The present disclosure receives an energy volume generated by a plurality of energy generation systems. Further, a current market price value is predicted and an expected revenue for each of the plurality of energy generation systems is computed. Simultaneously, an energy generation cost, an energy conversion cost is computed, and an energy storage cost are computed. Further, a market price variation risk associated with each of the plurality of multi-energy day-ahead markets is computed. Further, a market price risk forecast is computed. Finally, an optimal energy generation schedule is computed for each of the plurality of energy generation systems in a plurality of time window associated with a day using a portfolio optimization technique.