Virtual Power Plant Control via Scenario-Based Optimization
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Solution Overview
Problem
Current methods for controlling virtual energy generation and storage networks in hybrid energy systems fail to effectively account for uncertainties in renewable energy production and market price fluctuations, leading to suboptimal operation and load distribution.
Innovation Solution
A method that optimizes setting values for energy components over a predeterminable time horizon, integrating stochastic optimization and scenario tree analysis to manage energy exchange and trading across different markets, allowing for flexible time discretization and robust decision-making against uncertain energy developments and price forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed equidistant time discretizations are used for optimization, then the optimization process becomes simpler and more computationally efficient, but it cannot adequately capture uncertain energy production and market price fluctuations
Solution Approach 1:
The time horizon is segmented into multiple scenarios representing different possible future developments of renewable energy production and market prices. Each scenario captures a distinct pattern of uncertainty, allowing the optimization to consider multiple plausible futures simultaneously rather than relying on a single fixed discretization
Solution Approach 2:
The approach changes the temporal parameters from fixed equidistant discretization to scenario-based time structures where time points are defined by scenario developments. This allows the optimization to adapt to varying uncertainty patterns while maintaining computational tractability through the scenario tree framework
2Productivity
If agreements on energy amounts are made in advance within agreement periods, then market participation and load distribution are improved, but flexibility to adapt to uncertain future energy developments is reduced
Solution Approach 1:
The agreement structure is made dynamic by allowing different agreement periods and closing times for different scenarios. The optimization determines which agreements to make in advance and which to leave open for future decision-making, creating a flexible hierarchy of commitments that adapts to uncertainty
Solution Approach 2:
The method performs preliminary actions by making certain energy agreements in advance when uncertainty is lower or commitments are more certain, while deliberately leaving other decisions for later when more information becomes available. This selective advance planning balances market participation with adaptability
Data Source
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AI summary
The invention claims a method for controlling a virtual power generation and/or storage network (VPP) comprising a number of components (C1,...,C5) that are energetically coupled to one another by means of a plurality of buses and connected to one or more energy distribution systems, wherein the method comprises: - performing an optimization of setting values (SP) for the components over a predefinable time horizon (P), wherein the setting values comprise energy quantities that can be supplied by supplying components and/or received by receiving components depending on the states of the components, wherein an energy quantity is predetermined before the optimization is performed or is already determined by at least one supplying and at least one receiving component within an agreement period lying in the time horizon via at least one energy distribution system,if an agreement conclusion period for this agreement period has already expired, or is yet to be determined, if an agreement conclusion period for this agreement period lies in the future, - whereby the optimization takes into account an interaction between previously specified or already determined energy quantities and energy quantities yet to be determined, and - carrying out the control of the virtual energy generation and/or storage network based on the setting values, whereby the control effectes an exchange of energy quantities between the components as defined by agreement.