Distributed Energy Control Using Storage and Real-Time Price Signals
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Solution Overview
Problem
The smart grid electrical network faces challenges in managing demand and supply efficiently due to high time-varying demand, leading to increased costs and volatility, especially with the integration of renewable energy sources, which causes market uncertainty and risks for retailers and end-users.
Innovation Solution
A method and system for controlling the transfer of electrical power between two networks, where the second network can generate electricity on-site using stored energy, such as combustible gas, and adjust power transfer in real-time based on pricing information and demand characteristics, allowing for the storage or supply of electricity to minimize costs and stabilize the grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If grid generated supply is used to meet instantaneous demand, then electrical power can be supplied reliably, but cost volatility and market uncertainty increase for end-users
Solution Approach 1:
The system performs preliminary actions by storing energy in advance during periods of low demand and low prices. The controller predicts future pricing and demand characteristics, then proactively charges energy storage devices before peak demand periods occur, allowing the end-user to avoid high prices without compromising supply reliability.
Solution Approach 2:
The energy storage device acts as an intermediary between the electrical network and the end-user load. It buffers the price volatility by decoupling the timing of energy purchase from energy consumption, absorbing price fluctuations and providing stable, predictable costs to the end-user while maintaining continuous power supply.
2Object-affected harmful factors
If on-site electricity generation using stored energy is implemented, then exposure to price volatility is reduced, but device complexity and infrastructure requirements increase
Solution Approach 1:
The system enables self-service by allowing the end-user to generate their own electricity using stored energy (combustible gas) when it is economically advantageous. The controller automatically manages the generation process, fuel storage, and grid interaction, making the complex functionality accessible through simple user interfaces while reducing dependence on external infrastructure.
Solution Approach 2:
The system is highly dynamic, with the controller continuously adjusting power transfer decisions based on real-time and predicted pricing information, demand characteristics, and energy storage status. This dynamic optimization allows the system to adapt to changing market conditions and automatically select the most economical power source at any given moment.
3Productivity
If real-time power transfer adjustments are made based on pricing information, then energy usage is optimized and costs are minimized, but system complexity and control requirements increase
Solution Approach 1:
The system implements comprehensive feedback mechanisms where the controller continuously monitors pricing information from the electrical network, demand characteristics at the end-user site, and the status of energy storage devices. This feedback loop enables automatic optimization of power transfer decisions, adjusting energy procurement and consumption strategies in real-time to minimize costs while maximizing efficiency.
4Adaptability or versatility
If large scale storage and buffering of electricity is implemented, then demand and supply can be decoupled, but economic feasibility is compromised
Solution Approach 1:
The system segments the energy storage function into distributed, modular units located at individual end-user premises rather than requiring large centralized storage facilities. Each end-user has their own energy storage device(s) sized appropriately for their specific needs, making the solution economically feasible while still achieving demand-supply decoupling at the distributed level.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the exposure of end-users to price volatility, optimizes energy usage, and enhances the efficiency of the electrical power supply network by allowing real-time adjustments in power transfer, thereby minimizing costs and stabilizing the market.
Implementation Method 1
electrical generating capacity at the location based on stored energy accessible at the location
Data Source
AI summary
A method and system of controlling the time dependent transfer of electrical power between a first electrical network and a second electrical network is disclosed. The first electrical network is operable to provide instantaneous electrical power to the second electrical network located at a location, the second electrical network includes electrical generating capacity at the location based on stored energy accessible at the location. The method and system involves receiving at the second electrical network pricing information from the first electrical network, the pricing information associated with the future supply of electrical power by the first electrical network to the second electrical network and then modifying substantially in real time the transfer of electrical power between the first and second electrical networks in accordance with the pricing information and the electricity demand characteristics of the location.