Power Transfer Control Using Real-Time Pricing and Demand Shifting
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Solution Overview
Problem
Smart grid electrical networks face challenges in managing peak demand events, leading to high network costs and poor utilization, and renewable energy generation is not efficiently utilized due to market failures and lack of timely price signals to end-users.
Innovation Solution
A method and system for controlling electrical power transfer between networks by receiving real-time pricing information, modifying demand characteristics, and using on-site generation and storage to shift demand, with a controller managing power flow and consumption based on forecasted pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time pricing information and demand modification are implemented, then network utilization is optimized and peak demand is reduced, but device complexity and system infrastructure requirements increase
Solution Approach 1:
The system implements a feedback mechanism where the second electrical network receives real-time pricing information from the first electrical network, analyzes this information, and modifies its demand characteristics accordingly. This closed-loop feedback enables dynamic demand response that optimizes network utilization by shifting load away from peak periods based on actual pricing signals.
Solution Approach 2:
The system performs preliminary actions by receiving and analyzing pricing information in advance, then proactively modifying demand characteristics before peak demand events occur. This predictive approach allows the second network to pre-shift load to off-peak periods, preventing peak demand rather than merely responding to it.
2Loss of energy
If on-site generation and storage are used to shift demand, then renewable energy utilization is enhanced, but initial investment and system complexity increase
Solution Approach 1:
The second electrical network implements self-service by incorporating on-site generation and storage capabilities that enable it to independently manage its demand characteristics. The system uses its own resources to shift load and utilize renewable energy locally, reducing dependence on the broader grid and improving renewable energy utilization through autonomous decision-making based on pricing signals.
3Reliability
If demand characteristics are modified based on pricing information, then peak demand is reduced and network efficiency improves, but control system complexity increases
Solution Approach 1:
The control system implements dynamics by continuously adapting demand characteristics in response to changing pricing information. Rather than using fixed demand management strategies, the system dynamically adjusts load modification actions based on real-time pricing signals, enabling flexible response to varying market conditions and improving overall network efficiency.
Data Source
AI summary
A method and system for controlling the transfer of electrical power between a first electrical network and a second electrical network is disclosed. The method includes receiving at the second electrical network pricing information from the first electrical network, the pricing information associated with the supply of electrical power between the first electrical network and the second electrical network and modifying a demand characteristic of the second electrical network based on the pricing information.