Distribution System Optimization with Integrated Volt-VAR Control
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Solution Overview
Problem
The integration of Distributed Energy Resources (DERs) into electric power distribution systems poses challenges such as energy losses, voltage regulation, and feeder capacity issues, necessitating advanced control systems to optimize asset utilization and minimize impacts on existing infrastructure.
Innovation Solution
A system comprising a power forecasting module, demand response module, energy storage commitment module, unit commitment module, economic dispatch module, and Integrated Volt-VAR Control (IVVC) module, which forecasts load and power generation, dispatches demand response, schedules energy storage, and controls distribution assets to maintain voltage profiles and optimize DER operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If DERs are integrated into the distribution system to provide clean electric power closer to end-users, then transmission losses are reduced and power quality is improved, but feeder capacity is impacted and voltage regulation becomes more difficult
Solution Approach 1:
The distribution system is segmented into multiple feeders with distributed DERs, allowing localized power generation and reducing transmission losses. Each feeder operates semi-independently with its own control mechanisms, enabling granular management of DER integration while maintaining overall system efficiency.
Solution Approach 2:
The system performs load forecasting and DER generation forecasting in advance to proactively schedule demand response and energy storage operations. This preliminary action allows the system to prepare for anticipated fluctuations in power supply and demand, preventing voltage regulation issues and feeder capacity problems before they occur.
2Productivity
If multiple DERs are coordinated with distribution assets to maximize asset utilization, then system efficiency is improved, but control system complexity increases
Solution Approach 1:
The control system integrates multiple functions into a unified platform that simultaneously performs load forecasting, DER generation forecasting, demand response scheduling, energy storage management, and voltage regulation. This multi-functional approach maximizes asset utilization across all distribution assets while avoiding the complexity of multiple separate control systems.
Solution Approach 2:
The system continuously monitors actual load and DER generation against forecasts, and uses this feedback to adjust demand response dispatch and energy storage scheduling in real-time. This closed-loop control optimizes asset utilization dynamically while maintaining manageable system complexity through automated adjustments rather than manual intervention.
3Productivity
If demand response is dispatched to modify load forecast, then peak loads are reduced and energy efficiency is improved, but load control complexity increases
Solution Approach 1:
The system forecasts load and DER generation in advance, then pre-schedules demand response actions and energy storage discharge/charge operations to address anticipated peak loads. This preliminary scheduling reduces peak demand and improves energy efficiency while avoiding the need for complex real-time load control by preparing responses beforehand.
4Reliability
If energy storage devices are scheduled for charging and discharging, then peak load reduction is achieved and system reliability is improved, but operational complexity increases
Solution Approach 1:
The system determines energy storage charging and discharging schedules in advance based on load forecasts and DER generation forecasts. This preliminary scheduling ensures system reliability by preparing energy storage to discharge during anticipated peak loads or DER outages, while keeping operational complexity manageable through automated pre-planning rather than complex real-time decisions.
Data Source
AI summary
A power forecasting module determines a load forecast of a distribution system (DS) and a power generation forecast of distributed energy resources (DERs) A demand response (DR) module estimates an available DR based on the load and the power generation forecast and modifies the load forecast by dispatching an optimal DR. An energy storage commitment module determines a charging/discharging schedule of energy storage devices in the system based on the modified load profile and generates a second load profile by incorporating the charging/discharging schedule of energy storage devices. An unit commitment (UC) module determines a DER schedule of supplying electrical power to the loads in the second load profile based on a first objective function. An economic dispatch (ED) module determines an optimum operating point for each DER and an Integrated Volt-VAR Control (IVVC) module controls distribution assets to maintain a voltage profile in the system.