Power Plant Load Scheduling for Multi-Output Energy Demand
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Solution Overview
Problem
Thermal steam power plants face challenges in optimizing the combined output of electricity, steam, and heat due to limited operational degrees of freedom, which are mainly focused on primary energy use, wear, and contamination, making it difficult to efficiently manage energy distribution, especially with volatile energy sources and varying demand.
Innovation Solution
A method for controlling a power plant that involves measuring and monitoring physical variables, creating forecasts based on energy requirements, and optimizing operation using an algorithm to adjust the output of district heating, superheated steam, and electrical power, taking into account various operating modes and technical boundaries, to achieve the best possible fulfillment of load requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the power plant operates with fixed degrees of freedom focused on primary energy use and wear optimization, then the reliability and equipment life are improved, but the adaptability to varying energy demands and product output optimization deteriorate
Solution Approach 1:
The patent implements dynamic optimization by continuously adjusting operating parameters (steam extraction rates, turbine valve positions, generator output) based on real-time demand signals and forecasted energy requirements. The system transitions from static fixed-point operation to dynamic multi-variable control, allowing the power plant to adapt its degrees of freedom according to varying district heating, hot water, and electricity demands while maintaining equipment reliability through controlled adjustment ranges.
Solution Approach 2:
The optimization system changes multiple operating parameters simultaneously (steam pressure, temperature, flow rates, extraction points) to achieve optimal product output ratios. By coordinating changes in these parameters according to forecasted demand and current plant state, the system can shift between different operating modes (base load, peak load, maintenance modes) while preserving equipment reliability through predefined parameter boundaries.
2Quantity of substance
If energy is extracted from the power plant process for district heating, then the heat supply capability is improved, but the electricity generation capability deteriorates
Solution Approach 1:
The system dynamically balances steam extraction for heating against electricity generation by continuously adjusting the extraction rate based on real-time demand signals. When district heating demand increases, the optimizer increases steam extraction from the turbine; when electricity demand dominates, it reduces extraction. This dynamic balancing allows the plant to respond to varying demand patterns without fixed trade-offs.
Solution Approach 2:
The optimization system uses forecasted energy requirements to anticipate periodic demand patterns (daily, weekly, seasonal variations in heating and electricity demand). By pre-calculating optimal operating schedules based on these forecasts, the system proactively adjusts steam extraction timing and magnitude to minimize the negative impact on electricity generation while meeting anticipated heating demands.
3Productivity
If the power plant optimizes for electrical power output, then the electricity production efficiency is improved, but the combined output optimization of heat and cold deteriorates
Solution Approach 1:
The optimization system treats the power plant as a multi-functional system that simultaneously produces electricity, district heating, hot water, and cooling. The unified optimizer coordinates all product outputs according to their respective market prices, demand signals, and plant capabilities, allowing the same thermal energy to be allocated to different products based on current economic and operational conditions. This universal optimization approach enables the plant to function as a flexible energy hub rather than a single-purpose generator.
Solution Approach 2:
The system changes operating parameters (steam extraction points, reheat temperatures, condenser pressures) to optimize the combined output mix. By adjusting these parameters in response to forecasted demand and current product prices, the optimizer can shift the product portfolio between electricity, heat, and cooling to maximize overall effectiveness while maintaining high productivity through efficient parameter coordination.
4Adaptability or versatility
If the power plant operates between full load and partial load frequently, then the adaptability to demand changes is improved, but the wear and contamination increase
Solution Approach 1:
The system uses forecasted energy requirements to predict future demand patterns and proactively schedules load changes and operating mode transitions. By anticipating demand peaks and valleys in advance, the optimizer can plan load adjustments that meet demand requirements while minimizing the frequency and magnitude of transitions, thereby reducing wear and contamination from frequent partial-load operation.
Solution Approach 2:
The optimization system incorporates constraints and weighting factors that cushion against excessive wear by limiting the rate of load changes and the time spent in high-wear partial-load operating modes. These pre-defined protective measures are built into the optimization algorithm to balance demand responsiveness with equipment protection, smoothing out unnecessary fluctuations while maintaining adaptability to genuine demand changes.
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 method allows for demand-oriented optimization of energy production, optimizing the power plant's operation to meet varying energy demands while minimizing energy waste and maximizing revenue, by adjusting the ratio of products and operating modes based on forecasts and technical constraints.
Implementation Method 1
at least one system for the thermal conversion of primary energy and at least one water-steam cycle with at least one turbine and at least one generator
Implementation Method 2
at least one water-steam cycle with at least one turbine and at least one generator
Implementation Method 3
at least one water-steam cycle with at least one turbine and at least one generator
Data Source
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AI summary
The invention relates to a method for the closed loop-control of a power plant for producing and providing energy in the form of different products, which are selected from a group comprising district heat, district cooling, hot steam, hot water, and electric power, wherein the method comprises measuring and monitoring physical variables of the power plant and the surroundings, recording the measured physical variables by using a device for electronic data processing, creating a forecast of a time-variant anticipated maximum and/or minimum generated power from the power plant whilst taking into account different possible operating modes for a predefined forecast period and whilst taking into account the continuously monitored and/or recorded variables, creating a forecast for the energy demand anticipated to be provided in a forecast period depending on the magnitude and type of the product to be provided, creating a schedule as a control setpoint for the operation of the power plant between full load and part load and/or between different operating modes of the power plant within the forecast period, and controlling the operation of the power plant in accordance with the control setpoint from the schedule.