article · Applied Energy
Industrial demand-side energy management is becoming vital as power grids face fluctuating demand and an increasing share of intermittent renewable generation. An optimization model based on mixed integer linear programming was developed to assess electrical energy demand flexibility within the cement production sector. Applying this model to case study cement plants showed a demand flexibility potential of approximately 495 megawatt-hours per day, representing about 28 percent of their total daily electrical energy consumption. By shifting demand away from peak hours to off-peak periods, the plants decreased their peak loads by an average of 75 percent. This operational adjustment lowered daily electricity costs by an average of 14 percent and cut daily carbon dioxide emissions by 188 tonnes across the facilities. Operational scenarios involving waste heat recovery power plants and capacity factor adjustments further supported these demand response strategies.
Balancing electricity grids is increasingly difficult as intermittent renewable sources expand. By proving that energy-intensive cement manufacturing can shift over a quarter of its daily power use away from peak hours, this research highlights an effective pathway to stabilize power grids, lower industrial operational expenditure, and significantly decrease industrial carbon emissions without requiring new electricity supply infrastructure.
The research provides an operational optimization model for energy-intensive manufacturing plants and industrial energy managers seeking to implement demand-side flexibility strategies. The work represents an applied and tested model demonstrated on operational cement plants. It can inform automated load-scheduling software, grid balancing services, and the design of dynamic industrial electricity tariffs by policymakers and grid operators.
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Energy availability and reliability are essential for economic growth and sustainable development. The problems with growing energy demand could be addressed by supply-side energy management. However, this task has become increasingly challenging due to high fluctuations in electricity demand and the increasing penetration of intermittent renewable energy into the electricity supply mix. This study aims to investigate the energy demand flexibility potential in the energy-intensive cement production sector. A mixed integer linear programming model (MILP) has been developed to flatten the grid's hourly demand curve by minimizing the industrial customer's hourly peak loads and maximizing the shifting of demand to off-peak periods. The result reveals that the demand flexibility potential of the case study cement plants is about 495 MWh per day, constituting approximately 28 % of the daily total electrical energy used by these cement plants, proving that the cement industry is a potential candidate for demand response strategies. By adapting the proposed model, the loads of the case study plants during the peak period of the day are reduced by an average of 75 %. In addition, case study plants have achieved an overall reduction of 188 t of CO 2 emissions per day. Furthermore, the cost of consumed electrical energy for a day decreased on average by 14 % in these plants. Thus, the proposed model can help minimize the impact on grid instability and the cost of energy consumption of an industrial customer. Scenarios such as the variation of the capacity factor and onsite electrical power generation, i.e., waste heat recovery power plants, can promote the demand response strategies in the cement sub-sector. The study could be useful to energy-intensive industries and relevant policymakers to understand the demand response in maintaining power system reliability and explore ways to implement demand-side energy management strategies with appropriate electricity tariffs. • Assessed the DR-potential in an energy-intensive industry • Investigated the technical flexibility potential of demand response in the cement industry. • Developed an energy consumption optimization model suitable for energy intensive industries. • Evaluated optimal operational demand response strategies in the cement industry. • The peak demand and its CO 2 emissions of the grid is reduced by the proposed model.
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DOI: 10.1016/j.apenergy.2024.124608
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