Modelling Escalator Power Consumption and Demand Response Potential

Abstract

The power system faces a major transformation due to the increased penetration of renewable energy sources. Uncertainties, as a result of the intermittent-nature of renewable power generation, require the power system to be proportionally flexible. Maintaining the balance between the supply and demand while providing enough stability in the grid has become a challenge that requires participation of the demand-side. Engagement of the consumer-side can be passive, through utilizing energy efficient technologies, and active, through a mechanism called demand response. This dissertation focuses on escalator potential in demand response and its energy efficiency. More specifically the thesis provides an angle and a framework for escalator technology to participate in the balancing of the power system grid by providing flexibility. Developed approaches can be used as a supportive tool in decision-making processes for various stakeholders, such as building designers, managers and investors. The description of how escalators can be utilized in demand response is separated into two main topics. First, the escalator power consumption measurements and modelling approaches are used to develop a simulation tool that allows modelling high-resolution power consumption profiles. The main modelling approach is based on simulating the impact of passenger traffic on the power consumption profiles. Long-term power consumption measurements indicate that passenger traffic is recurring which allows to simulate the power consumption of escalators throughout the year. The approach also allows to simulate large numbers of escalator units and the aggregate of power consumption. Second, the developed simulation tool is utilized to model the available flexibility for demand response. The selected approach to reducing the escalator power consumption is through speed reduction. One of the consequences of the method is that speed reduction causes delays to the passenger travel time and might increase the queuing time. The simulation results indicate that the proposed approach for power curtailment meets the technical requirements for participation in the incentive-based and price-based demand response programs specified by the energy markets. In the thesis, the flexibility modelling process progresses from simulation-based models to statistical models which focus on predicting the possible power curtailment of escalator units for frequency containment. As an example of utilizing the statistical approach, the thesis proposes a solution for selecting the best fitting escalators for a task that requires smaller than available target of power curtailment. The statistical model allows to greatly reduce the computation time, which allows frequent short-term predictions.