![]() Process impact of demand response - Cumulative results If the green line is above the blue line, the consumer is saving ![]() ![]() The Process impact of demand response where the cumulative and real-time results are displayed.įinancial impact of demand response - Cumulative resultsĭata from the simulation showing how much the consumer is saving or not.The Financial impact of demand response which includes the cumulative and daily results.The consumer is then interested in the results which are broken down into two sections: It is explicit because it is clear and direct without other assumptions. This means participating in the market directly as a consumer without involving the electricity supplier. In this experiment, a market-based explicit direct response strategy was chosen. Evaluate the current potential using a simulation experiment.Using simulation, the modeler can visualize the results showing the potential of the simulation software in the following ways: Agent-based modeling, where agent interactions influence information access, which in turn influences market strategy.Discrete-event simulation as timing is crucial for market strategy.Descriptive simulation approach in order to compare results of different operational conditions and help decision making in a multivariate program.With simulation it is possible to compare different scenarios: to vary parameters and see how the modeled system responds.ĪnyLogic simulation software was the best option to simulate this demand response effect because of the following advantages it brings to an analysis: ![]() This analysis of demand response using simulation focused on a single industrial consumer, which was a Danish company in the meat processing industry. This will ease the electricity consumption during peak hours. In this case it means increasing the temperature in the cooling room during the non-peak hours in the grid, and reducing the temperature in the cooling room during peak hours. If the consumer accepts flexible prices, they can choose to use more electricity. So, the temperature can be changed depending on the power grid’s needs in order to provide a stable service.įor the electricity supplier, the prices vary depending on the time of the day, for example, the early morning and evening are more expensive, while the consumer has fixed prices. In the system, there is a maximum and minimum temperature threshold within which the meat can be stored. The raw material, which in this case is meat cuttings, is received by the industrial consumer and needs to be stored in a cooled room before it is processed. It is also more data-driven, which means that AnyLogic simulation could be applied here effectively. Therefore, this focuses on process rescheduling instead of new technology investments. This refers to changes in the use of electricity by consumers during high periods in order to decrease demand on the power grid and ensure electricity reliability. However, there is another option – demand response. ![]() So, it requires new solutions such as batteries which can store energy, hydrogen, and even super connected grids linking countries. However, this balancing act is becoming more uncertain and unpredictable because of the emergence of renewables. This is a simple case of supply and demand. Whenever someone turns on a light switch, someone on the other side has to increase production. Thungela pedestrian and traffic simulation model for a new parking facilityĪ power grid is simply one big interconnected machine. ![]()
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