Abstract
Electricity cost is one of main production costs for flow shops. Providing frequency regulation services can help electric loads reduce their electricity costs. Previous studies mostly focus on automatic generation control (AGC) strategies for other types of electric loads, such as air conditioners, EVs or battery storage. In this paper, we find flow shops competent to follow regulation signals and avoid interrupts of processing with the help of scheduling optimization. This finding may be an aid for flow shops by availing regulation services to the market and making a profit. Hence, we propose an AGC strategy for optimizing flow shop scheduling, without affecting the operation. To formulate the bidding strategy for flow shops in regulation market, we considered as many relevant factors as possible, including the regulation performance and yield of flow shops, constraints on load power, regulation reserve capacity and machines operation, inventory of each semi-finished product, AGC strategy—as well as the coupling between the bids in both energy market and regulation market. Our case study shows the potential of the methodology proposed in this paper to cut down the electric cost of flow shops and supplies of performance-qualified frequency regulation service.
Highlights
Reducing the energy cost of production is significant for the flow shops with a lot of energy consumption
One was the cost of electricity purchased in the day-ahead energy market, as expressed in the first term of Formula (1); the other is the revenue of reg regulation, as expressed in the second term of formula (1). λda and λh denote day-ahead market clearing price (DAMCP) ($/MWh) and h
With the help of flow shop scheduling optimization for automatic generation control (AGC), flow shops can provide frequency regulation ancillary service to power system, with a service performance qualified in Pennsylvania-New Jersey-Maryland (PJM)
Summary
Reducing the energy cost of production is significant for the flow shops with a lot of energy consumption. Flow shop scheduling optimization can help factories save energy consumption [2]. Flow shop scheduling plays an important role in reducing the electricity cost by optimizing power use at different periods [3] and providing demand response service [4]. Help realize a more flexible scheduling and industrial process control of flow shops. Big data, machine learning and cloud storage favor manufacturers to evaluate some complex and vague factors, like carbon emission and product performance. Most of these technologies are not yet universal [6]. For manufacturing industry in particular, those Industry 4.0 technologies can be instrumental for the operation of power system by some new models of energy management [10]
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