Energy management strategy for industries integrating small scale waste-to-energy and energy storage system under variable electricity pricing

• The concept of in-house WtE accompanied by storage system is proposed.
• WtE converts waste in to energy during off-peak period and this is stored to supply in peak period.
• Fuzzy inference system based energy management strategy is proposed.
• Lower consumption from grid during peak period reduces total electric bill.
• Cost analysis for testing the validity of proposed model is presented.

Energy is a basic need for different purposes in an industry and it incurs the highest cost in any production system. In order to reduce the energy cost, achieving energy efficiency with renewable fuel has no alternative. However, when the industry operates under variable electricity pricing, only energy efficiency cannot help cost saving. An energy management strategy for energy usage is also required. Waste-to-energy (WtE) can be an attractive solution for renewable energy source. Current research on small scale WtE paves the way of using WtE for energy efficiency into industries. The objective of this work is to propose a strategy to reduce the electricity bill for the industry under variable electricity pricing. In order to reduce the electricity bill, a fuzzy Inference System (FIS) based energy management strategy to produce electricity in low pricing period and utilize it in peak period is proposed by integrating small scale WtE and storage into industry system. Though this model is built for energy management, it indirectly works as a tool for waste management as well. The performance of the proposed model is tested with the data collected from a plastic container manufacturing industry. The cost analysis is shown to justify the higher establishment cost of WtE.

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