journal article·2022-07-27Open access

Model for Integrating the Electricity Cost Consumption and Power Demand into Aggregate Production Planning

Camila Matos, Antônio Vanderley Herrero Sola, Gustavo de Souza Matias, Fernando Henrique Lermen, José Luis Duarte Ribeiro, Hugo Valadares Siqueira

Applied Sciences· Volume 12· Issue 15

Abstract

The constant increases in electricity tax costs and the mandatory contracting of power demand in advance by companies connected to the high-voltage electrical system drive organizations to improve energy planning in their production processes. In addition, market uncertainties make only stochastic methods insufficient for forecasting future production demand. To fill this gap, this study proposes a model that integrates the cost with electricity consumption and power demand into the aggregate production planning, considering the market uncertainties. The model was empirically applied in the food industry, considering a family of potato chips products. From the collected data, a demand forecast was carried out for a later realization of the aggregate planning, using the Holt–Winters forecast model. Before modeling, the new energy demand was calculated, and finally, the model solution verification was performed. In the case study, after application, it was possible to reduce two workers and a cost reduction of R$ 14,288.00. Moreover, the proposal managed to define a power demand that minimized the costs of electric energy and the total costs of the aggregate production planning.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Energy Efficiency and Management · Sustainable Supply Chain Management · Supply Chain and Inventory Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Graduate Program in Industrial Engineering, Universidade Tecnológica Federal do Paraná, Street Doutor Washington Subtil Chueire 330, Ponta Grossa 84017-220, Brazil

Industrial Engineering Department, Universidade Estadual do Paraná, Street Comendador Correia Júnior, 117, Paranaguá 83203-560, Brazil

Chemical Engineering Graduate Program, Chemical Engineering Department, Universidade Estadual de Maringá, Avenue Colombo 5790, Maringá 87020-900, Brazil

Industrial Engineering Department, Universidad Tecnológica del Perú, Avenue Arequipa 265, Lima 15046, Peru

Industrial Engineering Department, Federal University of Rio Grande do Sul, Avenue Osvaldo Aranha, 99, Porto Alegre 90035-190, Brazil

Funding

CAPES Foundation · Universidad Tecnológica de Peru

References (50)

Show source-provided references
1. A production planning in highly automated manufacturing system considering multiple process plans with different energy requirements10.1007/s00170-013-5306-1 ↗
2. A New Energy-Aware Flexible Job Shop Scheduling Method Using Modified Biogeography-Based Optimization
3. Determinant factors in site selection for photovoltaic projects: A systematic review10.1002/er.4321 ↗
4. Lu, Y., Khan, Z.A., Alvarez-Alvarado, M.S., Zhang, Y., Huang, Z., and Imran, M. (2020). A critical review of sustainable energy policies for the promotion of renewable energy sources. Sustainability, 12.10.3390/su12125078 ↗
5. Value chain in distributed generation of photovoltaic energy and factors for competitiveness: A systematic review10.1016/j.solener.2020.09.040 ↗
6. Photovoltaic solar energy: Conceptual framework10.1016/j.rser.2017.02.081 ↗
7. Future scenarios and trends in energy generation in Brazil: Supply and demand and mitigation forecasts10.1016/j.jclepro.2014.09.082 ↗
8. Forecasting energy consumption of long-distance oil products pipeline based on improved fruit fly optimization algorithm and support vector regression10.1016/j.energy.2021.120153 ↗
9. Predicting energy consumption of multiproduct pipeline using artificial neural networks10.1016/j.energy.2014.01.062 ↗
10. Imaging time-series with features to enable visual recognition of regional energy consumption by bio-inspired optimization of deep learning10.1016/j.energy.2021.120100 ↗
11. Modelling industry energy demand using multiple linear regression analysis based on consumed quantity of goods10.1016/j.energy.2021.120270 ↗
12. Energy trade market effect on production scheduling: An Industrial Product-Service System (IPSS) approach10.1080/0951192X.2020.1858505 ↗
13. Nugraha, I., Hisjam, M., and Sutopo, W. (2020). Aggregate Planning Method as Production Quantity Planning and Control to Minimizing Cost. IOP Conference Series: Materials Science and Engineering, IOP Publishing.10.1088/1757-899X/943/1/012045 ↗
14. A light robust model for aggregate production planning with consideration of environmental impacts of machines
15. Application of fuzzy multiobjective linear programming to aggregate production planning10.1016/j.cie.2003.09.009 ↗
16. ANEEL—Agência Nacional de Energia Elétrica (2019, May 29). Resolução Normativa nº 414, de 9 de Setembro de 2010. Estabelece as Condições Gerais de Fornecimento de Energia Elétrica de Forma Atualizada e Consolidada, Available online: http://www.aneel.gov.br/ren-414.
17. An overview of production planning model: Structure classification and empirical assessment10.1080/00207548208947752 ↗
18. An improved production planning method for process industries10.1080/00207543.2010.547528 ↗
19. Arruda, O.R. (2014). Planejamento Tático da Produção Agroindustrial com Fluxo Divergente e Produção em Dois Estágios. [Master’s Thesis, Departamento de Engenharia de Produção, Escola Politécnica da Universidade de São Paulo].
20. A bi-objective aggregate production planning problem with learning effect and machine deterioration: Modeling and solution10.1016/j.cor.2017.11.001 ↗
21. Aggregate production planning by focusing on energy saving: A robust optimization approach10.1016/j.jclepro.2016.05.133 ↗
22. Models for Production Planning under Power Interruptions Naval
23. A holistic production planning approach in a reconfigurable manufacturing system with energy consumption and environmental effects10.1080/0951192X.2014.902106 ↗
24. How Should Additive Holt-Winters Estimates Be orrected?10.1016/S0169-2070(98)00040-5 ↗
25. Nahmias, S. (1995). Production and Operations Analysis, Irwin.
26. R Core Team (2021). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https://www.R-project.org/.
27. Distribution of the Estimates for Autoregressive Time Series with a Unit Root
28. Shapiro–Wilk test for skew normal distributions based on data transformations10.1080/00949655.2019.1658763 ↗
29. Energy efficiency index as an indicator for measuring building energy performance: A review10.1016/j.rser.2014.12.018 ↗
30. Godinho Filho, M.F. (2004). Paradigmas Estratégicos de Gestão da Manufatura. [Ph.D. Thesis, Universidade Federal de São Carlos (UFSC)].
31. Minimizing energy consumption via multiple installations aggregate production planning Clean Technologies and Environmental
32. Simulation techniques for the sensitivity analysis of multi-criteria decision models10.1016/S0377-2217(96)00307-4 ↗
33. Bazaraa, M.S., Jarvis, J.J., and Sherali, H.D. (2010). Linear Programming and Network Flows, Wiley. [4th ed.].10.1002/9780471703778 ↗
34. Workload control concepts in job shops: A critical assessment10.1016/S0925-5273(96)00088-6 ↗
35. A capacity-driven approach to establish reliable due dats in a MTO environment10.1016/j.ijpe.2005.03.003 ↗
36. Filho, F.H.B. (2019, January 15). A crise econômica de 2014/2017. Estudos avanChatuçados. vol.31 no.89 São Paulo Jan./Apr. Available online: https://doi.org/10.1590/s0103-40142017.31890006.10.1590/s0103-40142017.31890006 ↗
37. Consistent nonparametric regression, with discussion10.1214/aos/1176343886 ↗
38. STL: A seasonal-trend decomposition procedure based on LOESS
39. Smooth regression analysis
40. Optimal rates of convergence for nonparametric estimators10.1214/aos/1176345206 ↗
41. A multiobjective model for multi-product multi-site aggregate Production planning In a green supply chain: Considering collection and recycling centers10.1016/j.jmsy.2016.06.004 ↗
42. Aggregate Production Planning: Modeling and Solution via Excel Spreadsheet and Solver
43. Energy production planning of a network of micro combined heat and power generators10.1016/j.apenergy.2012.09.015 ↗
44. Multistage Production Planning in the Dairy Industry: A Mixed-Integer Programming Approach10.1021/acs.iecr.5b02247 ↗
45. Aggregate production planning for process industries under oligopolistic competition10.1016/j.ejor.2012.07.007 ↗
46. Optimal Production Planning in a Petrochemical Industry using Multiple Levels10.1016/j.cie.2016.08.008 ↗
47. Stevenson, W.J. (2001). Administração de Operações de Produção, LTC. [6th ed.].
48. Operational methods for minimization of energy consumption of manufacturing equipment10.1080/00207540701450013 ↗
49. Energy-oriented scheduling based on Evolutionary Algorithms10.1016/j.cor.2014.05.002 ↗
50. A random-key encoded harmony search approach for energy-efficient production scheduling with shared resources10.1080/0305215X.2014.971778 ↗