Enhanced Procurement and Production Strategies for Chemical Plants: Utilizing Real-Time Financial Data and Advanced Algorithms

Abstract

This paper presents an implementation of an automated algorithm powered by market and physical data to improve procurement & production of a chemical plant with the goal of improving the overall economics on the entity. Herein, the algorithm is applied to two scenarios which serve as case studies: conversion of natural gas to methanol and crude palm oil to biodiesel. The programme anticipates opportunities to increase prot or avoid loss by analysing the futures market prices for both reagents and the products 1 while considering cost of storage and conversion derived from physical simulations of the chemical process. Analysis conducted on 11.06.2018 in the biodiesel scenario shows that up to 219.28 USD per tonne of biodiesel can be earned by buying contracts for delivery of crude palm oil in July 2018 and selling contracts for delivery of biodiesel in August 2018 which equates to a margin 11.6% higher than in case of the direct trade.Moreover, it is shown that losses of up to 11.3% can be avoided and therefore, it is shown that there is realistic scope for increasing the protability of a chemical plant by exploiting the opportunities across dierent commodity markets in an automated manner. Consequently, such a cyber system can be used to assist eco-industrial parks with supply-chain management, production planning as well as nancial risk governance and, in the end, help to establish a long-term strategy.This study is part of a holistic endeavour that applies cyber-physical systems to optimise eco-industrial parks so that energy use and emissions are minimised while economic output is maximised.

The impact of intelligent cyber-physical systems on the decarbonization of energy

“…Although the development of blockchain-enabled P2P energy trading and storage has not yet been widely applied, there are already multiple explorations in the literature: blockchain-enabled P2P electricity trading in the chemical industry has been successfully demonstrated where two electricity producers and one electricity consumer can trade with each other 22 . The possibility of combining such blockchain-enabled energy trading with an automatic price predictor for energy arbitrage is also reported 141 .…”