Developing countries often witness a steady increase in maximum demand within their power systems. To maintain the reliability of the power supply, utility operators must regularly plan and upgrade both existing power stations and transmission networks to ensure reliable electricity delivery to consumers. Substantial investments are necessary from the utility companies that will ultimately be passed on to consumers through increased electricity tariffs. Thus, the objective of this research work is to develop a methodology to model the distribution of Energy Storage Systems (ESS) across an electrical network such that network-based modelling of ESS can be carried out to assess the financial and environmental benefits of maximum demand reductions by ESS. Such benefits are due to the reduced power generation costs and deferments of network upgrades and new peaking power plants. Several case studies are carried out by using the methodology based on the IEEE 24-bus transmission network with distributed ESS to perform maximum demand reductions. Results show that the optimum capacity of ESS is found to be 3700 MWh which brings the highest net financial saving of USD 402.54 million (RM 1900 million). In addition, 2679.1 ktons of carbon dioxide (CO2) emission is avoided with the reduction in maximum demands.