This study proposes a model based on mixed-integer linear programming (MILP) for the integrated expansion planning of generation and transmission systems with the implementation of distributed generation (DG). Most DG planning takes place after generation and transmission planning has been conducted. This model can be used to include DG potential simultaneously with generation and transmission expansion. DG is modelled as a negative load therefore DG is treated as a non-dispatchable unit of power generation. The objective of the model is to minimize overall cost including the investment cost of the generation units, DG units, and transmission lines, and the operating cost of the generation and DG units. The proposed model is staticdeterministic model in the form of MILP. The model was evaluated using the 6-bus Garver's test. To prove the effectiveness of the model, it was evaluated using the IEEE 46 Bus Test. The results show that due to the impact of DG on power system expansion planning ,the overall cost was reduced. The simulation results also show that a different optimal network configuration can be achieved by DG implementation in expansion planning.
State Finance Building of Yogyakarta is a community service that is included in the types of buildings that consume considerable electric energy so that often led to the power outage unexpectedly due to excessive use of electricity. This excessive use of electricity has also contributed to bill accounts for electricity from PLN, which each month up to hundreds of millions of dollars. To that end, this research was undertaken that aims to be able to a device that most optimal configuration in the use of solar panels and could compare the SOLAR PV system between On-Grid and PLN in the aspect of cost and CO2 emissions. In knowing the potential of alternative energy sources, namely solar power connected to the PLN as the optimal power plant is carried out employing researching the form of knowing the intensity of the solar radiation data, data in the form of electric power load is active for 24 hours, and data rates time of outside peak load and time of peak load from PLN for State Finance Building Of Yogyakarta. Later, she did the simulation using software to help homer modeling from the use of the most optimal solar panel. The research results obtained that the potential SOLAR PV system that is connected with the grid PLN unfit to be carried out because of the cost of the initial investment to expenses during the period of operation of the system, including the high value of the NPC of $970,742. However, the potential of the power plant that is appropriate for the conditions on-site research solar power plant was connected to the grid PLN power plant configuration that is optimized for without using batteries, use the only PV with a capacity of 91.35 kW, the converter with a capacity of 400 kW, and power grid network of PLN the system transmitted to SOLAR PV On-Grid of 552 kW.
The final energy demand and energy-related CO2 emission in industrial sector of Yogyakarta Province were analyzed in this study. The potential of energy saving and reduction of CO2 emission were estimated. The analysis was based on energy model. The model was constructed by LEAP model that describe the pattern of energy demand in industrial sector. Energy modeling and scenario analysis were used to simulate the impacts of various policies in energy demand and CO2 emission. Three scenarios were implemented in the model. Initially, the model was developed under business as usual (BAU) scenario that include current situation of energy-related activity in industrial sector. 2008 was selected as base year with projection period was terminated in 2025. Then, two alternative scenarios were developed that focus on energy efficiency improvement (EE scenario) and fuel switching to cleaner fuel (FS scenario). The two alternative scenarios were integrated into mitigation scenario. The result of alternative and mitigation scenario compare to BAU scenario in term of the final energy demand and energy-related CO2 emission. The result of the model showed the potential of energy saving by implementing mitigation scenario is 24.16% compare to BAU scenario. The expected reduction of CO2 emission under mitigation scenario is 20.22% compare to BAU scenario.
Greenhouse gas emissions produced by the energy sector, including the transportation sector, are a problem that must be resolved. One way to solve this problem is to provide energy in the transportation sector in a sustainable way, by using renewable energy. An integrated renewable energy system has been implemented through an optimization model for the supply of electricity and hydrogen energy for road transportation. The proposed model is in the form of mixed-integer linear programming with two objective functions: planning costs and greenhouse gas emissions. The multi-objective model was solved using the linear weighted-sum method. In this article, three scenarios are developed, namely the business-as-usual scenario, the renewable energy scenario, and the renewable energy with energy storage system scenario. The business-as-usual scenario is used to analyze the supply of electricity and hydrogen by prioritizing the objective function of planning costs. The renewable energy scenario prioritizes the objective function of greenhouse gas emissions in the optimization calculation, but without an energy storage system. The optimization calculation with the renewable energy with energy storage system scenario prioritizes the objective function of greenhouse gas emissions by including the energy storage system. The proposed model in a multi-objective form is implemented in a case study of road transportation in the Province of Yogyakarta, Indonesia. The results obtained indicate that the renewable energy with energy storage system scenario produces the lowest emission level of 56.55 Mt CO2 Equivalent, but with the highest planning cost of 192.13 x 109 Billion USD.
A model of regional energy planning has been developed based in West Papua province. Regional energy planning had two major scenarios: baseline and mitigation. Mitigation scenarios consisted of energy efficiency and fuel switch scenarios. All scenarios are implemented for industrial, commercial, household, transportation, and other sectors. A baseline scenario has been used to reflect energy demand without any intervention from the new energy policy in West Papua Province. The energy efficiency scenario describes the impact of more efficient vehicles and appliances on energy consumption. In the transportation sector, the energy efficiency scenario included a mode change scenario. The use of renewable energy has been included in the fuel switch scenario. In supply-side planning, renewable energy sources have been accommodated to meet a portion of electricity demand. The model of regional energy planning has been implemented by Long-range Energy Alternative Planning software. A cost-benefit analysis has been included in this study. The result indicated that the same goal of a regional development program could be achieved with less emission. By implementing the mitigation scenario, overall energy demand at the end of the projection period can be reduced by 16.63 PJ compared to the baseline. As an impact, the mitigation scenario's global warming potential is 15.89% less than a baseline scenario. It can be concluded that the emission intensity by the implementation of the mitigation scenario is 8.93 Thousand Ton CO2, Equivalent/Billion USD.
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