Combined heat and power – multi-objective optimization with an associated petroleum and wet gas utilization constraint

2018 ◽  
Vol 54 ◽  
pp. 25-36 ◽  
Author(s):  
Priambudi Pujihatma ◽  
Sasongko Pramono Hadi ◽  
Sarjiya ◽  
Tri Agung Rohmat
Keyword(s):  
Combined Heat And Power ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gas Utilization ◽  
Wet Gas

Simulation and multi-objective optimization of a combined heat and power (CHP) system integrated with low-energy buildings

2016 ◽  
Vol 5 ◽  
pp. 13-23 ◽  
Author(s):  
Jamasb Pirkandi ◽  
Mohammad Ali Jokar ◽  
Mohammad Sameti ◽  
Alibakhsh Kasaeian ◽  
Fazel Kasaeian
Keyword(s):  
Combined Heat And Power ◽  
Low Energy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Low Energy Buildings ◽  
Chp System

Multi-objective optimization of a syngas powered reciprocating engine equipping a combined heat and power unit

2020 ◽  
Vol 275 ◽  
pp. 115418 ◽  
Author(s):  
M. Costa ◽  
G. Di Blasio ◽  
M.V. Prati ◽  
M.A. Costagliola ◽  
D. Cirillo ◽  
...  
Keyword(s):  
Power Unit ◽  
Combined Heat And Power ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Reciprocating Engine

scholarly journals Combined heat and power - optimal power flow based on thermodynamic model with associated petroleum and wet gas utilization constraints

2019 ◽  
Vol 9 (1) ◽  
pp. 42
Author(s):  
Priambudi Pujihatma ◽  
Sasongko Pramono Hadi ◽  
Sarjiya Sarjiya ◽  
Tri Agung Rohmat
Keyword(s):  
Natural Gas ◽  
Thermodynamic Model ◽  
Heat Recovery ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Combined Heat And Power ◽  
Steam Generators ◽  
Gas Utilization ◽  
Optimal Power ◽  
Wet Gas

<span lang="EN-GB">Oil fields produce associated petroleum and wet gas, which can be mixed with commercial natural gas as fuel. Associated petroleum and wet gas are a low cost, low quality fuel, whereas commercial natural gas is the opposite. Two parameters are affected by this mixture: the fuel cost and the power – steam output of gas turbine – heat recovery steam generators. This research develops a Unit Commitment and Optimal Power Flow model based on Mixed Integer Nonlinear Programming to optimize combined heat and power cost by considering the optimal mixture between associated petroleum - wet gas and commercial natural gas. A thermodynamic model is used to represent the performance of gas turbine – heat recovery steam generators when subjected to different fuel mixtures. The results show that the proposed model can optimize cost by determining the most efficient power – steam dispatch and optimal fuel mixture. Furthermore, the optimization model can analyse the trade-off between power system losses, steam demand and associated - wet gas utilization. </span>

Multi-Objective Optimization of Combined Heat and Power Industrial Microgrid

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Elham Sheikhi Mehrabadi ◽  
Swamidoss Sathiakumar
Keyword(s):  
Power Systems ◽  
Storage Systems ◽  
Critical Role ◽  
Combined Heat And Power ◽  
Distributed Networks ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Environmental Objectives ◽  
Practical Constraints

Abstract Microgrids play a critical role in the transition from conventional centralized power systems to the smart distributed networks of the future. To achieve the greatest outputs from microgrids, a comprehensive multi-objective optimization plan is necessary. Among various conflicting planning objectives, emissions and cost are primary concerns in microgrid optimization. In this work, two novel procedures, i.e., non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective particle swarm optimization (MOPSO), were developed to minimize emissions and cost in combined heat- and power-based (CHP) industrial microgrids (IMGs) simultaneously, by applying the most practical constraints and considering the variable loads. Two different scenarios, the presence and absence of photovoltaics (PV) and PV storage systems, were analyzed. The results concluded that when considering PVs and PV storage systems, the NSGA-II algorithm provides the most optimized solution in minimizing economic and environmental objectives.

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