A linear programming model to optimize the decision-making to managing cogeneration system

Park

et al. 2009

Korean J. Chem. Eng.

This paper presents a scheme to achieve structural and operational optimization for the heat plant in a district energy system. A district energy system consists of energy suppliers and consumers, district heating pipelines and heat storage facilities in a region. Production and consumption of energy and transport of energy as well as storage of heat are taken into account in the model. The problem is formulated as a mixed integer linear programming (MILP) problem where the objective is to minimize the overall cost of the district energy system. Evaluation of the energy production cost is based on the daily operation for every season at the plant located at Suseo in Seoul, Korea. From the results of numerical simulations we can see that the district energy system is well approximated by the proposed model, and that the energy efficiency is improved by the application of the optimal operation conditions provided by the proposed model.

mentioning

confidence: 98%

Optimization of the heat plant of district energy systems

Park

et al. 2009

Korean J. Chem. Eng.

“…E CHP kJ The electric energy produced by the CHP H CHP kJ The heat energy produced by the CHP Q U kJ The sum of heat and electricity produced by a CHP G IN kJ The energy of input natural gas η % The CHP efficiency converting gas energy to heat and electricity ζ % Heat to electricity ratio (HTER) V G m 3 The volume of natural gas consumed by the CHP q kJ/m 3 The energy contained in a cubic meter of natural gas The heat demand of the community P E,CHP kW The output electricity power of the CHP P H,CHP kW The output heat power of the CHP P E,CHP_ahead kW…”

Section: Nomenclaturementioning

confidence: 99%

“…Traditionally, heat and electricity are provided with boilers and thermal power plants separately, whose overall efficiency is very low [2]. The low energy utilization efficiency means a waste of resources and a large amount of greenhouse gas emissions particularly carbon dioxide [3]. The existing problems provide incentives to utilize energy more efficiently.…”

Section: Introductionmentioning

confidence: 99%

“…The profit of the community in Mode C 4 H CHP,min kJ The minimum heat energy produced by the CHP H CHP,max kJ The maximum heat energy produced by the CHP E CHP,min kJ The minimum electric energy produced by the CHP E CHP,max kJ The maximum electric energy produced by the CHP P H,CHP,min kW The minimum output heat power from the CHP P H,CHP,max kW The maximum output heat power from the CHP P E,CHP,min kW The minimum output electricity power from the CHP P E,CHP,max kW The maximum output electricity power from the CHP V G,min m 3 The minimum volume of natural gas consumed by the CHP V G,max m 3 The maximum volume of natural gas consumed by the CHP…”

mentioning

confidence: 99%

See 1 more Smart Citation

Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

et al. 2016

Network-connected combined heat and powers (CHPs), owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs' overall efficiency and heat to electricity ratio (HTER) are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

“…The results demonstrated that the proposed approach enables determining near-optimal schedules for achieving energy-saving goals. Tibi and Arman [14] developed a mathematical linear programming model to optimize the decision-making for managing a cogeneration facility as a potential clean-development mechanism project in a hospital in Palestine. The model optimized the cost of energy and the cost of installation of a small cogeneration plant under constraints on electricity-and-heat supply and demand balances.…”

Section: Introductionmentioning

confidence: 99%

Energy-Saving Scheduling in a Flexible Flow Shop Using a Hybrid Genetic Algorithm

Huang¹,

Yu²,

Chen³

2017

JEP

Many researches discussing reduced energy consumption for environmental protection focus on machine efficiency or process redesign. To optimize the machine operation time can also save the energy, and these researches have received great interests in recent years. This study considers three different states of machines, among processing there are two different speeds, to solve the problem of minimizing energy costs under time-of-use tariff with no tardy jobs in flexible flow shop. This problem is basically NP-hard, we proposed a hybrid genetic algorithm (GA) to solve problems in reasonable timeliness. The result shows that to optimize different states of machines under time-of use tariff can reduce energy costs significantly in on-time delivery.