Sürdürülebilir enerji kaynaklarının kullanımı ve enerji kullanım verimliliğinin arttırılması, enerji ithal eden ülkeler için kritik önem taşımaktadır. 2012 BP raporuna göre elektrik ve doğal kullanımının %48'i endüstriyel kullanım kaynaklıdır. Endüstriyel kullanımlar dikkate alındığında, kojenerasyon ve trijenerasyon sistemlerinin kurulumu önem kazanmaktadır. Bu sistemler elektrik ve ısı tüketiminin yüksek olduğu sektörlerde hem enerji maliyeti hem de üretim kalitesi açısından avantaj sağlamaktadır.
Avrupa Birliği Enerji Verimliliği 2012 raporuna göre, kojenerasyon sistemlerinin dünya enerji ihtiyacının yalnızca %9'unu karşılamaktadır. Ayrıca, aynı raporda kojenerasyon kullanımının, elektrik ve ısıyı ayrı ayrı üretilmesi durumundaki maliyetlerin %30 ile %50 oranında azalttığı vurgulanmaktadır. Bu sayılar incelendiğinde kojenerasyon kullanımının özendirilmesi sürdürülebilirlik açısından zorunlu görülmektedir
Yakın dönemde, birçok araştırmacı kojenerasyon sistemlerin çizelgelenmesi yöntemlerini araştırmıştır. Geçmiş çalışmalara göre, türbinlerin ihtiyaçlarının belirlenmesi ve buna bağlı olarak türbinlerin kapasite kullanımlarının planlanması önemli faydalar sağlamaktadır. Aynı zamanda, şebekeye satılacak enerji miktarının doğru belirlenebilmesi ekonomik kazanç sağlayacaktır.
Literatürde kojenerasyon planlanması için farklı yöntemlere rastlanmaktadır. Bu yöntemlerden karma tamsayılı programlama, doğrusal ve doğrusal olmayan programla ve genetik algoritma sıkça kullanılan yöntemlerdendir. Bu modeller ekserjetik, çevresel ve ekonomik kısıtları dikkate alan çalışmalar olarak gruplanabilir.
Bu çalışmada, toplam enerji maliyetinin en küçüklenmesi karma tam sayılı programlama yöntemi ile modellenecektedir. Önerilen model hem kojenerasyon kullanarak enerji üretimini hem de üretim sisteminin çalışma parametrelerini belirlemede kullanılacaktır. Çalışma, üretim ve enerji planlamasını birlikte alarak yeni bir model ortaya koymayı hedeflemektedir.
Enerji piyasası değişimleri karar vermeyi doğrudan etkileyecektir. Oluşturulan model, enerji piyasası dinamiklerini dikkate alarak ısı ve elektrik maliyetlerini azaltırken, enerji kullanım verimliliğini arttıracak, üretim maliyetlerini azaltacaktır. Çalışma sonucunda elde edilecek modelin uygulanması ile enerji maliyetlerinin %8 ile %15 arasında azaltılması öngörülmektedir. Ayrıca, şebekeye elektrik satışı kararları alınırken model yol gösterici olacaktır. Böylece gün öncesi satış fiyatları tahminine göre şebekeye satılması en olurlu olan miktar belirlenebilecektir. Sistem ihtiyaçları dikkate alınarak kojenerasyon planlaması yapıldığında, şebekeye aktarılabilecek miktarlar kısıtlı kapasite altında belirlendiği için cezai durumların önüne geçilecektir.
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Supplying sustainable energy resources and improving energy usage efficiency has critical importance for countries depending on energy import. According to 2012 BP report, 48 % of both electricity and natural gas consumption are based on industrial usage. Because of the amount of industrial energy usage, cogeneration and trigeneration systems getting more important.
Cogeneration systems are more efficient than traditional systems about %30-%45. Cogeneration and trigeneration investments have 12-20 years economical life. According to World Energy Committee Turkish Council, investment cost of cogeneration is 890,000 €. According to cost and benefit analysis, return of investment is in almost 2.6 years.
Cogeneration installations start at the beginning of the 20th century. First applications begin with facility constructions at city centers for residential heating. Cogeneration usage has grown fast in countries those have central heating systems. Countries with liquid heating like USA, use high pressured hot steam for residential heating. %30 and %80 of heating requirements of Scandinavian countries is supplied by cogeneration usage.
Although cogeneration supplies both cost and production quality advantages for sectors with high power and heat consumption, usage rate is not high enough. European Union Energy Efficiency 2011 Report states that cogeneration systems responds 9% of global energy demand only. Additionally, the report emphasizes that using cogeneration instead of producing heat and electricity separately, reduces the energy costs about 30-50%. There is a lot to be done to encourage cogeneration more.
Usually natural gas is used for cogeneration systems. Because of combustion characteristic, low emission level and low cost, natural gas is mostly preferred. Propane is alternative with lower combustion efficiency. Renewable resources are also used for cogeneration and trigeneration systems.
In Turkey, cogeneration constructions are 50 years old. After the energy policy change in 1984, private sector producers are allowed to produce energy. Textile, pulp, petro-chemical and food producers prefer cogeneration plants.
Planning of cogeneration system includes different kinds of problems. Minimization of fuel consumption, minimization of operating costs are examples for these problems. Different researchers plan cogeneration scheduling, lately. Studies state that, defining requirements per turbines and allocation capacity of turbines provides incremental benefits. Moreover, planning the amount of power that will be traded with the grid will also provide economic advantages.
Literature review shows that different methods are used for cogeneration planning. Mixed integer programming, linear programming, non-linear programming and genetic algorithms are mostly used techniques. Models are based on exergetic, environmental and economic constraints.
In this study, planning cogeneration system and production facility integrated to cogeneration system is modeled. The research includes relation between power supplier and the grid. Total energy cost minimization will be accomplished by using a Mixed Integer Programming (MIP) method. The proposed mathematical model considers both planning the power generation using a cogeneration system and manufacturing parameters. This study is original in developing a system for combined schedules that can be updated interactively either from the energy or manufacturing sites.
Proposed math model will present minimizing heat and energy costs, increasing energy efficiency and decreasing manufacturing costs, via updating production plans according to the energy market. Model goals to plan optimum working regime for a day, hourly.
Within the scope of the model, different types of resources like turbines, boilers and steam boilers for energy production. Types of resources are defined according to input and output characteristics. Turbines produce electricity, hot exhaust gas and steam by using fuel. Boilers use fuel and produce hot exhaust gas. Steam boilers use fuel and produces steam.
Objective function of the model considers, cost of power acquisition, cost of fuel, cost of restarting turbines and income from power sales to grid.
Energy demand of production processes can be defined by a function. These function considers machine and product characteristics as inputs. These characteristic initiate the power demand of the machine, machine speed, steam pressure and grammage for pulp industry. These characteristic define a production process alternative. The model decides the production process according to optimal energy production level.
Constraints are related to pulp production system, cogeneration system and physical restrictions. There is a constraint to supply using a resource for single production process in a period. Energy demand can be supplied by producing and converting energy. Converting is possible for steam requirements. Steam requirements differentiates according to pressure level of level. Steam at high level pressure can be converted to low level pressure. When energy production and/or conversion is not enough to supply demands, acquisition is possible.
Production facility design directly effects energy production alternatives. For example, when a specific production machine which uses hot exhaust gas is used, at least one of related energy production resources must be used.
The important paper tissue producer of Turkey is selected for the application of the model. Hayat Kimya Holding has pulp/tissue, hygiene and chemical facilities in İzmit, Turkey. Energy demand of this campus is supplied through four natural gas turbines, six boilers and a steam boiler.
The facility has 32 MW power production capacity. Pulp factory is the main customer of cogeneration system. The remaining power from the campus demand is sold to grid. Amount of power to sell should be declared to grid.
The mathematical model supports decisions on detailed 24 hour regime for turbines, amount of power to be exported to the grid, reaction for differentiating pulp types and best schedule fort he dynamic pulp production.
It is observed that implementation of integrated plans reduces energy costs 8%-15%, by responding energy requirements of the manufacturing site fully.
Achievements of his study also avoid the penalties applied by the state energy department. This solution for integrated planning in a manufacturing to stock site is expected to be encouraging for cogeneration usage. By encouraging cogeneration usage, dependency on energy importation will decrease. |