تبادل انرژی بهینه از تولید همزمان صنعتی در بازار برق آتی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|16016||2008||9 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 4992 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Electric Power Systems Research, Volume 78, Issue 10, October 2008, Pages 1764–1772
This paper addresses an optimal strategy for the daily energy exchange of a 22-MW combined-cycle cogeneration plant of an industrial factory operating in a liberalized electricity market. The optimization problem is formulated as a Mixed-Integer Linear Programming Problem (MILP) that maximizes the profit from energy exchange of the cogeneration, and is subject to the technical constraints and the industrial demand profile. The integer variables are associated with export or import of electricity whereas the real variables relate to the power output of gas and steam turbines, and to the electricity purchased from or sold to the market. The proposal is applied to a real cogeneration plant in Spain where the detailed cost function of the process is obtained. The problem is solved using a large-scale commercial package and the results are discussed and compared with different predefined scheduling strategies.
Cogeneration is extensively used as a distributed energy source to meet industrial thermal and electrical demand, one of the reasons being that cogeneration schemes offer high energy efficiency. In the last three decades governmental policies have strongly encouraged industries to install cogeneration as a way to obtain global energy savings and reductions in the environmental impact. Under the scope of the ongoing restructuring process in electricity markets, cogeneration is now considered as a consumer/producer agent entitled to buy or sell electricity according to its needs, which in turn depend on the thermal and electric demands of the industrial process. Some authors have proposed many ways to solve the optimal dispatch problem of cogeneration systems by minimizing all production costs (fuel, operation, maintenance, etc.) related to electric power and thermal capacity , , , , ,  and . Pioneering contributions were made in the late 80s incorporating power trades between the cogeneration plants and electric distribution utility  and  inspired by the spot pricing theory condensed in Ref. . The implementation of spot pricing theory derives from complex price schemes, among other real-time prices (RTP) and time of use prices (TOU)  and . An efficient strategy for energy exchange scheduling in a cogeneration plant is presented in Ref.  that considers real-time prices and consequently shifts steam operations. To assess the impact of TOU prices in cogeneration sizing and operation several optimization procedures have been proposed in the literature and have been classified in Table 1. In Ref. , ,  and  Mixed-Integer Linear Programming (MILP) models have been proposed. Such optimization problems can be appropriately solved with large-scale commercial programming packages. Evolutionary Programming (EP) techniques as well as genetic algorithms (GA) were tested in Ref. , , ,  and  to tackle the nonlinearities of generation cost function. A Newton-based approach was proposed in Ref.  for optimal operation of back pressure cogeneration scheme under TOU rates. In Ref.  a generalized formulation to determine optimal scheduling of a combined-cycle cogeneration unit is discussed, but does not properly consider an energy market structure. The economic benefit of energy exchange of cogenerators with the electric network under pool markets has not been extensively considered, while electricity markets are actually being worldwide operated on this basis. Under day-ahead (DA) electricity markets the awareness of high or low electricity prices in the following day can encourage to sell or to buy electricity depending on the gas and steam turbines operation and the industrial demand in heat and electricity. The cogeneration plant can purchase power in several ways: directly from the DA market hour by hour, by a bilateral contract with a generator, or by a contract agreement with a retailer company (flat, two-part, TOU prices, etc.). Operators of cogeneration systems face a complex problem when considering operating strategies for their facilities. The management of the cogeneration system requires constant evaluation of electrical and thermal load, plant performance variables and the relationship of these variables to energy prices. The operating strategy used must be dynamic and available on an uninterrupted basis to meet the management goal of maximizing the plant's economic return. This work presents an optimal strategy for the energy exchange program of a cogeneration plant of an industrial factory in Spain entitled to sell power in a DA electricity market and to purchase electricity by a negotiated supply contract with a retailer. The optimization problem is written as a Mixed-Integer Linear Programming Problem maximizing the energy exchange profit of the cogeneration in the short term subject to the technical constraints as well as the industrial demand profile. The problem is solved using a large-scale commercial optimization package and the results are discussed and compared for different predefined scheduling strategies.
نتیجه گیری انگلیسی
This paper proposes a short-term optimization scheduling for a daily energy exchange of a combined-cycle cogeneration plant of an industrial factory. The knowledge in advance of day-ahead electricity prices facilitates the definition of an optimal strategy based on 24 h scheduling. The optimization problem is set as Mixed-Integer Linear Programming Problem and solved using a large-scale commercial package. The application of the model into a real cogeneration plant, using a very detailed cost function, shows an energy cost reduction of 10% (approximately 80.000 EUR/month) with respect to other predefined scheduling strategies.