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Author

Elnaz Abdollahi

Bio: Elnaz Abdollahi is an academic researcher from Aalto University. The author has contributed to research in topics: Power transmission & Thermal energy storage. The author has an hindex of 7, co-authored 11 publications receiving 392 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, a combined heat and power (CHP) based district heating (DH) system with RES and energy storage system (ESS) is studied and a modeling and optimization method is developed for planning and operating such CHP-DH systems.

318 citations

Journal ArticleDOI
TL;DR: In this paper, a planning model based on combined heat and power (CHP) modeling is developed for the smart hybrid renewable energy for communities (SHREC) system and a linear programming (LP) algorithm is developed to optimize the SHREC system in a weekly period and the results are compared with an existing energy optimization software.

48 citations

Journal ArticleDOI
TL;DR: In this article, an efficient decomposition-based optimization method is presented to optimize the hourly combined heat and power (CHP) production and power transmission between multiple areas. But the method is not suitable for large-scale HPC systems.

44 citations

Proceedings ArticleDOI
01 Nov 2014
TL;DR: In this article, the authors developed a model for optimizing the operation of a combined heat and power (CHP) plant together with a heat storage, which is a linear programming (LP) model consisting of hourly models connected together with dynamic storage constraints.
Abstract: Combined heat and power (CHP) production is a very efficient technique to produce power and heat in an integrated process. In CHP plants, generation of heat and power follows a joint characteristic, which means that production planning of both commodities must be done in coordination. The hourly produced power can be sold to the grid at market price, but heat must be produced to meet the local demand of district heating or heat for specific industrial processes. Typically, the most profitable operation of a CHP system can be planned by using an optimization model. The high efficiency and profitability of CHP plants can be further improved by utilization of energy storage units. Heat storages make it possible to relax the constraint to produce heat each hour to exactly match the local demand. This allows satisfying the variable heat demand more cheaply by storing heat during low demand and discharging heat when demand is high. By relaxing the connection between heat and power production, heat storages also allow producing more electricity to the power market when the spot price is high and reducing the power generation when spot price is low. The aim of this study is to develop a model for optimizing the operation of a CHP plant together with a heat storage. The model is a linear programming (LP) model consisting of hourly models connected together with dynamic storage constraints. The objective is to minimize the production (fuel) costs subtracted by revenue from selling power to the market. The model is demonstrated using modified reallife data of a Finnish city. The results are useful for planning efficient operation of the plant. The model can also be adapted for determining the optimal size of the storage.

32 citations

Journal ArticleDOI
TL;DR: A novel decomposition method is developed that solves three kinds of smaller sub-models iteratively and produces near-optimal solutions within three iterations, which can solve larger models much faster than the integrated model.

14 citations


Cited by
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Journal ArticleDOI
TL;DR: The potentials of energy hub concept, as a comprehensive model of sustainable energy systems in the future are discussed in this paper, by identifying these challenges and introducing new options for use in energy hub models.
Abstract: In the past, different energy systems were planned and managed independently. But nowadays the development of technologies such as efficient multi-generation system, lead to realizing the benefits of integrated energy infrastructure such as electricity, natural gas, and district heating (DH) networks, and thus a rapid movement toward multi-energy systems (MES). In such systems, different energy carriers and systems interact together in a synergistic way. However, consideration of such a concept requires a suitable tool for integrated management of the system components. Energy hub (EH) that can be defined as the place where the production, conversion, storage and consumption of different energy carriers takes place, is a promising option for integrated management of MES. This paper reviews the different concepts and models used in the literature for EH. The dominant structures used for energy hub models are studied and weaknesses, strengths, and challenges identified and discussed. This article, by identifying these challenges and introducing new options for use in energy hub models, discusses the potentials of energy hub concept, as a comprehensive model of sustainable energy systems in the future.

320 citations

Journal ArticleDOI
TL;DR: In this article, a combined heat and power (CHP) based district heating (DH) system with RES and energy storage system (ESS) is studied and a modeling and optimization method is developed for planning and operating such CHP-DH systems.

318 citations

Journal ArticleDOI
Wei Gu1, Jun Wang1, Shuai Lu1, Zhao Luo1, Chenyu Wu1 
TL;DR: In this paper, an optimal operation model for an integrated energy system (IES) combining the thermal inertia of a district heating network (DHN) and buildings to enhance the absorption of wind power is proposed.

317 citations

Journal ArticleDOI
TL;DR: In this article, the authors explore the implementation of thermal energy storage in district heating and cooling systems, highlighting their potential in combination with district heating, taking into account the research maturity of each type technology.

209 citations

Journal ArticleDOI
TL;DR: It was found that regardless of the method, time series aggregation allows for significantly reduced computational resources, and averaged values lead to underestimation of the real system cost in comparison to the use of representative periods from the original time series.

196 citations