Mixed integer linear programming for the design of solar thermal energy systems with short-term storage

Omu, Akomeno; Hsieh, Shanshan; Orehounig, Kristina

doi:10.1016/j.apenergy.2016.07.055

Cited by 40 publications

(13 citation statements)

References 24 publications

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“…Nevertheless, Equation 6, by considering only the contribution of the useful energy ("dynamic" losses) and neglecting that related to the residual energy ("static" losses), leads to an underestimation of the losses. Indeed, it has been shown by Omu et al [18] that considering static heat losses improves the accuracy of thermal-storage modeling, compared to a simplified thermal-battery model. To this end, different formulations that also consider the residual energy in the computation of the losses have been proposed [13].…”

Section: Teschargementioning

confidence: 99%

A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage

2019

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Cogeneration systems are widely acknowledged as a viable solution to reduce energy consumption and costs, and CO2 emissions. Nonetheless, their performance is highly dependent on their capacity and operational strategy, and optimization methods are required to fully exploit their potential. Among the available technical possibilities to maximize their performance, the integration of thermal energy storage is recognized as one of the most effective solutions. The introduction of a storage device further complicates the identification of the optimal equipment capacity and operation. This work presents a cutting-edge methodology for the optimal design and operation of cogeneration systems with thermal energy storage. A two-level algorithm is proposed to reap the benefits of the mixed integer linear programming formulation for the optimal operation problem, while overcoming its main drawbacks by means of a genetic algorithm at the design level. Part-load effects on nominal efficiency, variation of the unitary cost of the components in relation to their size, and the effect of the storage volume on its thermal losses are considered. Moreover, a novel formulation of the optimization problem is proposed to better characterize the heat losses and operation of the thermal energy storage. A rolling-horizon technique is implemented to reduce the computational time required for the optimization, without affecting the quality of the results. Furthermore, the proposed methodology is adopted to design a cogeneration system for a secondary school in San Francisco, California, which is optimized in terms of the equivalent annual cost. The results show that the optimally sized cogeneration unit directly meets around 70% of both the electric and thermal demands, while the thermal energy storage additionally covers 16% of the heat demands.

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Section: Teschargementioning

confidence: 99%

A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage

2019

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“…Tian and Zhao [17] have published a detail review study about solar collectors and thermal energy storage applications. Omu et al [18] have developed a mixed integer programming for fascinating the design of solar domestic hot water system. Nkhonjera et al [19] have prepared a review study about thermal energy storage designs, heat storage materials.…”

Section: Determination Of Effect Of Bottle Arrangement In the Sensible Thermal Energy Storage System Consisting Ofmentioning

confidence: 99%

Determination of Effect of Bottle Arrangement in the Sensible Thermal Energy Storage System Consisting of Water-Filled PET Bottles on Thermal Performance

Erdemir

2019

Hittite J. Sci. Eng.

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E nergy storage is a significant solution for the later or cheap usage of energy, when the energy source is unavailable or expensive. The main problem related to renewable energy utilization is the time difference between the energy demand and the availability of energy sources. The most common method for solving this mismatch problem is energy storage. Thermal energy storage (TES) is a common and advanced one among the energy storage methods [1, 2]. Basically, TES is to store the energy in a storage medium by converting the energy sources to heat. TES is divided into two sections, which are sensible and latent TES. While sensible TES is to store the energy as heat by changing the temperature of the storage medium, latent TES is to store the energy as heat by changing the phase of storage medium. TES types and storage materials are selected according to the storage capacity, environmental condition, working condition, type of energy sources, etc. Sensible TES

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“…A parametric analysis has been applied to define the optimal operation of a solar thermal system according to the life cycle cost and the energy performance of the system (Ibrahim 2014, -Testi 2016. For defining the optimal solar thermal system under a cold climate condition, a part of the literature has concentrated on the efficiency of the system or the optimal energy storing strategy (Omu 2016, Hugo 2012). An optimal integration of a solar thermal system has been investigated with other onsite energy generation systems such as a heat pump or a photovoltaic system (Tamayo 2014, Lindenberger 2000.…”

Section: Introductionmentioning

confidence: 99%

A cost-optimal solar thermal system for apartment buildings with district heating in a cold climate

Arabzadeh

Jokisalo

Kosonen

2018

International Journal of Sustainable Energy

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Finding the global optimal combination of the main components for a solar thermal energy system is an important topic in utilizing solar radiation in a costeffective way. However, selecting an optimal solar thermal system in a cold climate condition is a challenging task due to the dependency on the heat demand and the limited availability of solar radiation. This research presents several sets of optimum combinations of a solar thermal collector and a hot water storage tank regarding energy efficiency and the life cycle cost for a typical Finnish apartment building. Since domestic hot water consumption forms the significant part of the heat demand in new energy efficient apartment buildings, the applied consumption information were extracted precisely according to measured data. A multi-objective optimization algorithm as NSGAII was implemented to search for global optimal values for selected decision variables. The decision variables were considered as the hot water storage tank volume, the solar thermal collector area and the tilt angle. Based on the results, by using the measured domestic hot water consumption data and through various economic scenarios, the cost-optimal ratio of the solar thermal collector area and storage tank volume was achieved as 16 m 2 /m 3 to 21 m 2 /m 3. The solar thermal system with cost-optimal component sizes was able to save district heat energy consumption up 24% to 34% and made 4 €/m 2 to 23 €/m 2 in financial profit in the studied apartment building.

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Mixed integer linear programming for the design of solar thermal energy systems with short-term storage

Cited by 40 publications

References 24 publications

A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage

A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage

Determination of Effect of Bottle Arrangement in the Sensible Thermal Energy Storage System Consisting of Water-Filled PET Bottles on Thermal Performance

A cost-optimal solar thermal system for apartment buildings with district heating in a cold climate

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