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Pablo Benalcazar
Mineral and Energy Economy Research Institute of the Polish Academy of Sciences, Division of Energy Economics, ul. Wybickiego 7A, 31-261, Kraków, Poland

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Journal article
Published: 25 June 2021 in Energy
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In the next decades, energy storage technologies will play a major role in decarbonizing the European heating and cooling sector. In this regard, the deployment of complementary technologies is of paramount importance for the energy transformation of the Polish heating sector. This work addresses the challenge of sizing large-scale thermal energy storage (TES) systems for combined heat and power (CHP) plants connected to district heating networks and participating in day-ahead electricity markets. In this paper, a method based on a mixed-integer linear programming approach is proposed to find the optimal capacity of TES units connected to coal-fired CHP systems. The model considers the specific investment costs of the storage technology and optimizes the annual operation scheduling of the CHP-TES system. The model is applied to the case study of a coal-fired CHP system. Four scenarios are used to investigate the performance of the CHP system and evaluate the effects of rising carbon prices on the optimal capacity of the TES unit. The results reveal that the integration of the TES leads to a significant drop in the utilization of the heat-only boilers, helping mitigate fuel and environmental costs.

ACS Style

Pablo Benalcazar. Optimal sizing of thermal energy storage systems for CHP plants considering specific investment costs: A case study. Energy 2021, 234, 121323 .

AMA Style

Pablo Benalcazar. Optimal sizing of thermal energy storage systems for CHP plants considering specific investment costs: A case study. Energy. 2021; 234 ():121323.

Chicago/Turabian Style

Pablo Benalcazar. 2021. "Optimal sizing of thermal energy storage systems for CHP plants considering specific investment costs: A case study." Energy 234, no. : 121323.

Journal article
Published: 01 June 2021 in Energy Conversion and Management
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Thermal energy storage technologies are of great importance for the power and heating sector. They have received much recent attention due to the essential role that combined heat and power plants with thermal stores will play in the transition from conventional district heating systems to 4th and 5th generation district heating systems. This paper presents a novel decision support method for sizing and optimizing the operation of thermal energy storage units in combined heat and power plants. To achieve this goal, the method in this paper comprises three steps. The first step provides an approximation of the storage capacity based on the characterization of the thermal load. The second step extends the applicability of the method by enabling the evaluation of the hourly operation of the combined heat and power plant with thermal storage. The third step evaluates the long-term economic effects of retrofitting the combined heat and power plant with a heat storage option. The applicability of the method is illustrated using the example of a coal-fired combined heat and power plant and the study of two scenarios. The analysis of the scenarios shows that the utilization of the energy storage enhances the operational flexibility of the system by increasing the number of hours in which the combined heat and power plant operates at its maximum electrical output and, at the same time, reduces the thermal contribution of the heat-only boilers. The method developed in this work can be applied to carry out the financial analysis of an energy storage project.

ACS Style

Pablo Benalcazar. Sizing and optimizing the operation of thermal energy storage units in combined heat and power plants: An integrated modeling approach. Energy Conversion and Management 2021, 242, 114255 .

AMA Style

Pablo Benalcazar. Sizing and optimizing the operation of thermal energy storage units in combined heat and power plants: An integrated modeling approach. Energy Conversion and Management. 2021; 242 ():114255.

Chicago/Turabian Style

Pablo Benalcazar. 2021. "Sizing and optimizing the operation of thermal energy storage units in combined heat and power plants: An integrated modeling approach." Energy Conversion and Management 242, no. : 114255.

Journal article
Published: 29 August 2020 in Journal of Natural Gas Science and Engineering
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The delivery of natural gas to consumers requires significant infrastructure that consists of numerous technical units and other gas transmission assets. The failure of a single component in a gas transmission and distribution network might compromise the reliability of the gas supply system. Thus, the proper location of facilities for employees and contractors performing inspections and maintenance activities is of critical importance for the uninterrupted operation of a natural gas network. In this context, this study addresses the problem of identifying the optimal location of gas network maintenance centres (GNMCs) in a natural gas transmission company which is actively seeking to improve its maintenance and service response times while minimising costs. In an effort to determine the optimal number of GNMCs required to maintain assets in areas covered by the company, a decision-support tool based on a mixed-integer linear programming approach (MILP) is proposed. The tool is applied to the case study of a natural gas transmission company operating in central Poland. The case study is extended to explore four alternative scenarios which illustrate the additional functionalities of the proposed model. The model results indicate that the total system cost of the gas network maintenance infrastructure can be reduced by up to 13% with the operation of only two out of five existing GNMCs and one candidate facility. The results also demonstrate the versatility of the optimisation model since it enables decision-makers to evaluate the effects of changing maintenance strategies.

ACS Style

Marcin Malec; Pablo Benalcazar; Przemysław Kaszyński. Optimal location of gas network maintenance centres: A case study from Poland. Journal of Natural Gas Science and Engineering 2020, 83, 103569 .

AMA Style

Marcin Malec, Pablo Benalcazar, Przemysław Kaszyński. Optimal location of gas network maintenance centres: A case study from Poland. Journal of Natural Gas Science and Engineering. 2020; 83 ():103569.

Chicago/Turabian Style

Marcin Malec; Pablo Benalcazar; Przemysław Kaszyński. 2020. "Optimal location of gas network maintenance centres: A case study from Poland." Journal of Natural Gas Science and Engineering 83, no. : 103569.

Journal article
Published: 01 August 2020 in Energies
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Hybrid energy systems (HESs) generate electricity from multiple energy sources that complement each other. Recently, due to the reduction in costs of photovoltaic (PV) modules and wind turbines, these types of systems have become economically competitive. In this study, a mathematical programming model is applied to evaluate the techno-economic feasibility of autonomous units located in two isolated areas of Ecuador: first, the province of Galapagos (subtropical island) and second, the province of Morona Santiago (Amazonian tropical forest). The two case studies suggest that HESs are potential solutions to reduce the dependence of rural villages on fossil fuels and viable mechanisms to bring electrical power to isolated communities in Ecuador. Our results reveal that not only from the economic but also from the environmental point of view, for the case of the Galapagos province, a hybrid energy system with a PV–wind–battery configuration and a levelized cost of energy (LCOE) equal to 0.36 $/kWh is the optimal energy supply system. For the case of Morona Santiago, a hybrid energy system with a PV–diesel–battery configuration and an LCOE equal to 0.37 $/kWh is the most suitable configuration to meet the load of a typical isolated community in Ecuador. The proposed optimization model can be used as a decision-support tool for evaluating the viability of autonomous HES projects at any other location.

ACS Style

Pablo Benalcazar; Adam Suski; Jacek Kamiński. Optimal Sizing and Scheduling of Hybrid Energy Systems: The Cases of Morona Santiago and the Galapagos Islands. Energies 2020, 13, 3933 .

AMA Style

Pablo Benalcazar, Adam Suski, Jacek Kamiński. Optimal Sizing and Scheduling of Hybrid Energy Systems: The Cases of Morona Santiago and the Galapagos Islands. Energies. 2020; 13 (15):3933.

Chicago/Turabian Style

Pablo Benalcazar; Adam Suski; Jacek Kamiński. 2020. "Optimal Sizing and Scheduling of Hybrid Energy Systems: The Cases of Morona Santiago and the Galapagos Islands." Energies 13, no. 15: 3933.

Journal article
Published: 21 June 2020 in Energy Policy
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This paper investigates the potential economic consequences of setting up a capacity market in Poland. A computable model of the Polish power generation system is developed and employed to analyse the impact of this mechanism. Two scenarios are designed for this study: (i) a reference scenario that reflects the energy-only market and (ii) a capacity market scenario that assumes the implementation of such an instrument. To assess the economic consequences, the following parameters are estimated: (i) annual electricity prices, (ii) Loss Of Load Hours, (iii) Expected Energy Not Served, and only for the capacity market scenario: (iv) market clearing price, (v) total budget of the capacity market, and (vi) increase in electricity price due to the introduction of the capacity market. The findings of the study indicate that the long-term maintenance of the energy-only market results in higher electricity prices when compared to putting a capacity market into operation. Introducing a capacity market enables existing resources to be used effectively without excessive capital expenditure. The methods and conclusions presented in this paper provide valuable findings and policy insights regarding the potential economic consequences of a capacity mechanism in a power system mostly dominated by coal and undergoing an energy transition.

ACS Style

Aleksandra Komorowska; Pablo Benalcazar; Przemysław Kaszyński; Jacek Kamiński. Economic consequences of a capacity market implementation: The case of Poland. Energy Policy 2020, 144, 111683 .

AMA Style

Aleksandra Komorowska, Pablo Benalcazar, Przemysław Kaszyński, Jacek Kamiński. Economic consequences of a capacity market implementation: The case of Poland. Energy Policy. 2020; 144 ():111683.

Chicago/Turabian Style

Aleksandra Komorowska; Pablo Benalcazar; Przemysław Kaszyński; Jacek Kamiński. 2020. "Economic consequences of a capacity market implementation: The case of Poland." Energy Policy 144, no. : 111683.

Journal article
Published: 20 February 2020 in Energies
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Microgrids constitute an attractive solution for the electrification of areas where grid extension is not technically feasible or prohibitively expensive. In recent years, national governments have implemented various support policies to encourage the deployment of renewable energy systems (RES) and microgrid hybrid-powered systems. A fundamental aspect during the design and disposition of these types of units is the determination of the optimal configuration and sizing of each power generation component. Furthermore, the optimal design of microgrids is strongly dependent on technological parameters, local meteorological conditions, among other factors. In this context, this paper investigates the effects of different policy measures on the optimal configuration of microgrids functioning in islanded mode. A computable model is employed to carry out a set of sensitivity analyses and assess the impact of capital and fuel subsidies on the levelized cost of electricity of various systems. The model employed for this study minimizes the total life cycle costs (TLCC) over the 20-year lifetime of the microgrid project. Besides, as meteorological conditions are crucial parameters to consider while designing microgrids, a sensitivity analysis is conducted to examine the effect of wind speed and solar irradiation on the capacities of each distributed generation units. Our results indicate that capital subsidies, as well as fuel price variations, have a substantial effect on the final design of microgrid systems for rural electrification.

ACS Style

Pablo Benalcazar; Adam Suski; Jacek Kamiński. The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems. Energies 2020, 13, 955 .

AMA Style

Pablo Benalcazar, Adam Suski, Jacek Kamiński. The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems. Energies. 2020; 13 (4):955.

Chicago/Turabian Style

Pablo Benalcazar; Adam Suski; Jacek Kamiński. 2020. "The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems." Energies 13, no. 4: 955.

Conference paper
Published: 23 January 2019 in IOP Conference Series: Earth and Environmental Science
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With the advent of sustainable energy systems based on renewable energy sources (RES) and the development of a new generation of district heating systems (4GDH), it has become imperative for cogeneration and RES plant operators, as well as district heating (DH) operators, to apply new tools that lead to improvements in production planning, energy efficiency, and at the same time, reduce costs of heat generation. In recent years, machine learning (ML) methods used for the estimation and forecasting of energy demand have drawn considerable attention due to their advantage over linear and nonlinear programming models. In this context, the paper presents an artificial neural network (ANN) approach for the prediction of short-term heat load in a district heating system. The ANN model is trained with past heat load data, weather data and social behavior components. The predictive performance of the neural network model is measured by the mean absolute percentage error (MAPE) and the root mean square error (RMSE).

ACS Style

P Benalcazar; J Kamiński. Short-term heat load forecasting in district heating systems using artificial neural networks. IOP Conference Series: Earth and Environmental Science 2019, 214, 012023 .

AMA Style

P Benalcazar, J Kamiński. Short-term heat load forecasting in district heating systems using artificial neural networks. IOP Conference Series: Earth and Environmental Science. 2019; 214 (1):012023.

Chicago/Turabian Style

P Benalcazar; J Kamiński. 2019. "Short-term heat load forecasting in district heating systems using artificial neural networks." IOP Conference Series: Earth and Environmental Science 214, no. 1: 012023.

Journal article
Published: 20 December 2017 in Gospodarka Surowcami Mineralnymi
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In the 21st century, energy has become an integral part of our society and of global economic development. Although the world has experienced tremendous technological advancements, fossil fuels (including coal, natural gas, and oil) continue to be the world’s primary energy source. At the current production level, it has been estimated that coal reserves (economically recoverable) would last approximately 130 years (with the biggest reserves found in the USA, Russia, China, and India). The intricate relationship between economic growth, demographics and energy consumption (particularly in countries with coal intensive industries and heavy reliance on fossil fuels), along with the elevated amounts of greenhouse gases in the atmosphere, have raised serious concerns within the scientific community about the future of coal. Thus, various studies have focused on the development and application of forecasting methods to predict the economic prospects of coal, future levels of reserves, production, consumption, and its environmental impact. With this scope in mind, the goal of this article is to contribute to the scarce literature on global coal consumption forecasting with the aid of an artificial neural network method. This paper proposes a Multilayer Perceptron neural network (MLP) for the prediction of global coal consumption for the years 2020-2030. The MLP-based model is trained with historical data sets gathered from financial institutions, global energy authorities, and energy statistic agencies, covering the years 1970 through 2016. The results of this study show a deceleration in global coal consumption for the years 2020 (3 932 Mtoe), 2025 (4 069 Mtoe) and 2030 (4 182 Mtoe).

ACS Style

Pablo Benalcazar; Małgorzata Krawczyk; Jacek Kamiński. Forecasting global coal consumption: An artificial neural network approach. Gospodarka Surowcami Mineralnymi 2017, 33, 29 -44.

AMA Style

Pablo Benalcazar, Małgorzata Krawczyk, Jacek Kamiński. Forecasting global coal consumption: An artificial neural network approach. Gospodarka Surowcami Mineralnymi. 2017; 33 (4):29-44.

Chicago/Turabian Style

Pablo Benalcazar; Małgorzata Krawczyk; Jacek Kamiński. 2017. "Forecasting global coal consumption: An artificial neural network approach." Gospodarka Surowcami Mineralnymi 33, no. 4: 29-44.