Journal articles: 'Multi-generation energy system'

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Barakhtenko, E. A., and G. S. Mayorov. "Impact of distributed energy generation on energy supply to consumers in an integrated energy system." iPolytech Journal 26, no. 4 (January 2, 2023): 612–25. http://dx.doi.org/10.21285/1814-3520-2022-4-612-625.

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In this work, an approach for accounting and regulating the share of distributed generation in an integrated energy system is developed. In order to model an integrated energy system, a multi-agent approach was used, which presents a technologically complex system as a combination of agents, each having individual behaviour. The essence of a multi-agent approach is as follows: an integrated energy system is represented as a combination of components modelled by their agents having an individual behaviour algorithm; each element of an integrated energy system is involved in the generation of a solution and protects its interests on the basis of efficient energy supply. The implementation of this approach was carried out using the AnyLogic software environment, which includes the basic components of agent and simulation modelling, allowing any multi-agent systems to be developed depending on the application. The custom structure of the multi-agent system for integrated energy systems was developed, factoring in its performance features and interaction of objects, the main composition and types of agents of the multi-agent system being determined. The following types of agents were distinguished: consumer agent, dynamic consumer agent, network agent, manager agent of dynamic consumer, agent of centralised energy source, network agent and advisory agent. A multi - agent model of a real power supply system of a residential area in Irkutsk, having centralised and distributed energy sources, was developed. Taking into account the efficient operation of centralised energy sources, the principles for regulating the share of distributed generation in the system were proposed, allowing the total costs of energy supply to consumers to be reduced by rearranging power between centralised and distributed generation sources. The results obtained using the developed multi-agent model were used to formulate the principles of interactions of centralised and distributed energy generation sources. The redistribution of power between these energy sources on the basis of the above principles reduced the total costs by 4.22% for heat supply and 9.94% for electricity supply to consumers.

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Wang, Yajing, Zhuangzhuang Qu, and Zhimei Wen. "Development and application status of multi energy complementary energy system." E3S Web of Conferences 252 (2021): 03059. http://dx.doi.org/10.1051/e3sconf/202125203059.

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With the emergence of energy shortage and environmental problems, multi energy complementary has been widely used. This paper first analyzes the current grim energy situation, and points out the necessity of implementing multi energy complementary. Secondly, it introduces the multi energy complementary power generation system and multi energy complementary heating system, gives several common system forms, and introduces the system composition and process. Finally, the development prospect of multi energy complementary system is analyzed and summarized.

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Ben Abdessalem, Wahiba, Sami Karaa, and Amira S. Ashour. "Renewable Energy Management with a Multi-Agent System." International Journal of Energy Optimization and Engineering 4, no. 3 (July 2015): 49–59. http://dx.doi.org/10.4018/ijeoe.2015070104.

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Renewable energy generation (Wind, solar …) is rising rapidly around the world. Energy storage is being today realistic with some kind of variable renewable electricity sources such as the Pumped Hydraulic Storage (PHS). The incorporation of the PHS requires different policies since there are a variety of electric generation technologies that can be exploited commonly with the PHS. The energy management system, the scheduling of the generation units is a crucial problem for which adequate solutions can optimize the energy supply. This paper focuses on the applicability of the PHS technology in the development of renewable energy generation in Tunisia. This paper proposes also a multi agent system that can be implemented to simulate the exploitation of the PHS, commonly with other energy sources: conventional energy, wind energy, photovoltaic energy etc.

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Ghasemi-Marzbali, Ali. "Multi-area multi-source automatic generation control in deregulated power system." Energy 201 (June 2020): 117667. http://dx.doi.org/10.1016/j.energy.2020.117667.

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Alirahmi, Seyed Mojtaba, Sajjad Rahmani Dabbagh, Pouria Ahmadi, and Somchai Wongwises. "Multi-objective design optimization of a multi-generation energy system based on geothermal and solar energy." Energy Conversion and Management 205 (February 2020): 112426. http://dx.doi.org/10.1016/j.enconman.2019.112426.

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Wang, Chun, Zu Hua Fang, Ting Ting Hong, Ying Sun, Hong Bing Xu, and Pei Ying Han. "Research on Battery Management in Multi-Power Grid Generation System." Advanced Materials Research 479-481 (February 2012): 1982–85. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1982.

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The multi-power grid generation system will be the main technology in the future use of energy. It can provide high quality uninterruptible power supply for users through the grid-connected system of photovoltaic system, wind power, batteries, and gas-fired power and other clean energy source. Due to the instability of energy source system and the special conditions of the energy storage system, an important factor of affecting the multi-power grid generation system is the energy storage system. So, this paper aims to design an optimized battery management system (BMS). It not only can take advantage of solar, wind, gas and other clean energy source but also have an efficient management and maintenance system to batteries, which can reduce the costs of battery maintenance, and improve the battery packs' efficiency. This design has outstanding advantages over low-medium power applications.

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Jun, Zeng, Liu Junfeng, Wu Jie, and H. W. Ngan. "A multi-agent solution to energy management in hybrid renewable energy generation system." Renewable Energy 36, no. 5 (May 2011): 1352–63. http://dx.doi.org/10.1016/j.renene.2010.11.032.

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Sechilariu, Manuela. "Intelligent Energy Management of Electrical Power Systems." Applied Sciences 10, no. 8 (April 24, 2020): 2951. http://dx.doi.org/10.3390/app10082951.

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Smart grid implementation is facilitated by multi-source energy systems development, i.e., microgrids, which are considered the key smart grid building blocks. Whether they are alternative current (AC) or direct current (DC), high voltage or low voltage, high power or small power, integrated into the distribution system or the transmission network, multi-source systems always require an intelligent energy management that is integrated into the power system. A comprehensive intelligent energy system aims at providing overall energy efficiency with regard to the following: increased power generation flexibility, increased renewable generation systems, improved energy consumption, reduced CO2 emission, improved stability, and minimized energy cost. This Special Issue presents recent key theoretical and practical developments that concern the models, technologies, and flexible solutions to facilitate the following optimal energy and power flow strategies: the techno-economic model for optimal sources dispatching (mono and multi-objective energy optimization), real-time optimal scheduling, and real time optimization with model predictive control.

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He, Xiaohong, and Lijun Zheng. "Analysis Of Multi-energy Complementary Integration Optimization Technology." E3S Web of Conferences 118 (2019): 01057. http://dx.doi.org/10.1051/e3sconf/201911801057.

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This paper studies ways to improve the capacity of renewable energy to reduce the adverse effects of renewable energy generation on the power grid system, improve energy efficiency, and implement comprehensive complementary utilization of multiple energy sources. According to different resource conditions and energy demands, the multi-energy complementary systems are constructed through comprehensive energy management and collaborative optimization control. On the basis of summarizing the technical routes of multi-energy complementary system at home and abroad, the key technologies of multi-energy complementary were discussed, including various power characteristics, complementary ways and future research directions. It provides a reference for the development and application of multi-energy complementary system

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Bozorg-Haddad, Omid, Irene Garousi-Nejad, and Hugo A. Loáiciga. "Extended multi-objective firefly algorithm for hydropower energy generation." Journal of Hydroinformatics 19, no. 5 (June 9, 2017): 734–51. http://dx.doi.org/10.2166/hydro.2017.114.

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Classical methods have severe limitations (such as being trapped in local optima, and the curse of dimensionality) to solve optimization problems. Evolutionary or meta-heuristic algorithms are currently favored as the tools of choice for tackling such complex non-linear reservoir operations. This paper evaluates the performance of an extended multi-objective developed firefly algorithm (MODFA). The MODFA script code was developed using the MATLAB programming language and was applied in MATLAB to optimize hydropower generation by a three-reservoir system in Iran. The two objectives used in the present study are the maximization of the reliability of hydropower generation and the minimization of the vulnerability to generation deficits of the three-reservoir system. Optimal Paretos (OPs) obtained with the MODFA are compared with those obtained with the multi-objective genetic algorithm (MOGA) and the multi-objective firefly algorithm (MOFA) for different levels of performance thresholds (50%, 75%, and 100%). The case study results demonstrate that the MODFA is superior to the MOGA and MOFA for calculating proper OPs with distinct solutions and a wide distribution of solutions. This study's results show that the MODFA solves multi-objective multi-reservoir operation system with the purpose of hydropower generation that are highly nonlinear that classical methods cannot solve.

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Fan, Lijun, and Jiedong Cui. "Capacity optimization of renewable energy microgrid considering hydropower cogeneration." Journal of Physics: Conference Series 2083, no. 3 (November 1, 2021): 032068. http://dx.doi.org/10.1088/1742-6596/2083/3/032068.

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Abstract This paper proposes a renewable energy system based on photovoltaic power generation, wind power generation and solar thermal power generation, combining thermal power plants with low-temperature multi-effect distillation. Through the electric heater and the thermal storage system photovoltaic and wind power will spare capacity in the form of heat energy, at the same time by thermal power generation system to maintain the stability of the power supply, run under constant output scheduling policy, to the levelling of the smallest energy cost and the design of power rate of maximum satisfaction as the goal, using multi-objective particle swarm optimization (PSO) algorithm to find the best combination of capacity, this system is established. At the same time, combined with low-temperature multi-effect distillation, compared with reverse osmosis seawater desalination cost is lower, reduce energy consumption, has a good application prospect.

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Cui, Shuangshuang, Qing He, Yixue Liu, Tingting Wang, Xingping Shi, and Dongmei Du. "Techno-economic analysis of multi-generation liquid air energy storage system." Applied Thermal Engineering 198 (November 2021): 117511. http://dx.doi.org/10.1016/j.applthermaleng.2021.117511.

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Xu, Zhicheng, Gang Lu, and Jiujin Zhao. "Multi-scenario generation technology considering extreme scenarios in energy system modeling." IOP Conference Series: Earth and Environmental Science 546 (August 12, 2020): 022057. http://dx.doi.org/10.1088/1755-1315/546/2/022057.

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Almehmadi, Fahad Awjah, Hassan Fawzy Elattar, Ali Fouda, Saeed Alqaed, Mathkar A. Alharthi, and Hassanein Abdelmohsen Refaey. "Towards an Efficient Multi-Generation System Providing Power, Cooling, Heating, and Freshwater for Residential Buildings Operated with Solar-Driven ORC." Applied Sciences 12, no. 21 (November 3, 2022): 11157. http://dx.doi.org/10.3390/app122111157.

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In buildings, multi-generation systems are a promising technology that can replace discrete traditional energy production methods. A multi-generation system makes it possible to efficiently produce electricity, cooling, heating, and freshwater simultaneously. This study involved the numerical analysis of a modified proposed novel solar-driven multi-generation system (MGS-II) integrated with the Organic Rankine Cycle (ORC), Humidification–Dehumidification Desalination System (HDH), and Desiccant Cooling System (DCS) by using heat recovery and thermal energy storage (TES) units. In addition, a comparison study with the basic multi-generation system (MGS-I) is performed. The proposed system is designed to supply electricity, air conditioning, domestic heating, and fresh water to small/medium-sized buildings. How operating conditions affect system productivity and performance metrics have been investigated. The results show that the proposed multi-generation system (MGS-II) can produce electrical power, space cooling, domestic heating and fresh water while maintaining comfortable conditions inside the conditioned space. Moreover, the MGS-II outperforms the MGS-I system, and the maximum MGS-II system productivity; electricity production (\({W_{net}^{\bullet}}\)), freshwater (\({m_{fresh}^{\bullet} }\)), space cooling (\({Q_{cooling}^{\bullet} }\)), and domestic heating (\({Q_{heating}^{\bullet} }\)) are 102.3 kW, 141.5 kg/h, 20.77 kW, and 225 kW, respectively. In addition, the highest total gained output ratio (TGOR), specific total gained energy (STG), and specific total gained energy equivalent price (STGP) of the MGS-II system are 0.6303, 3.824 kWh/m2, and 0.149 USD/m2, respectively. The accepted ranges of comfortable space-supplied air conditions (temperature and humidity) are 15.5–18.2 °C and 9.2–12.00 gv/kga for both systems, MGS-I and MGS-II. Finally, the current system (MGS-II) has the maximum of the system’s performance indicators and productivity (TGOR and \({{\overset{.}{m}}_{fresh} }\)) compared with the other reported systems.

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Yang, Jialin, Zhen Li, Nan Wang, Pengxiang Zhao, Xichao Zhou, Lin Cong, Lu Xue, and Yongli Wang. "Integrated energy system planning study based on load prediction." E3S Web of Conferences 245 (2021): 01057. http://dx.doi.org/10.1051/e3sconf/202124501057.

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The planning of integrated energy system is a very complex multi-objective, multi-constraint, nonlinear, random uncertain hybrid combination optimization problem, its planning and design process should consider not only the system capacity, energy exchange, energy storage, energy and other links between the interdependence, but also the interaction and mixing of cold, hot, electricity and other multi-energy flow, which is essentially a non-deterministic polynomial problem. Based on load prediction technology, combined with scene generation, multi-interconnected energy system modeling and other technologies, around the integrated energy system planning and design, consider the comprehensive evaluation of the whole life cycle, an optimal configuration of the integrated energy system is formed.

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Wang, Liying, Ming Zeng, Yuwei Cao, Shi Tian, Xuefeng Xu, and Jun Yang. "Research on operation strategy optimization method of multi-energy complementary new energy generation system." IOP Conference Series: Materials Science and Engineering 677 (December 10, 2019): 032027. http://dx.doi.org/10.1088/1757-899x/677/3/032027.

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Chen, Zhen, and Wei Dou Ni. "Synergetic Utilization of Coal and Industrial Waste Heat in Power Generation System." Advanced Materials Research 724-725 (August 2013): 990–98. http://dx.doi.org/10.4028/www.scientific.net/amr.724-725.990.

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Coal and industrial waste heat synergetic utilization power generation system (the synergetic system) is proposed according to the energy cascade utilization principle. The industrial waste heat is used for feedwater heating of coal-fired power generation system to substitute steam extraction from steam turbine. The thermal performance of stand-alone waste heat power generation, stand-alone coal-fired power generation, and synergetic systems were studied, to compare the power generation capability of each system using heat balance method. The results show that the power generation capability of synergetic power generation system is larger than that of the two stand-alone systems. The equivalent and same grade waste heat synergized with higher-parameter, larger-capacity coal-fired power generation systems can generate more electricity than with the low-parameter ones; the high-parameter waste heat synergized with the higher-parameter and larger-capacity power generation systems can reach larger power generation capability. The multi-energy synergetic heating mode can greatly improve the comprehensive energy efficiency and reduce the coal consumption compared with the stand-alone energy heating mode.

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Cui, Yong, Anselme Andriamahery, Lie Ao, Jian Zheng, and Zhiqiang Huo. "Analysis of Optimal Operation of Multi-Energy Alliance Based on Multi-Scale Dynamic Cost Equilibrium Allocation." Sustainability 14, no. 24 (December 7, 2022): 16337. http://dx.doi.org/10.3390/su142416337.

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This paper discusses the power generation characteristics between new energy and traditional energy. This paper uses different energy alliance operation modes for a power system led by new energy power generation. The peak-valley power imbalance issue for real-time load is mitigated through coordinated and optimized energy supply by wind, photovoltaic, hydro (hydropower station with pumped storage function as an example.), and thermal power, aiming to peak load shifting for the system. Moreover, from the perspective of optimal allocation of resources within the alliance and multi-scale cost equilibrium optimization of each subject’s power generation combination, the marginal contribution of different agents is considered. A multi-energy alliance operation optimization decision-making method is designed based on the Shapley value method. This paper studies the multi-scale combination cost allocation of each subject and the distribution law of dynamic optimization of its output ratio. The relationship between the power generation ratio and the cost allocation for each subject. Moreover, the discrete coefficient equation of cost equilibrium values is constructed to verify the equilibrium distribution effect of the Shapley cost allocation model. The case analysis shows that the 46th combination scheme for the multi-energy alliance can realize the main output of wind power and photovoltaic new energy under the premise of the relatively stable alliance corresponding output ratio of 0.2 and 0.4, respectively. The research proves that the operation mechanism of the multi-energy alliance plays a supporting role in the optimal operation of the new energy power system. Meanwhile, this method can be used as a basis for the power generation planning, cost control, and power generation combination optimization decisions on each entity within the alliance.

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Ghorab, Mohamed, Libing Yang, Evgueniy Entchev, Euy-Joon Lee, Eun-Chul Kang, Yu-Jin Kim, Sangmu Bae, Yujin Nam, and Kwonye Kim. "Multi-Objective Optimization of Hybrid Renewable Tri-Generation System Performance for Buildings." Applied Sciences 12, no. 2 (January 16, 2022): 888. http://dx.doi.org/10.3390/app12020888.

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Hybrid renewable energy systems are subject to extensive research around the world and different designs have found their way to the market and have been commercialized. These systems usually employ multiple components, both renewable and conventional, combined in a way to increase the system’s overall efficiency and resilience and to lower GHG emissions. In this paper, a hybrid renewable energy system was designed for residential use and its annual energy performance was investigated and optimized. The multi-module hybrid system consists of a Ground-Air Heat Exchanger (GAHX), Photovoltaic Thermal (PVT) panels and Air to Water Heat Pump (AWHP). The developed system’s annual performance was simulated in the TRaNsient SYStem (TRNSYS) environment and optimized using the General Algebraic Modelling System (GAMS) platform. Multi-objective non-linear optimization algorithms were developed and applied to define optimal system design and performance parameters while reducing cost and GHG emissions. The results revealed that the designed system was able to satisfy building thermal heating/cooling loads throughout the year. The ground source heat exchanger contributed 21.3% and 26.3% of the energy during heating and cooling seasons, respectively. The initial design was optimized in terms of key performance parameters and module sizes. The annual simulation analysis showed that the system was able to self-generate and meet nearly 29.4% of the total HVAC electricity needs, with the rest being supplied by the grid. The annual system module performance efficiencies were 13.4% for the PVT electric and 5.5% for the PVT thermal, with an AWHP COP of 4.0.

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Zhou, Nan, and Da Xie. "Multi-energy System Planning Based on Cascade Hydro-Photovoltaic-Pumped Storage Hybrid Generation System." IOP Conference Series: Earth and Environmental Science 766, no. 1 (June 1, 2021): 012007. http://dx.doi.org/10.1088/1755-1315/766/1/012007.

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Hui, Qian, Yun Teng, and Zhe Chen. "A Multi-Energy System Cluster Operation Optimization Method Based on Nanocomposite Electrode Materials Energy Storage Equipment." Journal of Nanoelectronics and Optoelectronics 16, no. 12 (December 1, 2021): 1931–41. http://dx.doi.org/10.1166/jno.2021.3159.

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A cluster operation optimization method of multi-energy system is proposed based on nanocomposite electrode materials energy storage in this paper, aiming at the difficulty in power balance coordination control of regional-level multi-energy systems due to the rapid growth of renewable energy power generation. In this method, the dynamic influence of nanocomposite electrode materials on the peak power of energy storage is fully considered. The power balance adjustment capability of the multi-energy system is effectively improved by this method. First, an operation optimization control model of multi-energy system cluster based on nanocomposite electrode materials energy storage equipment is established based on the peak power of energy storage, the joint response of renewable energy, thermal and hydrogen energy, and the operation characteristics of multi-energy systems. Then, the multi-energy system cluster coordinated operation strategy model and its solution algorithm based on the maximum renewable energy consumption and operating benefit are studied. Finally, a PSCAD simulation model based on the IEEE 14-nodes system is established. The simulation results and analysis show that the multi-energy system cluster operation optimization model based on nanocomposite electrode material energy storage equipment can effectively improve the power balance ability of the multi-energy system under the condition of the uncertainty of renewable energy. And this method can reduce the cost of grid operation and power regulation, and improve the efficiency of refined energy management of energy storage.

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Riaz, Ahmad, Chao Zhou, Ruobing Liang, and Jili Zhang. "Performance study on photovoltaic thermal building façade component in multi-energy generation during winter." Building Services Engineering Research and Technology 42, no. 4 (February 7, 2021): 405–19. http://dx.doi.org/10.1177/0143624421991970.

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Photovoltaic thermal systems have gained tremendous popularity in the production of electric and thermal energy. In this paper, the photovoltaic thermal modules for the building façade assisted by heat pump system is proposed which combines the photovoltaic modules with an evaporator part of the heat pump system to produce hot water and electrical energy. Also, the photovoltaic thermal panels are used to preheat the cold ambient fresh air without heat pump operation. The proposed system was constructed at the Institute of Building Energy, Dalian University of Technology, China to study the ambient fresh air heating characteristic, electrical power generation, and hot water generation through performance evaluation indices under natural weather conditions. It was found that the average electrical, thermal, and overall efficiencies are 8.8%, 26%, and 50%, respectively during the pre-heating of fresh air. While the average air temperature is 15.2°C inside an air gap. The average COP for water heating is 3.91 during the water heating mode. This study could be used as a guide for photovoltaic thermal solar-assisted heat pump systems on building envelopes in a multi-energy generation under different weather conditions. Practical application: The study considers the photovoltaic thermal modules for building façade not only to generate the electrical energy and pre-heated fresh air but also to generate the hot water when assisted with the heat pump system. This research could assist researchers and engineers in the field of photovoltaic thermal façade systems in multi-energy generation such as for the production of electricity, heated/cooled fresh air, and hot water generation.

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Ma, Chao, Sen Dong, Jijian Lian, and Xiulan Pang. "Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System." Sustainability 11, no. 19 (October 1, 2019): 5441. http://dx.doi.org/10.3390/su11195441.

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Hybrid energy storage systems (HESS) are an effective way to improve the output stability for a large-scale photovoltaic (PV) power generation systems. This paper presents a sizing method for HESS-equipped large-scale centralized PV power stations. The method consists of two parts: determining the power capacity by a statistical method considering the effects of multiple weather conditions and calculating the optimal energy capacity by employing a mathematical model. The method fully considers the characteristics of PV output and multiple kinds of energy storage combinations. Additionally, a pre-storage strategy that can further improve stability of output is proposed. All of the above methods were verified through a case study application to an 850 MW centralized PV power station in the upstream of the Yellow river. The optimal hybrid energy storage combination and its optimization results were obtained by this method. The results show that the optimal capacity configuration can significantly improve the stability of PV output and the pre-storage strategy can further improve the target output satisfaction rate by 8.28%.

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Tezde, Efe Isa, Halil Ibrahim Okumus, and Ibrahim Savran. "Two-Stage Energy Management of Multi-Smart Homes With Distributed Generation and Storage." Electronics 8, no. 5 (May 8, 2019): 512. http://dx.doi.org/10.3390/electronics8050512.

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This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such as PV and wind turbines, distributed storage systems (DSS) such as electric vehicle (EV), and batteries. HEMS organizes the controllable appliances considering user preferences, amount of energy generated/stored and electricity price. A group of optimum consumption schedules for each HEMS is calculated by a Genetic Algorithm (GA). In the second stage, a neighborhood energy management system (NEMS) is established based on Bayesian Game (BG). In this game, HEMSs are players and their pre-determined optimal schedules are their actions. NEMS regulates the total power fluctuations by allowing the energy transfer among households. In the proposed algorithm, HEMS decreases the electricity cost of the users, while NEMS flats the load curve of the neighborhood to prevent overloading of the distribution transformer. The proposed HEMS and NEMS models are implemented from scratch. A survey of 250 participants was conducted to determine user habits. The results of the survey and the proposed system were compared. In conclusion, the proposed hybrid energy management system saves power by up to 25% and decreases cost by 8.7% on average.

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Bayod-Rújula, Angel A., Yue Yuan, Amaya Martínez-Gracia, Jiangyu Wang, Javier Uche, and Huanxin Chen. "Modelling and Simulation of a Building Energy Hub." Proceedings 2, no. 23 (November 21, 2018): 1431. http://dx.doi.org/10.3390/proceedings2231431.

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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 heating 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. An Energy hub (EH) 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. In this work we present the hourly Schedule along a year of a building energy hub, with local generation of heat and power, energy storage and electrical and thermal loads. We include PVT systems and a CHP system in the local generation of heat and power, and a gas boiler. A battery is considered as electrical storage and a water tank as thermal storage. The system is connected to the mail grids of power and gas. The typical thermal and electrical load of a building has been considered, with a heat pump that is considered as a deferral load. The model for all the components has been developed, and a yearly simulation has been carried out in which prices of electricity and gas have been considered.

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Yu, Chutian, Xinyi Lai, Fei Chen, Chenwei Jiang, Yikai Sun, Lijun Zhang, Fushuan Wen, and Donglian Qi. "Multi-Time Period Optimal Dispatch Strategy for Integrated Energy System Considering Renewable Energy Generation Accommodation." Energies 15, no. 12 (June 13, 2022): 4329. http://dx.doi.org/10.3390/en15124329.

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With the target of carbon peaking and carbon neutrality, renewable energy generation (REG) develops rapidly. The increasing penetration of REG brings along the problems of fluctuation in power flow and the possible abandonment of wind and photovoltaics (PV) generation. In this context, the so-called integrated energy system (IES) becomes a promising solution to the accommodation of REG thanks to energy storage systems and coupling devices inside. In this paper, the optimal operation model of an IES is first presented, with the schemes of green certificate trading and carbon emission right trading included to provide economic incentives for accommodating REG. Next, in order to address the problem of uncertainty in REG, the devices in the IES are divided into three types based on regulation flexibility, and a multi-time period optimal dispatching scheme is proposed, including day-ahead optimal scheduling, rolling optimal dispatching, and real-time control strategy. Finally, it is demonstrated by simulation results of a numerical example that the proposed method not only promotes the accommodation capability for REG but can also cope well with contingencies.

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Jasim, Ali M., Basil H. Jasim, Habib Kraiem, and Aymen Flah. "A Multi-Objective Demand/Generation Scheduling Model-Based Microgrid Energy Management System." Sustainability 14, no. 16 (August 16, 2022): 10158. http://dx.doi.org/10.3390/su141610158.

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In recent years, microgrids (MGs) have been developed to improve the overall management of the power network. This paper examines how a smart MG’s generation and demand sides are managed to improve the MG’s performance in order to minimize operating costs and emissions. A binary orientation search algorithm (BOSA)-based optimal demand side management (DSM) program using the load-shifting technique has been proposed, resulting in significant electricity cost savings. The proposed optimal DSM-based energy management strategy considers the MG’s economic and environmental indices to be the key objective functions. Single-objective particle swarm optimization (SOPSO) and multi-objective particle swarm optimization (MOPSO) were adopted in order to optimize MG performance in the presence of renewable energy resources (RERs) with a randomized natural behavior. A PSO algorithm was adopted due to the nonlinearity and complexity of the proposed problem. In addition, fuzzy-based mechanisms and a nonlinear sorting system were used to discover the optimal compromise given the collection of Pareto-front space solutions. To test the proposed method in a more realistic setting, the stochastic behavior of renewable units was also factored in. The simulation findings indicate that the proposed BOSA algorithm-based DSM had the lowest peak demand (88.4 kWh) compared to unscheduled demand (105 kWh); additionally, the operating costs were reduced by 23%, from 660 USD to 508 USD, and the emissions decreased from 840 kg to 725 kg, saving 13.7%.

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Adebayo, Victor, Mustafa Dagbasi, Michael Taiwo, Qi Huang, and Olusola Bamisile. "Energy, exergy and environmental analyses of a biomass driven multi-generation system." International Journal of Exergy 31, no. 3 (2020): 249. http://dx.doi.org/10.1504/ijex.2020.10027917.

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Bamisile, Olusola, Qi Huang, Mustafa Dagbasi, Michael Taiwo, and Victor Adebayo. "Energy, exergy and environmental analyses of a biomass driven multi-generation system." International Journal of Exergy 31, no. 3 (2020): 249. http://dx.doi.org/10.1504/ijex.2020.106454.

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Nazarpour, Daryoush, Mehdi Rashidi, Amin Safari, and Mahdi Sabri. "Multi-objective optimal placement of renewable energy generation in deregulated power system." International Journal of Energy and Statistics 05, no. 01 (March 2017): 1750001. http://dx.doi.org/10.1142/s2335680417500016.

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Ahmadi, Pouria, Ibrahim Dincer, and Marc A. Rosen. "Development and assessment of an integrated biomass-based multi-generation energy system." Energy 56 (July 2013): 155–66. http://dx.doi.org/10.1016/j.energy.2013.04.024.

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Malik, Monu, Ibrahim Dincer, and Marc A. Rosen. "Development and analysis of a new renewable energy-based multi-generation system." Energy 79 (January 2015): 90–99. http://dx.doi.org/10.1016/j.energy.2014.10.057.

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Efimov, Dmitry, and Dmitry Bykov. "Load-flow model of a multi-energy system." E3S Web of Conferences 139 (2019): 01050. http://dx.doi.org/10.1051/e3sconf/201913901050.

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Current trends in the energy development includes the creation of multi-energy systems (MES) with several energy carriers that are planned, designed and operated with essential coordination of their subsystems. When managing the development and functioning of such systems, optimization problems should be solved to minimize the cost of production, transmission and distribution of energy resources. Traditionally, the means of such minimization are the redistribution of the loads of generation sources, consumers and energy storage devices. The topology of MES if different for different energy carriers, and topologies are combined through energy hubs – nodes in which energy is converted from one type to another. Such transformation can simply be considered as the consumption of one type of energy with the simultaneous generation of another type. This provides brand new opportunities for optimizing modes specific to a MES. Essential part of the search of optimal solution is the calculation of the load flow – that is, the determination of nodes’ and connections’ mode parameters of the system subject to balance equations (Kirchhoff’s circuit laws). The load flow equations act as constraints in optimization problems. This paper presents an attempt to form a single model for calculating the load flow of different energy carriers in a MES.

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Delgado, Carmen, and José Antonio Domínguez-Navarro. "Multi-objective design optimization of hybrid renewable systems using UGF." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 34, no. 6 (November 2, 2015): 1825–44. http://dx.doi.org/10.1108/compel-11-2014-0326.

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Purpose – Renewable generation is a main component of most hybrid generation systems. However, randomness on its generation is a characteristic to be considered due to its direct impact on reliability and performance of these systems. For this reason, renewable generation usually is accompanied with other generation elements to improve their general performance. The purpose of this paper is to analyze the power generation system, composed of solar, wind and diesel generation and power outsourcing option from the grid as means of reserve source. A multi-objective optimization for the design of hybrid generation system is proposed, particularly using the cost of energy, two different reliability indexes and the percentage of renewable energy as objectives. Further, the uncertainty of renewable sources and demand is modeled with a new technique that permits to evaluate the reliability quickly. Design/methodology/approach – The multi-state model of the generators and the load is modeled with the Universal Generating Function (UGF) to estimate the reliability indexes for the whole system. Then an evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm) is used to solve the multi-objective optimization model. Findings – The use of UGF methodology reduces the computation time, providing effective results. The validation of reliability assessment of hybrid generation systems using the UGF is carried out taking as a benchmark the results obtained with the Monte Carlo simulation. The proposed multi-objective algorithm gives as a result different generators combinations that outline hybrid systems, where some of them could be preferred over others depending on its results for each independent objective. Also it allows us to observe the changes produced on the resulting solutions due to the impact of the power fluctuation of the renewable generators. Originality/value – The main contributions of this paper are: an extended multi state model that includes different types of renewable energies, with emphasis on modeling of solar energy; demonstrate the performance improvement of UGF against SMC regarding the computational time required for this case; test the impact of different multi-states numbers for the representation of the elements; depict through multi-objective optimization, the impact of combining different energies on the cost and reliability of the resultant systems.

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Ramakrishna, K. S. S., and T. S. Bhatti. "Automatic generation control of single area power system with multi-source power generation." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 222, no. 1 (February 2008): 1–11. http://dx.doi.org/10.1243/09576509jpe405.

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Arabkoohsar, Ahmad, Amirmohammad Behzadi, and Natasa Nord. "A highly innovative yet cost-effective multi-generation energy system for net-zero energy buildings." Energy Conversion and Management 237 (June 2021): 114120. http://dx.doi.org/10.1016/j.enconman.2021.114120.

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Yuksel, Yunus Emre, and Murat Ozturk. "Energy and exergy analysis of renewable energy sources-based integrated system for multi-generation application." International Journal of Exergy 22, no. 3 (2017): 250. http://dx.doi.org/10.1504/ijex.2017.083170.

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Ozturk, Murat. "Energy and exergy analysis of renewable energy sources based integrated system for multi-generation application." International Journal of Exergy 22, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijex.2017.10003719.

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Lombardi, Pio, Bartlomiej Arendarski, Konstantin Suslov, Natalia Shamarova, Polina Sokolnikova, Antonio Marco Pantaleo, and Przemyslaw Komarnicki. "A Net-Zero Energy System Solution for Russian Rural Communities." E3S Web of Conferences 69 (2018): 01013. http://dx.doi.org/10.1051/e3sconf/20186901013.

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The COP 21 agreement state that the reduction of CO2 emissions will limit the rise of global temperatures and thus the impacts of global warming. Since the energy sector is one of the biggest CO2 emitters, greening it is one of the actions selected to achieve COP 21 targets. Increased generation from renewable sources, however, should entail an increase of flexibility options for integrating renewable energy in the system. The volatility of renewable sources such as wind and sun requires flexible storage units, energy conversion and management techniques as well as active consumer participation to ensure the power system is balanced. In multi-energy systems, the electricity generated by renewables is converted into other energy forms such heat or gas. Rural areas result to be attractive test bench in which multi-energy system could be developed. The objective of this study is to analyze the potential for the development of multi-energy systems in remote Russian communities.

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Tseng, Cheng-Jui, Ngakan Ketut Acwin Dwijendra, Maria Jade Catalan Opulencia, Sarvinoz Ganieva, and Iskandar Muda. "Optimal Energy Management in a Smart Micro Grid with Demand Side Participation." Environmental and Climate Technologies 26, no. 1 (January 1, 2022): 228–39. http://dx.doi.org/10.2478/rtuect-2022-0018.

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Abstract The energy management in energy systems is the main solution for energy companies in order to provide minimization of the energy generation costs and emission polluting. In this work, a multi-criteria optimization model is implemented for minimizing the generation cost and emission in a smart micro grid (SMG) at day-ahead planning. In this modelling, the demand side participates in optimal energy management through two strategies such as demand shifting and onsite generation by the energy storage system (ESS). The optimal participation of demand side is modelled based on energy price in energy market. Implementation of the proposed approach in GAMS software is done, and weight sum method (WSM) is employed for solving multi-criteria optimization. The desired optimal solution of multi-criteria objectives is found via the max-min fuzzy procedure. Finally, confirmation of the proposed approach is analysed by numerical simulation in two case studies.

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Pei, Huanjin, Su Guo, Yi He, and Jiale Wang. "Capacity optimization of concentrated solar power-photovoltaicwind power combined generation system." E3S Web of Conferences 118 (2019): 02060. http://dx.doi.org/10.1051/e3sconf/201911802060.

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Due to the fluctuation and randomness of renewable resources, such as solar irradiation resource and wind resource, independent renewable power plants are not easy to generate stable and reliable power. However, multi-energy complementary power generation with energy storage can improve the power quality of renewable energy generation and meet the requirements of grid-connected, so it will be the mainstream of renewable energy generation in the future. Capacity optimization of multi-energy complementary system is the basis and key to improve the power quality and reduce cost of renewable power generation. This paper describes the capacity optimization model of concentrated solar power-photovoltaic-wind (CSP-PV-Wind) combined power generation system. The optimization objectives are as follows: (1) the power is as close to the load as possible; (2) the low overall investment of the combined power supply; (3) the high annual total power generation revenue. The improved particle swarm optimization algorithm is used to optimize the capacity configuration of CSP-PV-Wind combined power generation system, and obtain the optimal dispatch strategy. The results show that, power quality of CSP-PV-Wind combined power generation system is obviously better than that of PV-wind combined power generation system, while Surplus of Power Supply Probability (SPSP) and Loss of Power Supply Probability (LPSP) are all below 15%. However the power generation cost is still a little higher. Therefore, the strategy of reducing the area of collector and increasing the storage tank capacity will be used to decrease the generation cost in the future.

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Xu, Lin, Jing Yu Ru, Xi Jian Zhang, Ya Qiang Chen, and Xi Qing Mu. "The Design of Off-Grid Multi-Energy Complementary Power System." Advanced Materials Research 282-283 (July 2011): 739–43. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.739.

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One kind of multi-energy off-grid hybrid power system is designed. The system combines highly efficient solar photovoltaic power generation system, ultra low wind speed electric power facility, pedal-powered electricity generating device with the function of automatic reciprocating type. The signals are selected and controlled by STC12c2052 single chip, then the electric energy is delivered to the storage battery through the DC/DC module. Thus, a system with high efficiency and multi-energies complementary is obtained. It can be conclude that this system, cost-effective and environmentally friendly, has great potential in saving energy and environmental protection.

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Zhang, Ning, Nien-Che Yang, and Jian-Hong Liu. "Optimal Time-of-Use Electricity Price for a Microgrid System Considering Profit of Power Company and Demand Users." Energies 14, no. 19 (October 4, 2021): 6333. http://dx.doi.org/10.3390/en14196333.

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With high proportions of renewable energy generation in power systems, the power system dispatch with renewable energy generation has currently become a popular research direction. In our study, we propose a multi-objective dispatch model for a hybrid microgrid comprising a wind generator, photovoltaic (PV) generator, and an energy storage system to optimize the time-of-use (TOU) electricity price. The objective of the proposed multi-objective dispatch model is to maximize the profit of the power company and demand users, and minimize the proportion of users abandoning PV power and wind power. The elastic price of the load demand with a linear function is employed to optimize the TOU electricity price. Finally, we applied five test cases to validate the practicability of the multi-objective dispatch model.

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Sosnina, Elena N., Andrey V. Shalukho, and Natalya I. Erdili. "INCREASING THE EFFICIENCY OF RENEWABLE ENERGY SOURCES IN A VIRTUAL POWER PLANT BASED ON MULTI-AGENT CONTROL." Vestnik Chuvashskogo universiteta, no. 3 (September 29, 2022): 103–13. http://dx.doi.org/10.47026/1810-1909-2022-3-103-113.

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The article is devoted to the problem of increasing the efficiency of renewable energy sources (RES). The development of distributed energy based on renewable energy sources is one of the most important areas for ensuring the energy security of consumers and reducing the anthropogenic load on the environment. Combining distributed sources of electricity into virtual power plants (VPP) with a general control system makes it possible to use the potential of renewable energy sources more efficiently. An approach to the management of energy exchange in a virtual power plant (VPP) based on a multi-agent system (MAS) is proposed and substantiated, taking into account the criterion of environmental friendliness of distributed generation (DG) installations and ensuring the efficient use of environmentally friendly renewable energy sources. Algorithms for the operation of generation and load agents have been developed to control energy exchange in a virtual power plant based on a multi-agent system. The algorithms differ in taking into account the environmental friendliness rating of distributed generation installations and allow you to maximize the renewable energy sources potential, ensuring the balance of electrical power in the virtual power plant and minimal losses during its transmission. A 20 kV virtual power plant is considered, combining 10 decentralized power supply systems (DPSS) with sources of distributed generation of various types and having the ability to exchange electricity with a centralized power system (CES). With the help of software complexes JADE and “RastrWin”, a study of the effectiveness of the method for controlling energy exchange in virtual power plant based on multi-agent system was carried out, taking into account the environmental rating of distributed generation installations. The results of the research showed that the use of a multi-agent approach to control the virtual power plant made it possible to increase the share of the use of renewable energy sources and reduce power losses in the electrical network.

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Mou, Min, Yuhao Zhou, Wenguang Zheng, and Yurong Xie. "Integration and Modeling of Multi-Energy Network Based on Energy Hub." Complexity 2022 (September 5, 2022): 1–11. http://dx.doi.org/10.1155/2022/2698226.

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The energy conversion units and energy storage equipment connected to the multi-energy system are becoming diversified, and the uncertain factors brought by distributed wind power and photovoltaic power generation make the system energy flow structure more complex, which brings great difficulties to the modeling and application of traditional energy hub modeling methods. This study deeply analyzes the multi-energy flow coupling structure and operation mechanism of multi-energy systems, and carries out the power flow calculation and analysis of multi-energy systems based on an energy hub, so as to ensure the safe and stable operation of regional energy. Based on the physical characteristics of energy systems such as power systems, thermal systems, and gas systems, this article studies the comprehensive power flow model including the electric-gas-thermal multi-energy coupling network and proposes the power flow decomposition of the energy supply subsystem and its applicable equation based on Newton–Raphson method. The effectiveness of the proposed method under different operation modes is verified by case studies. The calculation results show that under constant load, the energy hub running in fixing thermal by electricity (FEL) and fixing electricity by thermal (FTL) mode has little influence on the voltage of each node in the power sub-network. Within the constraint range, the natural gas flow obtained from the natural gas subsystem is coupled with the power subsystem to meet the load demand. The influence on the power flow at each node of the heat network is not obvious.

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Yu, Changle, Lin Yang, Penglong Qi, Jia Wan, Yuanda Zhu, and Qingqing Zhang. "Research on dynamic energy optimization strategy of park smart energy system with complementary multi-energy." Journal of Physics: Conference Series 2401, no. 1 (December 1, 2022): 012008. http://dx.doi.org/10.1088/1742-6596/2401/1/012008.

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Abstract The only way to develop a smart grid is to build a smart energy system in the park with coordinated optimization of source, network and load, and flexible interaction. In order to achieve the best operation of the multi-energy complementation of cooling, heating, and electricity in the smart energy system of the park when the output of renewable energy is uncertain, the Latin hyper square sampling method and the synchronous back generation method are used to analyze and model the uncertainty of renewable energy in the system. A model for the optimal operation of the integrated energy system for cooling, heating, and electricity is established. This model considers various demand response measures of controllable load and electric energy storage and considers how source, load, and storage can work together to reduce energy consumption. After conducting a multi-scenario simulation study, it is determined that this approach may significantly boost the park’s operational dependability and economic performance.

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Stevens, Gary, Juliana Early, Geoff Cunningham, Martin Murtagh, Roy Douglas, and Robert Best. "Multi-fidelity validation algorithm for next generation hybrid-electric vehicle system design." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 13 (January 25, 2019): 3438–48. http://dx.doi.org/10.1177/0954407018825015.

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With the evolution of increasingly complex hybrid-electric vehicle powertrains, the process of creating validated system models has become progressively more difficult to achieve. Increasing levels of confidence in how instantaneous vehicle energy states are captured is needed to take full advantage of the fuel consumption and emissions reduction potential of the vehicle to move towards more sustainable transportation systems. While many strategies for model validation exist, the majority rely on ascertaining comparisons with global system characteristics, for instance, total fuel consumption over a fixed driving event. However, these methods do not necessarily account for the rapidly fluctuating energy states which need to be understood to optimise the vehicle’s energy management strategy. The current work proposes a new validation approach which captures these instantaneous characteristics taking advantage of the high signal sampling rates available from modern data acquisition equipment rather than relying on drive cycle average or cumulative global behaviours. The method proposed provides a holistic view of the behaviours demonstrated by the vehicle model and identifies regions of poor system validation targeting areas for further model refinement. The algorithm is demonstrated on a new post-transmission, parallel mild-hybrid-electric bus. The model was developed in the MATLAB Simulink modelling environment. The validation algorithm is tested against vehicle dynamometer and test track data. With an increasing volume of mild and full hybrid vehicle configurations emerging, validation strategies such as the one proposed here are increasingly important for the design of energy management strategies to deliver the full potential benefits of the vehicle. The algorithm is proposed in a step by step method which can be automated to limit required user input.

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Fang, Hong Wei, Jia Jia Cheng, Qi Wei Yang, and Jing Lian. "Multi-Frequency Proportional-Resonant Control for Wave Power Generation System." Advanced Materials Research 760-762 (September 2013): 1139–43. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1139.

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A grid voltage vector oriented proportional resonant (PR) control strategy is applied to the grid current control of the float-type wave power generation system. Compared with the conventional double closed-loop proportional integral (PI) control method, the proposed multi-frequency PR control method can realize zero steady-state error in AC input signal in the stationary frame, without complex coordinate rotation transformation and decoupling control. The overall wave power generation system model is built with Matlab/Simulink to evaluate the performance of the PR control method. Simulation results have shown that the PR control can well improve the robustness and the power quality of the float-type wave energy conversion control system.

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Dr. S. Jeyanthi, Shilaja C,. "MULTI-OBJECTIVE OPTIMIZATION FOR OPTIMAL HYBRID RENEWABLE ENERGY SOURCE SELECTION IN HYBRID RENEWABLE ENERGY SYSTEMS." Psychology and Education Journal 58, no. 1 (January 15, 2021): 4283–88. http://dx.doi.org/10.17762/pae.v58i1.1496.

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Power generation is more important to fulfill power demand throughout the world. Population and their electric power demand are increasing day by day. Achieve the energy demand from end-users, and recent research works have concentrated on designing a hybrid energy system. This paper proposed a multi-objective optimized model of a hybrid renewable energy system for a grid. The optimal model can choose a suitable design model of solar, wind, diesel, and batteries interconnected in the hybrid energy system. Optimization is applied for minimizing the system cost, fuel cost and diminish the fuel emission. It also aimed to improve the reliability of renewable sources. Initially, the problem is defined as a multi-objective problem and solved by a multi-objective evolutionary algorithm. From the simulation results, it is identified that the proposed multi-objective evolutionary algorithm performs better.

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Fan, Wen, Qing Liu, and Mingyu Wang. "Bi-Level Multi-Objective Optimization Scheduling for Regional Integrated Energy Systems Based on Quantum Evolutionary Algorithm." Energies 14, no. 16 (August 4, 2021): 4740. http://dx.doi.org/10.3390/en14164740.

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Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and builds an integrated energy system model. Two evaluation indexes are proposed: the integrated energy self-sufficiency rate and the expected energy deficiency index. Based on these evaluation indexes and taking into account the uncertainty of wind power generation, a bi-level optimization model based on meta-heuristic algorithms and multi-objective programming is established to solve the problem of regional integrated energy system planning under different load structures and for multi-period and multi-scenario operation modes. A quantum evolutionary algorithm is combined with genetic algorithms to solve the problem.

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Journal articles on the topic 'Multi-generation energy system'

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