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Energy Management and Technology - Volume:8 Issue: 2, Spring 2024

Journal of Energy Management and Technology
Volume:8 Issue: 2, Spring 2024

  • تاریخ انتشار: 1403/03/12
  • تعداد عناوین: 6
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  • MohammadHadi Heidari, Hamdi Abdi *, Mohammad Moradi Pages 78-92

    The combined heat and power economic dispatch (CHPED) problem seeks to find the optimal point for power and heat generations to minimize the fuel cost considering the problem constraints. In this paper, the snake optimization (SO) algorithm is used to solve the CHPED problem, considering power losses. Two case studies including 5-, and 48-unit test systems have been simulated in MATLAB software. The simulation results of test case 1 verify that the SO reduces the minimum operation costs by at least 0.774%, 0.367%, 0.1437%, 0.143%, 0.1143%, and 0.0215%, compared to the best results of genetic algorithm (GA), harmony search (HS), classic particle swarm optimization (CPSO), imperialist competitive algorithm (ICA), group search optimizer (GSO), and imperialist competitive Harris hawks optimization (ICHHO) algorithms, for load profile 1. It also reduces the minimum operation costs by at least 1.705%, 1.361%, 0.1293%, 1.109%, 0.0957%, and 0.0756%, in compassion to GA, HS, CPSO, ICA, GSO, and ICHHO algorithms for load profile 2. Furthermore, for load profile 3, SO decreases the minimum operation costs by at least 0.5948%, 0.3716%, 0.122%, 0.1206%, and 0.0761% compared to GA, HS, CPSO, ICA, and GSO algorithms. In 48-unit test system, considering power losses, prohibited operating zones, and the valve point loading effect, the reduction of operating costs using the SO algorithm compared to CPSO, gravitational search algorithm (GSA), GA, hybrid time varying acceleration coefficients-GSA-PSO (TVAC-GSA-PSO), group search optimizer (GWO), society-based gray wolf Optimizer (SGWO), and ICHHO algorithms is 1.943%, 1.288%, 0.463%, 0.659%, 0.426%, and 0.197%, respectively.

    Keywords: combined heat, power economic dispatch, Combined Heat, Power Units, meta-heuristic algorithms, Snake Optimization, Power Losses
  • SEYEDSINA KHAMESI *, Hossein Yousefi, Behrouz Behnam Pages 93-103
    Hydronic networks transfer energy through the heating and cooling of the working fluid. The heat transfer depends on the temperature and flow rate of the fluid. Even small changes in the physical parameters of the transmission network, such as size, length, and cross-sectional area, can cause changes in the flow rate and transferred heat flux due to the non-linear equations governing the transmission of the working fluid. This research aims to investigate the possibility of balancing energy transmission networks and the cost reduction that results from this balance. The energy transmission network is modeled using the Hardy-Cross method, and the results are analyzed in the 50-year life cycle cost of the network. The research method used is a numerical analysis using the Newton-Raphson method to calculate the current of the energy transmission network through the numerical solution. The research presents a new model for designing industrial and residential energy transmission networks based on the density and layout of the network. The model can reduce energy consumption, air pollution production, and operating costs during the operation period of a complex. This research shows a 30% reduction in the operating costs of the energy transmission network in its balanced condition. The model presented in this research applies to other energy transmission networks and can be used to reduce energy consumption and operating costs.
    Keywords: life-cost-cycle, hydronic-network, flow-balance, Water, Energy
  • Samad Ranjbar Adrekani *, Ezatollah Asgharizadeh, Mohammadreza Sadeghimoghaddam, Mohammadreza Nikbakht Pages 104-113
    This article investigates the identification and prioritization of the components to implement environmental management accounting in manufacturing industries through two parts of qualitative and quantitative. In the qualitative part, the Meta-synthesis method was used to identify the components of environmental management accounting implementation. Hence, various keywords were initially searched in the most popular foreign and domestic databases, and 268 related research works were identified. Then, with the preliminary review of these studies based on certain indicators, 32 scientific and research works directly examining the components of environmental management accounting implementation were selected. Finally, using the coding technique, the related concepts were identified and categorized under the following seven components: Management factors, Resources, Environmental incentives and pressures, Environmental uncertainty, Laws and regulations, Competency of accountants, and Company structural characteristics. The quantitative part of the research included the statistical community, environmental experts, and researchers, 20 of whom were selected by purposive sampling. A paired comparison questionnaire, whose validity was confirmed by experts, was used to collect data. The data were analyzed using the Analytical Hierarchy Process (AHP) to prioritize the components of environmental management accounting implementation and the criteria related to each. The results of the quantitative part of the research demonstrated the component of management factors as the most significant with a relative weight of 0.283.
    Keywords: Analytical hierarchy process (AHP), Environmental Management Accounting, Manufacturing Industries, Metacomposite Analysis
  • Amirhossein Fathi *, Hossein Yousefi, Ali Ghayedhosseini, Masoumeh Bararzadeh Ledari, Mohammad Salehi, Parisa Hajialigol Pages 114-128
    This study investigates the planning and optimal operation of demand and supply systems in a renewable energy framework. The demand is categorized into cryptocurrency exploration, hydrogen production, and national power grid, while the supply consists of a national grid and a private solar power plant. The energy flow diagram considers feeding the cryptocurrency exploration and hydrogen production systems using both the national grid and solar power plant, and the solar power plant can also supply to the national grid. A linear optimization model is used to determine the optimal capacity of the solar power plant and demand planning to maximize investor profit while considering supply and demand limitations. The study includes 43803 decision-making variables and 26281 inequality constraints. The analysis focuses on the lifetime of system components, which aligns with the lifespan of renewable technologies. The system design considers variations in electrical energy consumption per bitcoin extraction, ranging from 70 MWh/BTC to 300 MWh/BTC, as well as changes in the price of Bitcoin, ranging from 5000 $/BTC to 55 k$/BTC. Additionally, the price of hydrogen ranges from 2 $/(kg_(H2 ) ) to 12 $/(kg_(H_2 ) ), and the price of electrolyzers ranges from 1250 $/(kW_Elect ) to 3000$/(kW_Elect ), over the study's 4356 scenarios. These scenarios encompass 31 unique states of supply and demand system design, along with optimal utilization of the supply system. The variability in energy exchange tariffs between the national grid and demand sectors accounts for the differences among the 26 distinct supply and demand system designs.
    Keywords: Linear optimization, energy systems, Cryptocurrency exploration, Hydrogen production, Investor profit
  • Saeid Zamanian, Mahdi Akhbari * Pages 129-140
    Zero-energy buildings (ZEBs) are a design option developed to meet the environmental benefits and long-term cost savings for both the governments and customers. However, geographical and climate situations like being remote, difficult crossing and renewable-suited have attracted the attentions to off-grid ZEBs. off-grid ZEB is an effective solution for the customers living in such regions, which denotes the concept of supplying building's demand from a standalone energy system independent of urban electricity infrastructure. Besides, envelope thermal insulating as the passive design plays a key role in the energy efficiency enhancement of buildings. This paper presents a bi-level optimization model of a risk-based off-grid ZEB planning in hot climate regions, which consists of sizing the standalone energy system and designing the required thermal insulation. The upper-level problem seeks to find the cost-optimal capacities of the energy resources and determine the insulation design parameters. The expected annual operation cost is extracted from the lower-level problem that is defined within a scheduling model and ensures the feasibility of the sizing problem in meeting the annual electric demand. The robust approach as the risk management tool is employed to mitigate the inherent uncertainty associated with the building demand. Furthermore, the bi-level problem is solved through a hybrid algorithm, composed of numerical metaheuristic and mathematical programming method. Moreover, an industrial campus in Kish Island is selected as the simulation case study to validate the proposed approach in creating an off-grid energy efficient system.
    Keywords: ZEB, off-grid, insulating, robust, passive design
  • Ali Aminlou *, Mohammadmohsen Hayati, Kazem Zare Pages 141-147
    Peer-to-peer (P2P) energy trading markets have emerged locally as a result of the higher usage of renewable energy sources in low-voltage networks. P2P energy trading systems have been increasingly popular in recent years, allowing consumers in residential and industrial types to trade electricity with each other. P2P energy trading has become feasible due to several developments in communication technology and the increased acceptance of renewable energy sources like solar and wind power. In this market, Consumers have been more interested in sharing their extra energy with others to get access to the new market and increase their profit. There are two approaches to P2P energy trading. The centralized approach involves a third-party entity, typically a network operator, that manages the trading platform. This approach offers a reliable option but may pose certain shortcomings such as limited privacy. In contrast, the decentralized approach empowers consumers to transact their surplus energy directly to one another, without requiring the intervention of a centralized authority. Such an approach endows participants with greater flexibility and preserves their privacy. This paper presents a fully decentralized approach for a local P2P energy trading market using the alternating direction method of multipliers (ADMM) algorithm. This paper also considers a compressed air energy storage (CAES) technology to increase flexibility and reduce peak demand. In the following, Numerical studies are carried out for a local community in a distribution network. Simulation results demonstrate how the P2P markets can facilitate the customers to manage their energy in the local community.
    Keywords: Peer to Peer, Energy Transaction, ADMM algorithm, Decentralized approach, CAES