Energy System Configuration Research Articles

Environmental impacts of optimal designs of community energy systems under different CO2 footprints of electric grids

This work determines optimal energy system configurations that minimize CO2 emissions under three typical grid electricity generation sources: (a) mostly nuclear and hydro; (b) natural gas; (c) coal. Benefits of implementing ground source heat pump (GSHP) and air source heat pump (ASHP) are compared to using combined cooling-heating-power (CCHP) system considering meeting cooling, heating, and electricity demands of consumers. GSHP is modeled via a novel multilayer model of borehole field heat transfer. Results from case studies show that for regions using mainly renewable energy technologies, configuration anchored on GSHP + ASHP has the lowest emissions, while configurations anchored on ASHP or ASHP + CCHP emit 5% more. When electricity is generated from natural gas or coal, relative to the configuration with the lowest emissions (all equipment), configurations anchored on GSHP + CCHP emits 1% and 2% more, while configurations anchored on ASHP + CCHP emit 3% and 19% more, respectively.

Techno-economic investigation of a hybrid biomass renewable energy system to achieve the goals of SDG-17 in deprived areas of Iran

Improving the quality of life in deprived areas is one of the main programs of the United Nations, highlighting the significance of a clean and reliable power supply for sustainable development. This study focuses on the configuration of hybrid renewable energy systems (HRES) in Iran's northern and southern rural areas, utilizing a combination of wind turbines, storage banks, photovoltaic panels, biogas, and diesel generators. These regions possess animal- and agriculture-based biomass resources that can effectively meet their primary residential energy needs. This study highlights the importance of employing multi-criteria decision-making (MCDM) for selecting suitable hybrid renewable energy systems (HRES) in rural areas. By incorporating a novel objective weighting process based on the SDG-17 framework, the study considers a range of criteria, including economic, environmental, energy security, and technical factors. Furthermore, the validation of HOMER's accuracy in sizing renewable energy systems with particle swarm optimization (PSO) has demonstrated the significant capability of the primary model. The results demonstrate that relying solely on economically optimal scenarios may not align with CO2 emissions, energy efficiency, and reliability goals. Utilizing the HOMER-MCDM method, the study achieves a more optimal combination of energy systems, considering multiple aspects of sustainable development beyond economic efficiency. For the climates of northern and southern rural regions of Iran, the study identifies the PV/WT/Bio/battery system as the best solution, with levelized costs of electricity (COE) of 0.251 and 0.219 $/kWh, respectively. This configuration relies entirely on local resources, emits nearly zero emissions, and provides power to the communities. Additionally, a sensitivity analysis assesses the impact of changes in capital costs of power generation components and the potential of renewable resources. Adjusting the investment costs of PV and WT systems between 0.7 and 1.3 times their original values results in a COE range of 0.198 to 0.233 $/kWh, representing a decrease of 9.2% and an increase of 6.9% compared to the initial operation, respectively.

A comprehensive multi-node multi-vector multi-sector modelling framework to investigate integrated energy systems and assess decarbonisation needs

The pathway towards decarbonised energy systems involves massive changes in adopted energy vectors, installed technologies, networks roles, and interaction capabilities. To investigate the combination of these effects, this work presents the OMNI-ES modelling framework (Optimisation Model for Network-Integrated Energy Systems), which offers a comprehensive approach to analyse multi-node, multi-vector, multi-sector energy systems. It adopts a detailed temporal and spatial resolution and implements multiple conversion options between energy vectors (electricity, hydrogen, natural gas, biomethane, biofuels, e-fuels, …). The formulation solves the energy vector balances at each time step, taking into account sources, sinks, conversion processes, and storage systems. CO2 flows are also tracked, allowing the introduction of CO2 emission constraints that account for all contributions (fossil and biogenic, direct and indirect) and mitigation measures (capture, re-use, sequestration). In the article, OMNI-ES is applied to investigate an Italian scenario for 2050, adopting a regional (NUTS-2) resolution. The model output yields the cost-optimal energy system configuration that is capable to support the demand with net-zero CO2 emissions. Results show that the need for CO2 balance closure calls in several technologies, including massive renewable power generation (up to 20 times today’s capacities), storage systems (batteries, hydrogen, pumped hydro), biogenic sources (residual biomass and biomethane), and CO2 capture (both on fossil and biogenic sources). Networks emerge as critical elements, as the need to transport energy vectors saturates the expected capacities of grid infrastructures, especially in the case of hydrogen.

Optimal configuration of a large scale on-grid renewable energy systems with different design strategies

Several oil-importing countries tend to utilize renewables as alternatives to traditional energy sources. This is to replace conventional fossil fuel plants with clean, economical, and reliable energy resources. In this paper, all possible on-grid renewable energy systems with different design scenarios are investigated to satisfy the load demand of Al-Mastaba city, Jordan. These grid-connected cases include solar photovoltaic (PV) only, wind only, hybrid PV/wind, PV/pumped hydro storage (PHS), wind/PHS, and hybrid PV/wind/PHS systems. In each scenario, the optimal sizing and energy management strategy are achieved using flow direction optimization algorithm. This is done by minimizing the grid usage factor (GUF). The decision variables include the number of PV panels, the number of wind turbines, and/or the height of upper reservoir (UR) of the PHS facility (hhydro). The input hourly measured data for systems' components were brought from formal institutions to get realistic and future real-life recommendations. Results showed that hybrid PV/wind/PHS (Scenario 6) has the best design. It has the lowest GUF of 0.59%. It comprises of 12,692 solar panels, 28 wind turbines, and 106.98m as hhydro of the UR. The uncertainty analysis on input measured data is implemented to test the system's robustness. It is noticed that the 6th scenario released an amount of CO2 of 122.29 t/year and the corresponding renewable storage factor is 63.72% with 0.042 $/kWh as the lowest value of levelized cost of energy. The methodology of this paper is highly recommended anywhere to reduce grid purchases and make it dispensable by adopting renewable retrofitting systems.

Capacity optimal configuration and collaborative planning of multi-region integrated energy system

At present, the integrated energy system (IES) is designed and built separately according to the peak load of respective regions, without considering the combination of multi-regional energy, which will lead to low energy efficiency of equipment and decline of economic benefits. In this paper, considering heating networks, a multi-region IES collaborative planning model is proposed. For the ring-shaped heating network between the various regional CCHP systems, a heating network model is established considering the node flow balance, thermal energy-flow constraint and thermal loss balance constraint. Combining the energy balance constraint of the CCHP system and the heating network model, a mixed integer linear programming (MILP) model of the capacity of the multi-region CCHP system for the collaborative optimization is established. Finally, a comprehensive area in China Xiongan New Area is taken as an example for simulation analysis. In view of the four types of users, including business area, office area, residential area, industrial area, the two scenarios are deeply compared and analyzed. The saving rate of scenario 2 compared with scenario 1 is about 8.95%. The multi-region collaborative planning and optimize operation in this paper can greatly improve gas turbine utilization, reduce gas boiler configuration capacity, minimize thermal energy transmission loss, and significantly reduce operating costs.

Energy-economic assessment of self-sufficient microgrid based on wind turbine, photovoltaic field, wood gasifier, battery, and hydrogen energy storage

Designing self-sufficient renewable energy systems is becoming a key issue in the energy sector due to modern energy goals. Due to the variability of renewable energy sources, very often it is necessary to adopt hybrid configurations of renewable energy systems and advanced energy storage to achieve self-sufficiency. However, the adoption of complex and novel systems, including technologies as photovoltaic, wind turbines, biomass gasifiers, hydrogen energy storage, must to be founded on a comprehensive analysis of the system operation under different conditions and its energy and economic performance in the investigated case study. Therefore, the aim of the present paper is carry out a comprehensive feasibility analysis of a novel hybrid renewable energy system achieving a high self-sufficiency level. The system integrates a wind turbine and photovoltaic panels to match the energy load of a tourist resort in Agkistro, Greece. Energy exceeding the load is directed to the energy storage system based on the battery and hydrogen tank. As backup energy source, a wood gasifier is used.The investigation is performed by means of a numerical model developed in TRNSYS software allowing one to simulate dynamically the system and to assess its energy and economic performance. The goal achieved during the simulation of the system was to ensure at least 97% of energy demand from renewable sources. Moreover, a parametric analysis of the storage system is presented. It is found that payback period of the installation varies in the range between 11 and 15 years, for systems configurations allowing to satisfy 90–98% of the users energy yearly demand from renewables. The achieved results allows one to evaluate the feasibility of the proposed system from both an energy and economic point of view.

Novel design, implementation, and performance optimization of inverters by considering the effect of modulation

This research seeks to combine a comprehensive analysis of the literature regarding energy efficiency and inverters with an analysis of a configuration of a hybrid energy system including a generator, an inverter and a battery. The inverter's power output is analyzed under the influence of different distribution functions during a robust modulation procedure for achieving optimum energy saving. The modulation is tested on two processing machines independently: (a) an electric discharge machine, and (b) an injection molding machine. Based on the research methodology, problem formulations and the conducted analysis, a novel research software called “Inverter Pro V1” was programmed to analyze the estimations and performance of inverters in an energy system. An optimal levelized cost of electricity was determined given certain systems design and operating hours, and a sensitivity analysis was undertaken that identified a range of energy savings. In the sensitivity and optimization analysis, interactions among the primary decision parameters including the system's capacity, operating time, energy saving, cost of energy and payback period are investigated. It is also found that for each system, the inverter modulation categories with the optimum payback period belong to a modulation of inverter designed according to the Sawtooth function with a 45% duty cycle and switching intervals of 0.35 s. By considering the operating hours of 12.5 h per day, and the calculated system's investment cost of €31,782.158, the optimum payback period is estimated to be 1.7729 year. The study results are to inform policy with regard to assisting sustainable electricity production.

Research on energy management of integrated energy system coupled with organic Rankine cycle and power to gas

Integrated energy system could offer multiple products, such as heat and power. However, the supplied energy and thermoelectrical ratio may not conform with the demand and or thermoelectrical ratio of end user. In order to solve the energy mismatch between source side and load side an integrated energy system coupled with organic Rankine cycle and power to gas was constructed, and energy management strategies based on organic Rankine cycle and power to gas were proposed. Considering the economic, energy and environmental performance of the system, the evaluation index and multi-objective optimization model were constructed, respectively. Then, a case study of an industrial park including factory, dormitory and commercial buildings was employed and the hourly heating, electrical and gas loads were simulated. Finally, the capacity configuration optimization, system performance of integrated energy system under four strategies: without organic Rankine cycle and power to gas, with power to gas, with organic Rankine cycle and with organic Rankine cycle and power to gas were compared. Simultaneously, the suitable integrated energy system configuration between different thermoelectrical ratio range of end user was analyzed. Results showed that when organic Rankine cycle and power to gas were added to integrated energy system, the output range of thermoelectrical ratio could be widened. When thermoelectrical ratio was less than 0.42, the comprehensive performance of integrated energy system coupled with organic Rankine cycle was the best. When thermoelectrical ratio was greater than 3.89, the comprehensive performance of integrated energy system coupled with power to gas was the best. Integrated energy system coupled with organic Rankine cycle and power to gas presented better performances if the thermoelectrical ratio was between 0.43 and 3.21.

Optimal Design of Biomass-centered Integrated Energy System under Uncertainty

To achieve the goal of carbon peak and carbon neutrality, China is actively promoting the production and consumption of clean and sustainable energy such as biomass. The optimization of integrated energy system (IES) configuration including biomass has gradually become a research hotspot. In this paper, aiming at the configuration optimization problem of biomass-centered IES under uncertainty, considering the uncertainty of user load and energy price, the maximum annual profit is selected as the objective function, and the configuration planning model of IES under uncertainty is established. Then, the artificial bee colony (ABC) algorithm is used to solve the optimization model, and the influence of uncertainty factors on the configuration optimization of IES is explored. The results of the example show that with the two-stage stochastic programming model used to deal with the uncertainty factors in the IES, the equipment configuration capacity and operating parameters in the system are changed compared with the results of the deterministic conditions. It can overcome the problem of over-optimism in the deterministic condition and reduce the system operation risk due to the random variation of uncertainty factors.

Innovative hybridization of the two-archive and PROMETHEE-II triple-objective and multi-criterion decision making for optimum configuration of the hybrid renewable energy system

Photovoltaic (PV) and Wind turbine (WT) systems are the most promising options for rural energy delivery. In the literature, numerous studies have simply considered only on economic efficiency, while maximizing dependability by a constant value for the given demand load. Moreover, a single set Pareto optimal front (PF) has been attained for the multi-objective optimization problem. Furthermore, the primary challenge of various the off-grid multiple renewable energy sources is excessive energy loss, resulting over/under sizing and a highly total cost for the system. Therefore, this paper presents a unique improved bi-archive approach to develop the diversity and convergence independently in order to find four optimum sets of PF solutions. In addition, a new integration based on best worst method (BWM) and preference ranking organization for enrichment evaluations (PROMETHEE II) method along with group decision making (GDM) mechanism are addressed to sort and rank the optimal sets PF solutions with full consistency ratios of the three experts opinions and high degree of stability in ranking configurations. The theoretical results based on actual hourly meteorological data in Malaysia and South Africa indicated that the suggested improved two-archive-BWM- PROMETHEE II-GDM method is not only able to construct a uniform set of Pareto optimal solutions with fast convergence and high diversity, but can also rank and select the most desired design for the PV/WT/Battery system. The optimum configurations of the two cases studies are composed of a single WT, 105 PV modules, and 69 batteries storages at zero LLP, 60185 ($) of LLC, and 13548018 (KWh) of Pdump for Malaysia case study, meanwhile it composes of 16 WTs, 80 PV modules, and 69 batteries storage at zero of LLP, 66073 ($) of LCC, and 31371 (KWh) of Pdump. The proposed standalone hybrid renewable energy sources system is verified and assessed in a comparison with existing hybrid methods in terms of increasing the reliability, lowering overall cost, and reducing wasted energy.

Techno-Economic Evaluation of Hydrogen-Based Cooking Solutions in Remote African Communities—The Case of Kenya

Hydrogen has recently been proposed as a versatile energy carrier to contribute to archiving universal access to clean cooking. In hard-to-reach rural settings, decentralized produced hydrogen may be utilized (i) as a clean fuel via direct combustion in pure gaseous form or blended with Liquid Petroleum Gas (LPG), or (ii) via power-to-hydrogen-to-power (P2H2P) to serve electric cooking (e-cooking) appliances. Here, we present the first techno-economic evaluation of hydrogen-based cooking solutions. We apply mathematical optimization via energy system modeling to assess the minimal cost configuration of each respective energy system on technical and economic measures under present and future parameters. We further compare the potential costs of cooking for the end user with the costs of cooking with traditional fuels. Today, P2H2P-based e-cooking and production of hydrogen for utilization via combustion integrated into the electricity supply system have almost equal energy system costs to simultaneously satisfy the cooking and electricity needs of the isolated rural Kenyan village studied. P2H2P-based e-cooking might become advantageous in the near future when improving the energy efficiency of e-cooking appliances. The economic efficiency of producing hydrogen for utilization by end users via combustion benefits from integrating the water electrolysis into the electricity supply system. More efficient and cheaper hydrogen technologies expected by 2050 may improve the economic performance of integrated hydrogen production and utilization via combustion to be competitive with P2H2P-based e-cooking. The monthly costs of cooking per household may be lower than the traditional use of firewood and charcoal even today when applying the current life-line tariff for the electricity consumed or utilizing hydrogen via combustion. Driven by likely future technological improvements and the expected increase in traditional and fossil fuel prices, any hydrogen-based cooking pathway may be cheaper for end users than using charcoal and firewood by 2030, and LPG by 2040. The results suggest that providing clean cooking in rural villages could economically and environmentally benefit from utilizing hydrogen. However, facing the complexity of clean cooking projects, we emphasize the importance of embedding the results of our techno-economic analysis in holistic energy delivery models. We propose useful starting points for future aspects to be investigated in the discussion section, including business and financing models.

Shared Energy Storage Configuration Optimization Method of Regional Energy System Based on Electric and Thermal Demand Response

In the new energy power system, the main applications of energy storage technology include power peak shaving, suppressing the fluctuation of transmission power, improving the stability of power system operation, and improving the power quality. The energy storage device can timely absorb or release power, effectively reduce the transmission network loss of the system, realize peak shaving and valley filling, and obtain economic benefits. Therefore, the significance of energy storage technology is very important. The use of all kinds of energy cannot be separated from the support of energy storage technology, but the traditional energy storage technology fails to optimize the configuration, resulting in low overall energy storage efficiency. Due to the low response degree of the traditional shared energy storage configuration method of the regional energy systems and the waste of resources caused by the large energy consumption of energy storage devices, the shared energy storage configuration optimization method of the regional energy systems based on electric and thermal demand response is researched. The electric heating demand response model is established to store heat and electricity, and the energy is reasonably utilized to meet the electric heating demand response. The distributed photovoltaic regional energy model is established to control the equipment and reduce the active and reactive power loss, and the cloud shared energy storage is used to optimize the configuration and reduce the cost to complete the optimization of the shared energy storage configuration of the regional energy system responding to the electric heating demand. The experimental results indicate that the proposed method has the highest energy storage capacity saving rate, realizes the efficient conversion of energy resources, reduces energy waste, and realizes the effective optimization of shared energy storage configuration in the regional energy systems.

Configuration Planning of Expressway Self-Consistent Energy System Based on Multi-Objective Chance-Constrained Programming

Regarding the problem of the optimal configuration of self-consistent energy systems based on a 100% renewable energy supply for expressway electricity demand in no-grid areas, this paper proposes a multi-objective planning model based on chance-constrained programming (CCP) to achieve the optimization objectives of low cost and high reliability. Firstly, the number of units of different types of wind turbines (WT), the capacity of photovoltaic (PV) cells, and the number of sets of energy storage systems (ESS) are selected for the design variables in our configuration plan. After defining the load grading shedding and ESS scheduling strategy, the Monte Carlo Simulation (MCS) method and the backward reduction method are applied to model the uncertainties of electric load and renewable energy sources. Finally, the set of Pareto solutions are optimized by the non-dominated sorted genetic algorithm-II (NSGA-II) and its unique best solution is determined by the Criteria Importance Though Intercriteria Correlation (CRITIC) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. Making use of the wind speed and solar radiation intensity historical data of an area in northwest China in the last five years, eight case studies of two typical scenarios are designed and carried out to explore in-depth the impact of different confidence levels and load fluctuation ranges on the planning results. The results verify that the proposed method can effectively improve the robustness of the system and satisfy the power demand in confidence scenarios.

Bioenergy generation from thermochemical conversion of lignocellulosic biomass-based integrated renewable energy systems

Anthropogenic activities and advancements in industries boost global energy demand and increase fossil fuel consumption, causing several global environmental problems, such as climate change. As a climate change mitigation strategy, the use of renewable energy technologies has gained unprecedented interest. In particular, the thermochemical processing of lignocellulosic biomass integrated with other renewable energy technologies has emerged rapidly. It is critical to select appropriate integrated renewable energy system configurations for sustainable and feasible power generation towards higher environmental benefits. Understanding the possible configurations of thermochemical lignocellulosic biomass processing technologies (gasification, pyrolysis, hydrothermal gasification, or hydrothermal carbonization) integrated with renewable energy technologies (solar thermal, fuel cell, fusion power, or energy storage) is crucial for the further development and propagation of the integrated renewable energy system. Hence, we provide a systematic review of the thermochemical conversion of lignocellulosic biomass integrated with the other renewable energy technologies. Finally, the challenges associated with the implementation of these systems and suggestions for future research on the systems are discussed.

Techno-Economic Analysis and Multi-Objective Optimization of Cross-Flow Wind Turbines for Smart Building Energy Systems.

This work reports a technical, economic, and environmental investigation of the possibility of using a recently developed smallscale crossflow wind turbine (CFWT) to supply the energy demand of buildings for different integration scenarios. For this purpose, three CFWT-assisted building energy system configurations with heat pumps, with and without batteries, and two-way interaction with the local grid in two residential building models in Iran and Germany are investigated. Triobjective optimization with a Nondominated Sorting Genetic Algorithm (NSGA-II) is performed for finding the optimal configuration of the energy system in different configurations. For economic assessment, the Capital Budgeting Analysis method is used with four indicators, namely, payback period (PP), net present value (NPV), internal rate of return (IRR), and profitability index (PI). The results show that due to different energy market regulations and prices, different integration scenarios and system configurations can outperform others in Germany and Iran. Overall, due to the exchange rate instability and low energy tariff in Iran, in order for the project to be feasible, either the CFWT cost must fall to below 30% of its current cost or the local electricity price should increase significantly to get a Levelized cost of energy of as low as 0.6 $ kWh-1.

Optimal Configuration and Scheduling Model of a Multi-Park Integrated Energy System Based on Sustainable Development

To maximize the utilization of renewable energy (RE) as much as possible in cold areas while reducing traditional energy use and carbon dioxide emissions, a three-layer configuration optimization and scheduling model considering a multi-park integrated energy system (MPIES), a shared energy storage power station (SESPS), and a hydrogen refueling station (HRS) cooperation based on the Wasserstein generative adversarial networks, the simultaneous backward reduction technique, and the Quantity-Contour (WGAN-SBR_QC) method is proposed. Firstly, the WGAN-SBR_QC method is used to generate typical scenarios of RE output. Secondly, a three-layer configuration and schedule optimization model is constructed using MPIES, SESPS, and HRS. Finally, the model’s validity is investigated by selecting a multi-park in Eastern Mongolia. The results show that: (1) the typical scenario of RE output improved the overall robustness of the system. (2) The profits of the MPIES and HRS increased by 1.84% and 52.68%, respectively, and the SESPS profit increased considerably. (3) The proposed approach increased RE utilization to 99.47% while reducing carbon emissions by 32.67%. Thus, this model is a reference for complex energy system configuration and scheduling, as well as a means of encouraging RE use.

Green carbon science: fundamental aspects.

Carbon energy has contributed to the creation of human civilization, and it can be considered that the configuration of the carbon energy system is one of the important laws that govern the operation of everything in the universe. The core of the carbon energy system is the opposition and unity of two aspects: oxidation and reduction. The operation of oxidation and reduction is based on the ternary elemental system composed of the three elements of carbon, hydrogen and oxygen. Its operation produces numerous reactions and reaction products. Ancient Chinese philosophy helps us to understand in depth the essence of green carbon science, to explore its scientific basis, and to identify the related platforms for technology development.

Research on Highway Self-Consistent Energy System Planning with Uncertain Wind and Photovoltaic Power Output

Highways are a critical consumer of energy. The integration of the highway and the energy system (ES) is a proven method towards carbon neutrality. The increasing energy demands of highway transportation infrastructure and the development of distributed energy and energy storage technologies drive the coupling between the highway system (HS) and the energy supply network, which is becoming tighter than ever before. Many scholars have explored the mode and path of integrated transportation and energy development. However, the energy and transportation systems’ coupling relationship and the collaborative planning scheme have not been thoroughly studied. Facing the increasing interconnection between transportation and energy networks, as well as addressing the demand for clean energy in highway transportation effectively, this paper proposes a highway self-consistent energy system (HSCES) planning model integrating uncertain wind and photovoltaic (PV) power output, so as to analyze the energy supply mode of the HS and determine the multi-energy capacity configuration of the self-consistent energy system (SCES). Firstly, the mathematical model related to each micro-generator of the SCES and the load aggregation scenario of the HS is established. Secondly, considering the uncertainty of renewable energy, this paper focuses on wind and PV power generation, and abatement technology, under uncertain conditions to ensure the best solution for reliability. Thirdly, taking the economy, reliability and the renewable energy utilization rate of the system into account, the system planning model is established under the condition of ensuring the system correlation constraints. Finally, the proposed method is validated using a section of the highway transportation system in western China. The results show that the hybrid energy storage planning scheme can cause the system’s renewable energy utilization rate to reach 99.61%, and the system’s power supply reliability to reach 99.74%. Therefore, it is necessary to carry out coordinated planning while considering the characteristics of the HS and the ES, which can minimize the planning cost of a HSCES, reduce the waste of wind and solar energy, and ensure the reliability of the power supply for the HS.

Design and multi-objective comprehensive evaluation analysis of PV-WT-BG-Battery hybrid renewable energy systems in urban communities

Determining the optimal configuration of hybrid renewable energy systems (HRESs) is the key to sustainable energy development. HRESs interface with multiple energy supply systems and need to simultaneously meet different time-varying loads. In this paper, 16 scenarios are formed from four resource conditions and four load types. All feasible HRES configurations for the 16 scenarios are simulated by using HOMER. Nine indexes are selected from three aspects (technology, economy and environment), and a comprehensive evaluation framework is established based on the Analytic Hierarchy Process. The optimal system in each scenario is selected and compared to assess the impact of resource and load conditions on system design. The results show that, in general, HRESs have a higher comprehensive index rating than single-source renewable energy systems, so HRESs should be considered as a better choice. And the optimal configuration of HRESs, including the size and type of generation devices and the size of energy storage device, is jointly determined by the conditions of energy resources and loads. The methodology presented in this paper can be an effective framework for designing and evaluating HRESs, and the obtained optimal systems can be valuable references for regions with similar resource and load conditions.

Optimal Configuration of Double Carbon Energy System Considering Climate Change

Optimal Configuration of Double Carbon Energy System Considering Climate Change