Total Power Generation Research Articles

A Decentralized Voltage Regulation Scheme Using Improved Volt‐Var Function of PV Smart Inverter

With the growing distributed PV installation rate in distribution systems, voltage regulation difficulties such as local voltage violations and fluctuations have become common. To solve the voltage regulation problems, the local voltage regulation method using volt‐var (VV) function is effective for its high regulation speed, high accuracy, and flexibility. However, there are still hurdles on real application, such as parameter setting difficulties, insufficient voltage fluctuation mitigation effect, and unfairness of reactive power generation between PV customers. To further improve the VV function, this paper proposes a PID closed‐loop based VV function and mode‐switching function of PV smart inverter (SI). To validate the proposed methods, numerical simulations were conducted using a 6‐feeder distribution system model based on the JST‐CREST 126 distribution feeder model. According to the simulation result, the proposed method can better mitigate the local voltage violation compared to basic VV function based on the VV curve, also improve the fairness between PV customers, while the total reactive power generation and tap operations increases for the aim of more adequate voltage regulation. © 2024 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Development pathway and influencing factors of hydrogen energy storage accommodating renewable energy growth

Hydrogen energy is considered an important energy storage mode with medium- and long-term cross-seasonal storage capabilities in scenarios with high penetration of renewable energy (RE). However, there is a lack of research regarding the appropriate scale of hydrogen energy storage (HES) considering different RE power generation scenarios. In response to this gap, the present study aims to establish a power system simulation model to analyze the development pathway of HES while accommodating RE growth with a minimum cost constraint for a power system operation. The impacts of carbon trading prices, advances in HES technology, and RE resource endowment on HES development are also investigated. The findings indicate that the total available solar energy resources in China are 46.94TW, and the total available wind energy resources are 9.52TW. When the share of RE generation reaches 44.33–54.78 % of total power generation, the utilization of HES for balancing power system is advantageous in reducing the overall system costs. Looking ahead to 2060, the year when China is projected to achieve its carbon-neutrality goal, RE is estimated to reach 63.12–91.1 % of total power generation. Consequently, the HES in each province is estimated to contribute to 3.58–18.02 % of total electricity consumption. Provinces with more abundant wind resources relative to solar resources are expected to have a 36.43 % higher demand for HES.

Numerical Study of an Innovative Concept for a Multibody Anti-Pitching Semi-Submersible Floating Wind Turbine

The floating offshore wind turbine provides a feasible solution for the development of renewable ocean energy. However, the sizeable rotor diameter of the wind turbine results in large wind heeling moments and pitch amplitude. It will increase the structural loads and cause safety problems. Additionally, the contradictory nature between the stability and the sea-keeping of the floating structure requires that the more flexible method should be adopted to reduce the motion response of the floating offshore wind turbine. Therefore, an innovative concept of a multibody anti-pitching semi-submersible floating offshore wind turbine, named the MBAPSF, is proposed in this paper. The MBAPSF consists of a 5 MW braceless semi-submersible wind turbine and three wave energy converters. The multibody coupled numerical model is established by using an F2A tool, and the dynamic performance of the MBAPSF is compared with that of the traditional semi-submersible wind turbine named the TSSF. The results show that the innovative concept proposed in this paper can reduce pitch motion up to approximately 27% under different load cases, and the maximum bending moment and shearing force at the tower base are also reduced by more than 10%. Meanwhile, WECs are beneficial for increases in the total power generation capacity.

Thermoeconomic analysis of a novel cogeneration system for cascade recovery of waste heat from exhaust flue gases

In low-grade waste heat recovery scenarios, an absorption refrigeration cycle (ARC) or organic Rankine cycle (ORC) can be used because of its widespread acceptance in combined cooling and power applications. This paper introduces a cogeneration configuration employing a cascade waste-heat recovery architecture (including an ARC, ORC, and intermediate heating loop) to harness waste heat from the flue gas of a gas turbine (GT). The results demonstrated that the first-law efficiency and total power generation were largely influenced by the ARC, whereas the second-law efficiency and total available energy were primarily affected by the ORC. When the ARC generation temperature difference and ORC evaporation temperature were adjusted, the first- and second-law efficiencies exhibited divergent trends, suggesting the absence of a unified strategy to enhance both efficiencies simultaneously in the current system. The system achieved its highest first-law efficiency of 54.84 % and maximum total power generation of 1866.10 kW at an ORC evaporation temperature of 145 °C and a heat-source inlet temperature of 160 °C. Furthermore, at an ORC evaporation temperature of 150 °C and a heat-source inlet temperature of 200 °C, the system reached its highest second-law efficiency of 34.57 % and maximum total available energy of 1233.3 kW. The case study revealed that the GT system (including air compressor, air preheater, combustion chamber, and gas turbine) accounted for the highest level of irreversibility, comprising 74 % of the overall system. Specifically, the combustion chamber in the GT system produced a significant irreversibility due to chemical reactions. Compared with traditional combined cooling and power systems, the proposed system can increase the first-law efficiency and lower the unit energy cost of the output.

Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms

Wind energy plays a crucial role in the quest for sustainable energy solutions. However, optimizing the efficiency of wind energy utilization remains a significant challenge. Wake steering, a key strategy in the field, offers the potential to address this challenge. This study introduces an innovative site-specific wake steering framework that incorporates a wake superposition model for wake steering, a machine-learning based fatigue and power predictor and a multi-objective optimizer to both enhance total power generation and mitigate fatigue loads within wind farms. The wake superposition model, developed and validated here, successfully replicates secondary wake steering effects and provides a new solution for calculating superimposed transverse velocity. The study comprehensively considers and implements constraints based on physical laws. Analysis of inflow speed and turbulence levels reveals that wake steering can continue to enhance total power output. Power enhancement can reach up to 18% at lower turbulence levels and still achieve significant increases even when inflow speeds exceed rated values, with only marginal increases in fatigue loads. Lower turbulence levels improve optimization results at the expense of heightened structural loads, while higher turbulence levels lead to diminishing power enhancement and additional fatigue loads. Examination of wind turbine spacing shows that smaller intervals yield substantial power enhancement, with improvements of up to 51.7%, although the effect diminishes as intervals increase and wake recovery takes place. In conclusion, the proposed site-specific wake steering framework offers an efficient means of balancing enhanced wind farm power output and structural integrity, representing a significant advancement in wind energy optimization.

An integrated alkali metal thermoelectric converter with sodium hydroxide thermoelectric water splitter and organic Rankine cycle for efficient power and hydrogen production

This study proposes the integration of the NaOH thermochemical water splitting cycle with both an alkali metal thermoelectric converter and an organic Rankine cycle. The objective of the proposed model is to enhance the overall efficiency by utilizing the waste heat generated by the NaOH thermochemical water splitting process and redirecting the heat from the alkali metal thermoelectric converter using bypass when hydrogen demand is low.Performance parameters such as system efficiency, system power, hydrogen production, AMTEC power production, and ORC power production were examined in the study. The results indicated an increase in power and hydrogen production with higher hot-end temperatures, along with an overall reduction in system efficiency for low values of load resistance. The system achieved a maximum efficiency of 53.37%.The system efficiency reached its peak at an AMTEC hot end temperature of 1173 °C, achieving 53.37 % efficiency at an RL value of 1.01 O. When the system operates at its maximum AMTEC power production, the AMTEC modules supply 12.81 kW, while the ORC generates 5.57 kW, and the hydrogen compressor consumes 0.13 kW. The total electrical power generation is 18.38 kW. The findings also indicate that the utilization of the bypass led to a reduction in hydrogen production while increasing the power output of the organic Rankine cycle.

Distributed Cooperative Control Strategy for Stable Voltage Restoration and Optimal Power Sharing in Islanded DC Microgrids

Conventionally, voltage regulation and economic dispatch in DC microgrid are performed at different time scales, which cannot keep the distributed generators (DGs) at the optimal operating point in real time. In this paper, a novel distributed cooperative control strategy is proposed to synchronously achieve stable bus voltage restoration and optimal power sharing in islanded DC microgrids. The proposed strategy breaks the constraints of hierarchical control strategies, and incorporates the objectives of voltage regulation and economic dispatch into a distributed cooperative control framework to eliminate average bus voltage deviation and minimize total power generation costs in real time. The stability of the proposed strategy is verified by eigenvalue analysis and steady-state analysis. Furthermore, the concept of “incremental cost (IC) margin” is introduced in cooperative control considering capacity constraints to avoid the converter output power violation and performance degradation. Finally, the MATLAB/Simulink simulation and StarSim HIL experimental results verify the effectiveness and robustness of the proposed strategy in an islanded DC microgrid under various testing scenarios.

Performance evaluation of a novel system for improving power generation and clean utilization of high-risk medical waste in a cement plant integrating with plasma gasification, gas turbine and ORC

The energy of medical waste can be cleanly utilized by plasma gasification technology, and the large amount of electricity required can be provided cheaply by cement plants. To improve the cement plant energy utilization efficiency, the waste heat of high-temperature syngas and flue gases is a suitable and cheap heat source to improve the steam parameters. The two systems have complementary advantages and have the potential to operate collaboratively. A new system is proposed and verified by thermodynamic, economic and sensitivity analyses. The key parameters, such as gasification agents, mass flow rate, steam temperature and pressure, organic working fluids and operating parameters, are optimized. O2 as the gasification agent can reduce the plasma gasification electricity consumption. The cement plant power generation efficiency can be increased by 3.75%, and its power generation exergy efficiency can reach 65.43%. Medical waste is cleanly utilized, and its power generation efficiency reaches 47.10%. The total net power generation is increased from 8.84MW to 14.12MW. The system can increase revenue by 12,539.84 k$ per year, and the increased investment is recovered in 1.14 years. This study provides a promising solution for the clean co-processing of medical waste and effectively reduces energy waste in the cement production process.

Integration of deep learning and improved multi-objective algorithm to optimize reservoir operation for balancing human and downstream ecological needs

Dam (reservoir)-induced alterations of flow and water temperature regimes can threaten downstream fish habitats and native aquatic ecosystems. Alleviating the negative environmental impacts of dam-reservoir and balancing the multiple purposes of reservoir operation have attracted wide attention. While previous studies have incorporated ecological flow requirements in reservoir operation strategies, a comprehensive analysis of trade-offs among hydropower benefits, ecological flow, and ecological water temperature demands is lacking. Hence, this study develops a multi-objective ecological scheduling model, considering total power generation, ecological flow guarantee index, and ecological water temperature guarantee index simultaneously. The model is based on an integrated multi-objective simulation-optimization (MOSO) framework which is applied to Three Gorges Reservoir. To that end, first, a hybrid long short-term memory and one-dimensional convolutional neural network (LSTM_1DCNN) model is utilized to simulate the dam discharge temperature. Then, an improved epsilon multi-objective ant colony optimization for continuous domain algorithm (ε-MOACOR) is proposed to investigate the trade-offs among the competing objectives. Results show that LSTM _1DCNN outperforms other competing models in predicting dam discharge temperature. The conflicts among economic and ecological objectives are often prominent. The proposed ε-MOACOR has potential in resolving such conflicts and has high efficiency in solving multi-objective benchmark tests as well as reservoir optimization problem. More realistic and pragmatic Pareto-optimal solutions for typical dry, normal and wet years can be generated by the MOSO framework. The ecological water temperature guarantee index objective, which should be considered in reservoir operation, can be improved as inflow discharge increases or the temporal distribution of dam discharge volume becomes more uneven.

Multiobjective multihydropower reservoir operation optimization with transformer-based deep reinforcement learning

The paper introduces a transformer-based deep reinforcement learning (T-DRL) approach designed to address the multiobjective multihydropower reservoir operation optimization (MMROO) problem. Unlike existing literature that primarily focuses on maximizing power generation from individual reservoirs, the MMROO model in this study considers the broader context of multiple reservoirs, encompassing total power generation, ecological protection, and residential area water supply. The computational challenges posed by the numerous constraints and nonlinearities of multiple reservoirs render conventional multiobjective evolutionary algorithms both expensive and lacking in generalization capabilities for solving the MMROO problem. To overcome these challenges, the paper proposes a T-DRL approach that leverages the multihead attention mechanism within the encoder module to adeptly extract complex information from reservoirs and residential areas. The two-stage encoder effectively processes diverse information separately. The multireservoir network of the decoder then generates optimal decisions based on contextual information. The case study focusing on Lake Mead and Lake Powell in the Colorado River Basin demonstrates the efficacy of the T-DRL approach, producing operation strategies that outperform a state-of-the-art method. Specifically, the proposed approach yields a 10.11% increase in electricity generation, a 39.69% reduction in amended annual proportional flow deviation, and a 4.10% rise in water supply revenue. Overall, the T-DRL approach emerges as an effective method for the multiobjective operation of multihydropower reservoir systems.

Using Particle Swarm Optimization with Backpropagation Neural Networks and Analytic Hierarchy Process to Optimize the Power Generation Performance of Enhanced Geothermal System (EGS)

The optimization of the production scheme for enhanced geothermal systems (EGS) in geothermal fields is crucial for enhancing heat production efficiency and prolonging the lifespan of thermal reservoirs. In this study, the 4100–4300 m granite diorite stratum in the Zhacang geothermal field was taken as the target stratum to establish a numerical model of water-heat coupling of three vertical wells. However, relying solely on numerical simulation for optimization is time-consuming and challenging for the determination of the globally optimal production plan. The present study proposes a comprehensive evaluation method for optimizing the performance of EGS power generation based on the integration of particle swarm optimization with backpropagation neural network (PSO-BPNN) and analytic hierarchy process (AHP). Five different PSO-BPNN models were constructed based on the numerical simulation data to predict different EGS power generation performance indexes, including the production temperature, the injection pressure, the total electricity generation, the electric energy efficiency and the levelized cost of electricity. Based on these PSO-BPNN models, the weights of various thermal development evaluation indexes were calculated by AHP to conduct a comprehensive evaluation of the power generation performance of the three vertical wells EGS. The results show that the PSO-BPNN model has good prediction accuracy for EGS prediction of various performance indicators, with a coefficient of determination (R2) exceeding 0.999. The AHP evaluation of all production schemes reveals that the optimal power generation scheme entails a well spacing of 580 m, water injection rate of 56 kg/s, injection temperature of 38 °C and fracture permeability of 2.0 × 10−10 m2. Over a span of 30 years, this scheme can provide a total power generation capacity amounting to 1775 GWh, with an associated LCOE value of 0.03837 USD/kWh. This not only provides a reference for the development and optimization of geothermal systems in the Zhacang geothermal field but also provides a new idea for the optimization design of other geothermal projects.

Whether rural rooftop photovoltaics can effectively fight the power consumption conflicts at the regional scale – A case study of Jiangsu Province

To fight the power consumption conflicts at the regional scale, rooftop solar photovoltaics (RTSPV) in rural areas is considered as a critical way. In this study, we constructed a sophisticated framework for evaluating the regional RTSPV power generation potential of rural areas. Focusing on Jiangsu Province, the rural RTSPV power generation potential was evaluated. Then, the generation potential was compared with electricity demand to describe the spatial heterogeneity of the supply and demand situation, and proposed the pathways to alleviate the regional consumption conflicts. The results showed that the total RTSPV power generation potential of rural areas in Jiangsu Province is 202.91 TWh, which can meet the electricity demand of rural areas in this province. From the perspective of supply and demand, the conflicts between rural RTSPV power generation and electricity demand will be aggravated, especially in areas of rapid economic development. The rural RTSPV power generation of Suzhou, Wuxi, and Changzhou is far low the actual demand for electricity. While for the city with significant disparities between urban and rural areas, the development of rural RTSPV can effectively alleviate the power consumption conflicts. In particular, the rural RTSPV power generation in Xuzhou can meet the demand of total electricity.

Energy scavenging from the diurnal cycle with a temperature-doubler circuit and a self-adaptive photonic design

Abstract A temperature-doubler circuit is the functional equivalent of a voltage-doubler in the thermal domain. Effective temperature-doubler circuits could benefit energy scavenging from fluctuating thermal resources, e.g. the diurnal cycle. However, the current paradigm relies on static photonic designs of the selective solar absorber or blackbody emitter, which aims at maximizing energy harvesting from either the sun or outer space, but not from both. Furthermore, photonic and thermal optimizations have not yet been coupled to maximize the power output. Here we develop a general framework to optimize the energy acquisition and conversion simultaneously to maximize a temperature-doubler’s power output under a realistic solar-thermal boundary condition. With an ideal self-adaptive absorber/emitter to fully exploit the thermodynamic potential of both the sun and outer space, the theoretical limit of the temperature-doubler circuit’s average output power in a diurnal cycle is found to be 168 W m−2, a 12-fold enhancement as compared to the blackbody emitter. We provide a numerical design of such a self-adaptive absorber/emitter, which, combined with a thermoelectric generator, generate 2.3 times more power than the blackbody emitter in a synthetic “experiment”. The model further reveals that, as compared to traditional thermal circuits, the key merit of the temperature-doubler is not to enhance the total power generation, but to convert the fluctuating thermodynamic input to a continuous and stable power output in a 24 h day-night cycle.

Risk control of hydropower-photovoltaic multi-energy complementary scheduling based on energy storage allocation

The complementary scheduling of hydropower with wind and photovoltaic (PV) power is an effective way to promote new energy consumption. However, previous studies have disregarded the operational risks of hydropower plants due to their physical constraints when complementing new energy sources. This study proposes a risk control method for a hybrid hydro-PV power system by adding electrochemistry energy storage (EES). A “day ahead–intraday–real-time” three-layer nested model is developed to guide the joint operation of the hydro-PV-EES hybrid system. The complementary flexibility of hydropower and EES is quantified and utilized to minimize unfavorable operating conditions of hydropower units when regulating PV forecast deviations. A case study of China's Longyangxia hydro-PV complementary project shows that after EES is connected to the system: (1) the total power generation of the system is improved 3.04%, and no power curtailment or shortage occurs; (2) the number of startups and shutdowns, and crossing the vibration zone of hydropower units are reduced by 12.87% and 12.17%, thereby improving the safety and operational stability of the hydropower plant; (3) the regulation flexibility supply of the complementary system is considerably improved; and (4) EES achieves flexible and safe control itself, with over 90% of the scheduling periods being in a healthy SOC range.

Assessment of a sustainable power generation system utilizing supercritical carbon dioxide working fluid: Thermodynamic, economic, and environmental analysis

Solar energy stands out as one of the most abundant and cost-effective resources for energy conversion systems, playing a pivotal role in addressing the world's growing energy demands and environmental concerns. This study focuses on a power generation system that integrates multiple technologies for efficient energy conversion, including a parabolic solar trough collector unit, a supercritical carbon dioxide Brayton cycle, and two dual-pressure organic Rankine cycles. The goal is to assess this system from various angles, including energy, exergy, exergoeconomic, and exergoenvironmental aspects. The base mode study results reveal an overall energy efficiency of 16.66 %, exergy efficiency of 17.88 %, a total net power generation of 17.32 MW, a payback period of 4.38 years, and a total exergoenvironmental impact rate of 126.75 Pt/h. Additionally, the study conducts a parametric investigation to analyze how the system performs under different conditions and how changes in design parameters affect its main outputs. Furthermore, the study utilizes a multi-objective particle swarm optimization algorithm and a decision-maker method to identify the most desirable condition for the system's performance. Three optimization scenarios are considered, and various specific costs for electricity are evaluated to determine the payback period and net present value.

Numerical simulation of thermal performance based on cogeneration low carbon heating unit manufacturing

The renewable energy complementary cogeneration system has broad application prospects in the field of regional comprehensive energy utilization. The author proposes a trough solar assisted biomass cogeneration system, which uses medium and low temperature trough solar energy to heat conduction oil, drives absorption heat pump to preheat water in the heating network, saves heating steam extraction and increases power output under the condition that biomass fuel and heat supply remain constant. The EBSILON professional software was used to model and simulate the case unit and integrated system, and based on this, thermodynamic characteristics such as system energy flow and energy loss were analyzed. The results indicate that: under the design condition, 1.78 MWh of solar power can be generated, the photoelectric efficiency is 20.06%, and the photoelectric conversion efficiency can reach 21.60%. Hourly simulation analysis of the whole heating season shows that the total solar power generation generated in five months of the heating period is 1124.30 MWh, and the average photoelectric efficiency is 16.49%.

A Multi-Objective Approach to Hybrid Renewable Energy Systems: Cascading Hydropower for Solar and Wind Variability Compensation

Renewable energy sources like solar and wind face an insurmountable obstacle in the form of environmental change-induced discontinuity and instability. Since hydropower is quick to respond and doesn't cost much to alter, it was a common choice for electric energy system correction. A cascade hydropower (CHP) station compensates the hydro power-solar-wind energy system that we present in this study, which considers several long-term goals. Among the model's objectives is the optimization of the power system's annual total power generation while simultaneously minimizing power output variations. As a prerequisite for optimizing hydropower, this model first determines the total Photovoltaic (PV) and wind power, and then feeds those numbers into the power grid. In order to obtain a set of solutions for the model that has been proposed, we suggest an enhanced non-dominated sorting whale optimization algorithm (NSWOA). According to the findings, decision-makers have access to a plethora of options for optimal selection through the revised NSWOA, and hydropower's superior modifying capabilities more than compensate for the PV and wind power's deficiencies.

Analyzing the impact of blade geometrical parameters on energy recovery and efficiency of centrifugal pump as turbine installed in the pressure-reducing station

Improving renewable energy efficiency has received great attention globally by increasing demand for energy supplies and air pollution issues. The Soft Pressure Regulation System (SPRS) as a potential technology provides the possibility of regulating pressure and energy recovery in pressure-reducing stations. Pump as Turbine (PAT) is a good choice for installation in Water Distribution Network (WDN) pipelines due to its availability and economic benefits, and it can play a key role in decreasing startup time and return on investment. In this paper, the performance of centrifugal PAT under WDN conditions has been numerically and experimentally evaluated, and simulation validation was performed, too. Analyzing the work conditions of the pressure reduction station shows that the hourly flow rate trend changes considerably based on end-user demand. A major portion of the SPRS's operation time occurs in off-design conditions of the PAT, and efficiency is drastically decreased considering the lack of flow control tools. The effect of blade inlet angle, blade warp angle, blade curvature, and change of these parameters simultaneously was investigated to increase the high-efficiency working range. Losses resulting from flow separation and formation of vortices are significantly decreased by simultaneous change of blade geometrical parameters in the range of design point and higher flow rates (Q ≥ 1.0QBEP). Since the highest frequency of flow rate based on statistical analysis occurs in this range, the total power generation of SPRS improves significantly. The PAT efficiency with the improved impeller at part-load condition (0.8QBEP), design condition (QBEP), and over-load condition (1.2QBEP) is improved by 0.83 %, 2.69 %, and 6.71 % in comparison with the original impeller, respectively.

2D numerical modeling of solute transport Na-K from a geothermal reservoir: The case of Las Tres Vírgenes, BCS

Las Tres Vírgenes geothermal field (LTVGF) is located within the volcanic complex of the same name with temperatures between 250 and 275 °C and a total power generation capacity of 10 MW. For geothermal systems, understanding the thermodynamic-chemical equilibrium of the fluid-rock interaction allows us to study the reactions involved in the precipitation or dissolution of minerals. In this work, we use the hydrothermal alteration mineralogical phases albite, microcline, and zoisite that are in equilibrium with the geothermal fluid as a source of cations (Na+, K+, and Ca2+) to model the chemical composition of the geothermal fluids in the last 20 years. The heat transfer (conductive-convective) and solute transport (advective-diffusive) equations in 2D, were discretized using the Finite Volume Method (FVM) and were coupled to simulate the temperature profile and spatial distribution of the main cations in the LTVGF reservoir. The code evaluates the thermal and chemical evolution of the reservoir from an initial geothermal gradient and an initial chemical composition of the fluid to reach the present concentrations at reservoir conditions. Based on the model results, we consider a reservoir between 1000 and 2000 m in depth and initial concentrations of 100 ppm for sodium to get the average concentrations at reservoir conditions of wells LV-13, LV-11, LV-6, LV-3, LV-4, and LV-1 corresponding to values between 3138 and 3661 ppm and temperatures between 225 and 249 °C. For potassium, the initial concentration was 10 ppm to reproduce the average concentrations between 604 and 663 ppm for wells LV-13, LV-11, LV-4, and LV-5 obtaining temperatures between 223 °C and 257 °C. For calcium, the initial concentration was 2 ppm and reproduced the concentrations of wells LV-5 and LV-6 (251 and 260 ppm) which are at depths of 1737 and 2162 m and temperatures of 225 and 260 °C. This work presents perhaps the first approach to solute transport of the LTVGF reservoir and it was determined that the alteration minerals considered influence the chemical composition of the current discharge fluids of the field. These results promote using Na/K geothermometers based on ionic activities proposed in the literature to estimate the reservoir temperature according to the equilibrium conditions and the chemical composition of the fluids.

Multi-criteria decision-making for techno-economic and environmentally sustainable decentralized hybrid power and green hydrogen cogeneration system

For global sustainable development, supplying reliable, clean and affordable energy to all is critical. Also to achieve the stringent carbon emission reduction target, the global energy transition is towards increasing the renewable share of total power generation. As renewable resources are intermittent, widely variable and nature dependent, a decentralized hybrid energy system may be the potential solution to address these issues. However, mismatch between energy demand and generation of such systems is a critical problem that needs to be addressed. Excess power generated than local instantaneous demand must be utilized in a sustainable way. Production of hydrogen can address the above issues as it has large capacity and long term power absorption capability. Currently it is considered as a valuable energy carrier. This work proposes to convert the excess electricity of a distributed system to a value added by-product, i.e., ‘green’ hydrogen. This study presented an integrated methodology to evaluate the overall sustainability, i.e., techno-economic and environmental performances of this combined electricity and hydrogen production system. These sustainability assessments do not converge to a single optimal solution. Therefore, a multi-criteria decision making approach is adopted to decide the acceptable sustainable solution. This integrated methodology concludes that the solar-wind-diesel-battery-electrolyser combination is the acceptable optimal solution. It meets the required load and produces hydrogen as a by-product at least cost with optimal environmental impact (cost of electricity-$ 0.252/kWh, cost of hydrogen-$ 2.59/kg, renewable share- 98.4%, payback period- 6.1 yrs, human health- 76476.7 DALY, ecosystem 54.17 species.yr and resource-61521013 USD 2013).