Cogeneration Unit Research Articles

Performance of Gas-Steam Combined Cycle Cogeneration Units Influenced by Heating Network Terminal Steam Parameters

Performance of Gas-Steam Combined Cycle Cogeneration Units Influenced by Heating Network Terminal Steam Parameters

Optimization of speed droop governor operation at the gas turbine cogeneration unit

Variations in customer demand for active power can impact frequency levels, potentially leading to instability within the electrical power system. To uphold system stability, it becomes essential to control the provision of active power to ensure the frequency remains consistent. This research aims to develop a simulation model for optimizing of the operation of the speed droop governor at the gas turbine cogeneration unit. This research used the quantitative method and descriptive statistical analysis techniques. The simulation model was employed as a simulator for operating the speed droop governor for frequency regulation in the electrical system. The gas turbine cogeneration unit 2 operational data of the speed droop values was used to analyze the influence of the generating unit’s response to changes in frequency. The analysis and simulation results revealed the gas turbine cogeneration unit 2 speed droop value of 4%, which was considered ideal for maintaining the stability of the 60 Hz nominal frequency required by customers.

Theoretical analysis and economic evaluation of wind power consumption by electric boiler and heat storage tank for distributed heat supply system

The intermittency and volatility of wind power and the characteristics of the operating mode of cogeneration units pose certain challenges to the wind power consumption of the power grid. To optimize the performance of the power and heat combined operation system and maximize the wind power consumption, this paper establishes a mathematical model for each component of the cogeneration system, including the thermal dynamic characteristics of the heat network, buildings, cogeneration units, electric boiler, and heat storage tank. At the same time, a scheduling optimization model is proposed, which considers the power load demand, and wind power output of the regional heating system. The research results provide insights and optimal dispatching strategies for ensuring the reliable operation of the power system and heating system and realizing the efficient utilization of wind power. This paper verifies the effectiveness and feasibility of optimizing the cogeneration system and provides a practical solution to the challenge of cogeneration economics.

A potential coupling of reforming and electrolysis for producing renewable hydrogen from landfill gas

Organic sold waste disposed of in landfills undergoes a mostly anaerobic process which generates a mixture of methane (CH4), carbon dioxide (CO2) and other various gases such as nitrogen, oxygen, sulphides, and non-methane organic compounds (NMOC), known as landfill gas (LFG). Being composed mostly of CH4 and CO2, landfill gas is a potent greenhouse gas (GHG). As a result, various waste treatment interventions are required to minimize the potential catastrophic damage to the environment from direct greenhouse gas emissions from landfills. One effective solution is combustion to generate electricity exploiting methane’s flammability properties. Biomass-based power plants have been present for decades. However, the combustion process is accompanied by a remarkable production of thermal energy which is typically not exploited and therefore lost to the ambient. The current work presents an energetic solution to manage organic waste by employing green hydrogen production. To do so, a hybrid layout based on a cogeneration unit (CHP) fed with landfill gas is considered. The electrical power produced by the CHP is used to produce hydrogen through low-temperature water electrolysis. Furthermore, due to the significant waste heat available in the system, excess thermal power is employed for the methane steam reforming process through a heat recovery section. Hydrogen produced from the reforming section is green since the input is from landfill gas, which is considered renewable. The levelized cost of hydrogen produced from such a hybrid layout is obtained and compared with non-renewable sources in this field. In addition, the annual H2 production rate is calculated for a capacity factor equal to 70%. The results show an annual Hydrogen production of about 167 t/y. LCOH at the stack of about 2 €/kg is reported.

Research on the operation of integrated energy microgrid based on cluster power sharing mechanism

This paper proposes a Nash bargaining cooperative game model for a microgrid cluster system with double re-energy-load delay considering electricity, heat and gas multi-energy synergies. With the minimization of the operating cost of each microgrid as the objective function, a low-carbon operation model of a multi-energy complementary integrated energy microgrid considering fuzzy opportunity constraints is developed, an optimal operation mechanism including carbon quota and carbon trading is assessed, and a carbon capture system and an electricity-gas conversion device are added to the improved cogeneration unit model. Source-load uncertainty in microgrids is described in terms of new fuzzy parameters of new energy and undefined parameters of load demand. Each microgrid plays a second game with the marginal contribution rate and carbon trading cost rate as the bargaining power. The model is solved in a distributed manner using the ADMM-RGE algorithm. Finally, the simulation results show that the proposed multi-microgrid power-sharing way maximizes the benefits of microgrid alliances; the cooperative help of microgrid alliances is pretty distributed according to the size of each microgrid's energy contribution; carbon capture joint power-gas systems and energy sharing methods between microgrids can effectively reduce carbon emissions during microgrid operation.

Optimized Dispatch of Regional Integrated Energy System Considering Wind Power Consumption in Low-Temperature Environment

The wind abandonment phenomenon of cogeneration units in regional integrated energy systems (RIES) under the operation mode of “heat for electricity” and the improvement in the operation efficiency of the energy storage system under a low-temperature environment are problems that need to be solved urgently. To this end, a regional integrated energy system optimization scheduling method based on fine energy storage and wind power consumption is proposed in the paper. First, a fine energy storage model more adapted to a low-temperature environment is established on the power side to accurately simulate the actual working state of the energy storage components and quantify the uncertainty of the wind power output using the conditional value-at-risk (CVaR) theory. Then, a combined heat and power demand response mechanism is introduced on the load side to reduce the peak-to-valley difference in the heat and power loads, it is realized to promote the system’s consumption of wind power without increasing the transmission power of the contact line. Finally, the example is solved on the MATLAB platform with the objective of minimizing the total cost of the RIES optimal dispatch. The simulation results show that the proposed model is not only more adaptable to a low-temperature environment compared with the traditional model but also reduces the overall cost of the system by 2.58% while realizing the complete consumption of wind power. This innovative study provides a feasible and efficient solution to improve the performance of integrated energy systems, especially the operation capability in extreme environments.

An Assessment of the Development of a Mobile Agricultural Biogas Plant in the Context of a Cogeneration System

This article presents examples of cogeneration systems, which are standard equipment for biogas installations, based on the production of heat and electricity. It has been shown that in the case of microgeneration, ease of servicing and low installation costs are crucial. Characteristic aspects of developing concepts for mobile installations (small scale) that produce biogas, often with a simple container structure that is ready to be located in the economic infrastructure of the agricultural industry, were indicated. Recommendations for the operation of micro-biogas models are presented, which have the greatest impact on the advisability of using agricultural waste for energy purposes. A characteristic farm was selected, which has a substrate necessary for the process of methane fermentation of slurry from pig farming. The cogenerator, which constitutes a potential energy demand from the point of view of Polish agriculture in the context of renewable energy production, was analyzed. The research goal was to adapt the cogenerator to the conditions existing on a farm, which should meet the technical and technological expectations for the process of managing the produced methane with a value of 80% in agricultural biogas. The assessment of the impact of the amount of biogas on the level of CO, NO, NO2 and PM emissions was carried out at a constant engine speed for various load levels; the percentage of biogas was changed from 40 to approximately 70–80%, i.e., until significant knocking combustion was detected in the tested engines. As a result, the existing control and control system for the operation of the cogeneration unit prevents the most effective mode of operation of the research installation as a prosumer micro-installation. When the AG20P biogas unit operated in parallel with the grid with an active power of up to 11.7 kW, the electricity produced by the unit met the adopted assumptions and requirements. What is new in this article is the use of a cogeneration unit that has been adapted to its functionality, taking into account the assessment of the prospects for optimizing the cogeneration system in the context of the use of renewable energy sources as agricultural biogas. The best method was to attempt to determine the operating conditions of the cogenerator to develop the optimization of a biogas cogeneration unit producing electricity and heat in a micro-installation for the needs of an individual farm.

Low-carbon economic analysis of a virtual power plant with wind and solar power considering the integrated flexible operation mode of a carbon capture thermoelectric unit

During the period when heating is required in North China, the task of meeting the heating needs of customers is mainly undertaken by thermoelectric units under the ”determining electricity by heat” operation mode. This heating mode leads to difficulties in incorporating renewable energy and high carbon dioxide emissions. To solve these problems, carbon capture technology and wind power heating technology are introduced in this study. Cogeneration units with a carbon capture integrated flexible operation mode are introduced into the system to reduce CO2 emissions, while making the electric output and the thermal output more flexible. Then, the cogeneration optimal scheduling model of a virtual power plant is constructed. This model includes wind power heating equipment and carbon capture cogeneration units under the integrated flexible operation mode. Due to the highly nonlinear characteristics of the model, we solve this problem by the Deep Q-Network (DQN) algorithm, which is an algorithm that uses the nonlinear approximation value function of a neural network to make the model more robust. Finally, we propose three technical strategies and compare the results of the three strategies in terms of low carbon levels and economic value. The results show that the model can effectively improve the economic income of the system and reduce carbon emissions.

Performance investigation of a hybrid PV/T collector with a novel trapezoidal fluid channel

The photovoltaic-thermal collector (PV/T) is an innovative technology that combines PV cells and solar thermal collectors into a co-generation unit, enabling full-spectrum solar utilization. This research proposes and examines a hybrid PV/T system with novel trapezoidal fluid channels embedded in graphite, arranged in a parallel S-shaped structure under outdoor conditions of Beijing. Parametric discussions and daily performance analysis are conducted to assess its effectiveness and stability. A daily average of 12.7 °C reduction in cell temperature compared to PV modules results in a relative 5.20 % improvement in electrical output under the intensity of solar radiation is 597 W/m2. Similarly, the peak temperature of the water tank reaches 56.9 °C, and thermal efficiency is enhanced by 7.86 % over conventional sheet-tube PV/T collectors. For further optimization, a constrained adaptive particle swarm optimization algorithm (EPF-APSO) is constructed based on the experimental data, implementing a variable water flow rate (VWV) strategy. Compared to a constant water flow rate (CWV), the overall energy collected varies from 2.755 to 2.828 kWh per day, potentially reducing pump energy consumption by 17.93 %. The contribution of this paper provides references on structural and operational parameters optimization of PV/T collectors applying machine learning algorithms for better comprehensive efficiency.

Optimize configuration of multi-energy storage system in a standalone microgrid

Aiming at the integrated energy microgrid, an important part of the energy internet, this paper constructs a multi-energy storage system optimization configuration model of the integrated energy microgrid in an independent mode, and proposes a configuration method that includes the rated power and capacity of the storage system and the heat storage system. The storage system model includes the estimation of battery life during heating and non-heating periods. The model takes economy as the index, and considers the relevant constraints of thermoelectric coupling of thermoelectric units, including thermal and electrical balance, unit climb, energy storage system and self-sufficiency probability, etc., and uses a The bacterial colony chemotaxis (BCC) algorithm model based on unit output and energy storage system power distribution strategy to solve the problem. The operation characteristics of cogeneration units equipped with energy storage system are discussed. The results show that the proposed multi-energy storage system configuration method has significant economic and environmental benefits in both heating and non-heating periods, and promotes the uptake of wind power.

Thermodynamic performance of CaCl2 absorption heat pump thermal energy storage system with triple storage tanks

Renewable energy source is playing an increasingly important role in district heating based on cogeneration units. Absorption thermal energy storage has the characteristics of high thermal energy storage density and low heat loss in long-term storage. In this paper, an absorption heat pump thermal energy storage system with CaCl2-water solution as the working fluid is proposed for solving the problem of insufficient wind power accommodations due to coal-fired cogeneration heat-power coupling. A steady-state thermodynamic model of the system is constructed in the Aspen Plus software. Under the considered design conditions, the volume of the tank required for one hour of operation of the system, thermal energy storage density, thermal energy storage ratio, and heating ratio are 464.61 m3, 29.81 kW h/m3, 46.50%, and 53.54%, respectively. The thermal energy storage density is 1.43 times and 1.25 times, and the tank volume is 0.7 times and 0.8 times, of those of a dual tank thermal energy storage system with H2O and CaCl2-water solution as the working fluids respectively. The effects of the system parameters on the thermal energy storage performance are simulated to obtain the optimal performance. At the optimum system performance, the tank volume required to operate the system for one hour, thermal energy storage density, heating ratio, and thermal energy storage ratio are found to be 439.56 m3, 37.39 kW h/m3, 44.83%, and 55.17%, respectively. Accordingly, the thermal energy storage performance of this system is also found to be superior to that of the traditional thermal energy storage system, which will be beneficial for reducing the volume of storage tanks in cogeneration units and increasing the thermal storage temperature.

Energy Efficiency State Identification for Cogeneration Units Based on Benchmark Value

In China, cogeneration units predominantly employ a flexible operation mechanism. However, it is possible that this could lead to a decline in performance and an increase in energy consumption. This paper introduces a methodology that utilizes the data mining technique to ascertain the benchmark value section of the energy efficiency status index for cogeneration units. The equal interval division method is utilized for the purpose of categorizing the operating conditions. The Gaussian mixture model is utilized to ascertain the benchmark value section in relation to the fluctuating operating conditions by estimating the probability of historical data. The methodology is verified by utilizing historical data from a functioning cogeneration unit. The findings suggest that the unit’s total heat consumption can be decreased by 32.5–50 kJ·(kW·h)−1 when compared to the design-based approach.

The energetic and economic analysis of demand-driven biogas plant investment possibility in dairy farm

The paper aims to analyze the energy and economic effect of a demand-driven biogas investment versus a conventional one in modern dairy farm facilities of medium scale. Demand-driven exploitation may be the only way to obtain permission for connection to energy grid of new renewable energy sources (RES) installations in administrative regions where intermittent RES i.e. photovoltaics provide a large amount of energy to the grid. The biogas plant cogeneration capacity is meant to respond to demand out of the time range of intense electricity generation from photovoltaic farms.The energetic and economic analysis showed that the investment in the biogas plant would be profitable (payback period of 3.41 years in the best scenario), achieved thanks to operating as demand-driven biogas plant with CHP 499 kWe working 12 h/day (4250 h/year). Since the biogas plant is planned to operate as a demand-driven installation, it would also be possible to perform service inspections of the cogeneration unit (CHP) when it is not working. As a result, this small biogas plant (250 kW) with 499 kW CHP can produce as much as 2126 MWh/year. The second aspect of profitability is the use of biomass (mainly biowaste) from a farm as a substrate.

The Impact of Manure Use for Energy Purposes on the Economic Balance of a Dairy Farm

The use of methane fermentation in mesophilic conditions for the energy use of cow manure and additional co-substrates from the farm can bring a small dairy farm (140 dairy cows) financial benefits of up to EUR 114,159 per year. Taking into account the need to pay for emissions calculated as carbon dioxide equivalent, this profit could be reduced to EUR 81,323 per year. With the traditional direct use of manure, this profit would drop by as much as 60% to the level of EUR 33,944 per year. Therefore, the introduction of fees for emissions may significantly burden current dairy farms. As has already been shown, just compacting and covering the manure (which costs approx. EUR 2000 per year for 140 cows) would give almost twice as much profit—EUR 64,509 per year. Although an investment in a small biogas plant with a cogeneration unit on a family dairy farm may have a payback period of less than 6.5 years and a return of capital employed of 16%, most small farms in the world will not be able to afford its construction without external subsidies. At the same time, it would make it possible to reduce emissions by almost 270 times—from 41,460 to 154 tons of CO2eq per year—and the possibility of preserving valuable nutrients and minerals and supporting soil properties in the digestate. Therefore, it seems necessary for Europe to introduce a support system for small- and medium-sized farms with this type of investment in the near future in a much larger form than it has been so far.

Investigating effect of various time varying load models in grid connected microgrid system integrated with renewables and cogeneration units

ABSTRACT The optimal allocation of sources considering voltage-dependent load models is essential as the power consumption of the loads is sensitive to voltage magnitude. In this paper, optimal allocation of microgrid system with cogeneration units, renewable energy sources (RES), shunt capacitors and heat boiler are determined for constant, residential, industrial, commercial and mixed load models. The cost, emission, energy loss, voltage deviation and voltage stability values for each load model is determined using particle swarm optimisation (PSO) integrated fuzzy max–min approach while the uncertainties in RES are taken into account. Results demonstrate that the cost, energy loss and voltage deviation values are maximum for constant power (CP) load model compared with other load models. Furthermore, the system with constant impedance (CZ) load achieves maximum loading capability than with other types of constant loads. The proposed method is validated on 33-bus grid-connected microgrid system with all the load models.

Molecular catalysed Guerbet reaction: Moving to the larger and the Greener through LCA and scale up simulation approaches

Efficient homologation of bio-ethanol can be performed under mild conditions exploiting a catalytic system based of a ruthenium molecular catalyst, benzoquinone and a base as a co-catalysts. Conversions and selectivity can be tuned by changing the head space of the reactor. On this basis, preliminary design of a full-scale process has been developed based on the experimental results. The process has been characterized with specific energy and performance indicators per unit of produced butanol, which have been used as input for the life cycle assessment analysis. The LCA was applied as scientific methodology to address potential burdens of the baseline configuration, 3X catalytic cycles, electricity from Italian grid and heat from natural gas. Hotspots were identified according to a multi-impact approach method (ReCiPe 2016). The usage of dedicated lignocellulosic biomass as a source of EtOH, the synthesis of the catalytic system and the energy requirements were addressed as the major contributors. Thus, further sensitivity scenarios were created. The best configuration was identified in the use of waste biomasses and in an integrated cogeneration unit. In addition, enabling the recovery of the catalytic system up to five cycles to scenario shows a reduction in the impacts higher than 50% for the categories of global warming potential, −41% for the mineral resource scarcity and around −16% for the fine particulate matter formation. The results were also confirmed by an uncertainty analysis with the Monte Carlo method, which demonstrated the major environmental sustainability of the Guerbet route compared to the oxo synthesis from propylene.

Dynamic scheduling of market price-based combined heat–power-constrained renewable microgrid

Abstract In this paper, a market price-based combined heat–power dynamic dispatch model for a microgrid is presented. The microgrid comprises cogeneration units and wind and solar power-generation units. A battery and a heat storage tank are incorporated to optimally balance variations in heat-and-power load demands. The proposed model explores the impact of market prices of electricity, heat supply and load variability on the optimal schedule such that profit maximizes and emission, loss and waste heat are minimized. The Weibull probability distribution function is applied to characterize the uncertain renewable power variable in the model and to find the over- and under-scheduling costs. The problem is solved using an improved differential evolution algorithm in which a fuzzy membership module is appended to obtain a solution having the highest attainment for the selected multiple objectives. The results show that the proposed model can handle uncertain heat–power demand and price scenarios to produce feasible and optimal schedules with owner profits, heat utilization and renewable share varying between 10.55–115.97%, 72.51–90.39% and 26.82–38.05%, respectively.

Artificial Intelligence Methods for Analysis and Optimization of CHP Cogeneration Units Based on Landfill Biogas as a Progress in Improving Energy Efficiency and Limiting Climate Change

Combined heat and power generation is the simultaneous conversion of primary energy (in the form of fuel) in a technical system into useful thermal and mechanical energy (as the basis for the generation of electricity). This method of energy conversion offers a high degree of efficiency (i.e., very efficient conversion of fuel to useful energy). In the context of energy system transformation, combined heat and power (CHP) is a fundamental pillar and link between the volatile electricity market and the heat market, which enables better planning. This article presents an advanced model for the production of fuel mixtures based on landfill biogas in the context of energy use in CHP units. The search for optimal technological solutions in energy management requires specialized domain-specific knowledge which, using advanced algorithmic models, has the potential to become an essential element in real-time intelligent ICT systems. Numerical modeling makes it possible to build systems based on the knowledge of complex systems, processes, and equipment in a relatively short time. The focus was on analyzing the applicability of algorithmic models based on artificial intelligence implemented in the supervisory control systems (SCADA-type systems including Virtual SCADA) of technological processes in waste management systems. The novelty of the presented solution is the application of predictive diagnostic tools based on multithreaded polymorphic models, supporting making decisions that control complex technological processes and objects and solving the problem of optimal control for intelligent dynamic objects with a logical representation of knowledge about the process, the control object, and the control, for which the learning process consists of successive validation and updating of knowledge and using the results of this updating to determine control decisions.

Stochastic electrical, thermal, cooling, water, and hydrogen management of integrated energy systems considering energy storage systems and demand response programs

Energy hub (EH) is a multi-energy system that combines several energy sources to increase energy supply efficiency, flexibility, and reliability. In this paper, a stochastic two-step multi-objective optimization method is proposed for multi-EH planning that focuses on economic, environmental, and security concerns. In order to meet the demands for electricity, heating, cooling, hydrogen, natural gas, and water, the proposed model includes several components, such as nonrenewable and renewable energy sources, cogeneration units, converters, and storage systems. Also, price-based demand response programs are implemented to provide demand-side flexibility for EHs. The proposed multi-objective framework investigates the total cost of the system, average reserve index (ARI), emissions of the system, and energy not supplied (ENS), simultaneously. EHs categorize their objectives into main and secondary based on priority. Since the total cost is so important, it has been recognized as the primary objective that is minimized in the first step. Also, the emissions, ENS, and ARI are the secondary objectives that are optimized in the second step simultaneously. The proposed model's efficiency is evaluated using an 18-bus test network in both summer and winter seasons. The simulation results present that the proposed model improves the emission, ARI, and ENS by 47.78 %, 53.4 %, and 23.38 % in summer seasons, respectively. And also, the multi-objective framework improves the emission, ARI, and ENS by 45.66 %, 65.84 %, and 52.56 % in winter seasons, respectively.

Numerical analysis of natural gas, hydrogen and ammonia fueled solid oxide fuel cell based micro cogeneration units with anodic gas recirculation

The energy sector is actively transitioning towards climate-neutral solutions, emphasizing advancements in clean power generation technologies. Cogeneration systems based on solid oxide fuel cells (SOFC) currently exhibit higher electrical efficiencies than conventional plants, but their operation can still be improved. One of the approaches to increase its efficiency is implementing anodic off-gas recirculation. In this work, a numerical model of a 10 kW SOFC installation with anodic gas recirculation was analyzed using Aspen HYSYS software. System fueled with three alternative fuels (natural gas, hydrogen, and ammonia) was tested. In this paper it was proven that anode-off gas recirculation improves the electrical and total efficiency of the system for each fuel type. The cogeneration unit with a SOFC stack can operate safely over a wide range of recirculation ratios without need for additional modifications. Ammonia-fueled units achieve electrical efficiency (55%) higher than hydrogen-based system (47.6%) but lower than installation fueled with natural gas (61.8%).