Distributed Power Generation Research Articles

Sustainable All-Day Thermoelectric Power Generation From the Hot Sun and Cold Universe.

Energy conversion from the environment into electricity is the most direct and effective electricity source to sustainably power off-grid electronics, once the electricity requirement exceeds the capability of traditional centralized power supply systems. Normally photovoltaic cells have enabled distributed power generation during the day, but do not work at night. Thus, efficient electricity generation technologies for a sustainable all-day power supply with no necessity for energy storage remain a challenge. Herein, an innovative all-day power generation strategy is reported, which self-adaptively integrates the diurnal photothermal and nocturnal radiative cooling processes into the thermoelectric generator (TEG) via the spectrally dynamic modulated coating, to continuously harvest the energy from the hot sun and the cold universe for power generation. Synergistic with the optimized latent heat phase change material, the electricity generation performance of the TEG is dramatically enhanced, with a maximum power density exceeding 1000mWm-2 during the daytime and up to 25mWm-2 during the nighttime, corresponding to an improvement of 123.1% and 249.1%, compared with the conventional strategy. This work maximizes the utilization of ambient energy resources to provide an environmentally friendly and uninterrupted power generation strategy. This opens up new possibilities for sustained power generation both daytime and nighttime.

Optimal controller for S–CO2 compressor inlet conditioning

The small, simple, and effective characteristics of a Supercritical CO2 (S–CO2) power system make it an ideal candidate for distributed power generation. However, the distributed power generation will be required with constant changes in the operating conditions to meet the varying demand. Thus, it is necessary for the S–CO2 power system to demonstrate that it can operate safely and efficiently under all anticipated operating conditions. One of the key issues in the S–CO2 power system is controlling the compressor inlet conditions. This paper focused on the control of the compressor inlet temperature. In this paper, a system dynamic simulation code is used to model the precooler system for the compressor inlet control first. Based on the analysis results to obtain the transfer function and the state space, a linear quadratic controller was designed using optimal control theory. Since the controller was estimated to have steady-state error, a disturbance observer was also used. To validate the designed controller, experiments were conducted. The experimental results show that the proposed controller can be used to maintain the S–CO2 compressor inlet conditions under various transient scenarios without additional tuning.

Life cycle assessment of the production of an extruded dog food in Brazil

Sustainability is the current focus of the scientific community, governments, and companies in various market segments, such as pet food. Pet food production has increased rapidly in recent years, with a trend toward the development of environmentally friendly products and processes. The first step in creating strategies for mitigating environmental impacts is to assess key points in manufacturing processes. Given this, this study aimed to perform a life cycle assessment (LCA) to estimate the environmental impacts associated with the formulation, production, and distribution phases of an extruded dog food produced in Brazil. System boundaries were from cradle-to-gate, encompassing extraction of raw materials, transportation, processing, production, packaging, and distribution. Estimates were based on the amount of food required to meet the energy requirements for maintenance of a 10 kg dog (functional unit = 2.59 MJ day−1, reference flow = 177.3 g day−1). Environmental impacts were calculated by the environmental footprint method (EF 3.0 v. 1.00) using SimaPro software (v. 9.1.1.1). Product ingredients and packaging materials were modeled under Brazilian conditions using ecoinvent 3.7.1 and Agri-footprint 5.0 databases. Data regarding transportation, processing, distribution, electric and thermal power generation, water usage, and waste generation were obtained from the company's records (2019–2020). In this study, as expected, formulation was the most relevant factor, accounting for 70%–90% of the total environmental impacts. The main impact categories were terrestrial and marine eutrophication, acidification, particulate matter, and climate change (80% of total impacts). Production of the evaluated dog food was associated with the emission of 88.73 kg CO2 eq year−1 or 1.37 kg CO2 eq kg−1 distributed food. The use of animal meals (poultry by-product meal and meat and bone meal) and vegetable by-products (wheat bran and rice bran) contributed to reducing environmental impacts. Therefore, in this study, ingredient selection was considered the most important factor in mitigating the environmental impacts of pet foods. As the overall impact of the formulation depends on data on the use stage, such as nutrient excretion after consumption, future studies should adopt a cradle-to-grave approach for a better comprehension of the feasibility of applying animal and vegetable by-products in the eco-design of pet food products.

Reliable high impedance fault detection method based on the roughness of the neutral current in active distribution systems

Detecting High Impedance Faults (HIFs) in Distribution Systems (DSs) still requires effective solutions. HIFs can cause damage, such as shock hazards and bushfires. However, conventional protection cannot identify HIFs due to their low fault current, and most existing solutions neglect the multiple operating scenarios of the DSs. Thus, this paper proposes a new self-adaptive approach for HIF detection, considering the conductor fall period in a system with distributed generation, a condition usually overlooked in existing studies. The algorithm is based only on the fundamental component and third harmonic extracted from the neutral current using the Stockwell Transform. The approach was thoroughly evaluated, considering several scenarios, such as changes in the system loading, background noise, events that can cause false detection, and variations in the distributed generator power output. The tests considered HIFs signals from real field measurements and generated by a simulation model. The results showed that the algorithm is promising, with high detection rates for all the evaluated scenarios, which included over 400,000 HIF and 6,000 non-HIF cases. Additionally, a comparison proved the superiority of the proposed approach over existing methodologies.

Optimization of sustainable distributed power generation in distribution networks: a comprehensive analysis of location, capacity, and environmental impact

With the increasing integration of distributed generation (DG) into distribution networks, the impact of its output and configuration on the environment and overall benefits has become more pronounced. To enhance environmental benefits while minimizing costs, an optimization model for DG location and capacity considering environmental benefits (LCEB) is proposed. Initially, a mathematical model for DG location and capacity is established, with optimization objectives including voltage deviation, network loss, and environmental benefit. Subsequently, modified particle swarm optimization (MPSO) with a single-dimension search probability mutation is employed to solve this model, obtaining an optimized DG output and layout scheme. Finally, the feasibility and effectiveness of the proposed model are demonstrated through simulation and analysis by using the IEEE33 node system as an example. The results highlight the model’s capability to improve environmental and economic benefits, enhance voltage levels, and reduce network losses within the distribution network.

Micro Grid Integration of Distributed Power Generation Optimal Operating Methods

Microgrids, as localized energy systems comprising distributed power generation sources, offer resilience, flexibility, and efficiency to the modern power grid. Integrating various distributed energy resources (DERs) within microgrids poses challenges in optimizing their operation to ensure reliable and cost-effective energy supply. This paper presents a comprehensive review and analysis of optimal operating methods for the integration of distributed power generation within microgrids.The study explores various aspects of microgrid operation, including optimal dispatch strategies, demand-side management techniques, energy storage utilization, and renewable energy source integration. It investigates the application of advanced optimization algorithms, such as linear programming, mixed-integer linear programming, and metaheuristic algorithms, to address the complex optimization problems inherent in microgrid operation. Furthermore, the paper examines the role of smart grid technologies, advanced control systems, and communication infrastructure in facilitating the efficient operation of microgrids with distributed power generation. It discusses the importance of real-time monitoring, data analytics, and predictive modeling for enhancing decision-making processes and optimizing microgrid performance.

Value Evaluation Model of Multi-Temporal Energy Storage for Flexibility Provision in Microgrids

With the advancement of distributed power generation technology and the deepening of the low-carbon transformation of energy structure, a high proportion of renewable energy has become an inevitable trend in future energy systems, especially for microgrids. However, the volatility and uncertainty associated with renewable energy pose significant challenges to the secure and stable operation of power systems, necessitating the exploration of the flexible regulation of resources. Energy storage, as a crucial flexible resource characterized by technological diversity and a variety of regulation capabilities, has been extensively studied and applied. Nonetheless, the high investment costs and limited returns of energy storage technology, coupled with the ambiguous utility in different scenarios under the current electricity market’s framework, complicate its broader application. To thoroughly analyze the utility of energy storage in facilitating flexible adjustments in microgrids, this study developed a composite weight-TODIM (an acronym in Portuguese for interactive and multi-criteria decision making) model for assessing the utility of energy storage that incorporates heterogeneity in the risk preferences. This model enabled a comparative analysis of the utility of energy storage technology across multiple scenarios, taking the risk preferences of decision-makers into account, thereby providing strategic insights for the application of multi-temporal energy storage in microgrids. The feasibility and effectiveness of the model were validated through a case study analysis.

The consequences and barriers of power system voltage stability in the integration of solar and wind energy: An in-depth analysis

Wind and solar energy production is intermittent and variable, causing voltage fluctuations in the power system. These fluctuations can affect supply and demand balance, leading to voltage instability. In some cases, integrating solar and wind energy can result in overvoltage or undervoltage conditions, which can negatively impact the power grid's operation. The research examines the effects and challenges of integrating wind and solar energy into power grids, concentrating in particular on issues with voltage stability. The investigation explores fundamental issues like voltage stability-based distributed power generation (DG) unit sizing and optimal locations, stability of voltage assessment and methods for enhancement. Experiments are conducted to examine the effects of energy storage devices, adaptive alternate current (AC) transmission lines, static caps and other electric components of the system on the stability of the voltage of the distribution and transmission networks. It provides a comprehensive examination of the technical difficulties, such as the stability issues associated with incorporating massive solar systems into the electrical grid. The research obtained results on technical methods to address the power instability challenges with the integration of solar power on a massive scale into the transmission system and its subtransmissions, known as the medium voltage distribution system.

Design of distributed trading mechanism for prosumers considering the psychological gap effect in community electricity markets

With the large-scale customer-side development of distributed energy and continuous advancements in power market reform, the market-oriented trading of distributed power generation with the participation of prosumers has gradually become an important solution to promote the consumption of distributed energy. In addition, prosumers exhibit obvious bounded rationality characteristics; therefore, the design of efficient and reasonable trading mechanisms determines the efficiency of the market. From this perspective, a distributed electricity market trading mechanism based on the Stackelberg game is proposed for the community electricity trading market, with multiple prosumers participating in the distribution side. Firstly, the trading architecture of the community electricity market was established under the distribution network level. Secondly, the pricing strategy of the distribution network operator and the quantitative strategy of community prosumers were analysed; on this basis, the characteristics of the bounded rationality of prosumers were considered, and the impact of the psychological gap effect of prosumers on their energy utility was introduced into the objective function of prosumers. This facilitated the construction of a Stackelberg game model in which distribution network operators lead and community prosumers follow. Thirdly, the Stackelberg equilibrium was proven to exist and be unique, which was then solved by the distributed algorithm – combining the evolutionary algorithm and quadratic programming – which improves the solution efficiency and effectively protects the privacy of prosumers. Finally, the effectiveness and feasibility of the proposed trading mechanism were verified through numerical examples.

[formula omitted] gain-scheduled dynamic output feedback control with transient performance applied to electrical microgrid

This paper introduces an approach for designing gain-scheduled dynamic output feedback controllers for continuous-time Linear Parameter-Varying (LPV) systems. The aim is to improve transient response by incorporating both D-stability and H∞ criteria into the synthesis conditions. We achieve this by employing changes of variables and congruence transformations, which lead to new synthesis conditions expressed as linear matrix inequalities. Additional fine-tuned scalar parameters can be used to enhance further the controller performance in terms of less conservative H∞ guaranteed costs. To assess the effectiveness of our proposed synthesis procedure, we conduct computational experiments in the context of a microinverter-based distributed power generation system. These experiments take into account real-world operational characteristics, providing a comprehensive evaluation of our approach. The results demonstrate that the designed controller effectively ensures the desired closed-loop system behavior, even when dealing with state noise and discretization errors originating from digital implementation.

CFD investigation on wind power harvesting from small-scale wind turbines for powering residential buildings in New Zealand

ABSTRACT As an alternative solution, wind power could be harnessed by designing and implementing small-scale wind turbines for distributed power generation. In this work, 3-dimensional time-domain numerical simulations, based on the Reynolds-Average Navier-Strokes (RANS) model, are conducted for two categories of small-scale wind turbines, i.e. drag force- (Savonius) and lift force-driven (Darrieus) ones, while placing them at a flat surface and a step height, respectively. The present results confirmed that placing a small-scale wind turbine at a step height can improve the maximum power output, respectively, approximately 219.2% for the Savonius wind turbine and 121.0% for the Darrieus wind turbine operating at their optimum stage; moreover, the corresponding peak power spectral density of the turbine torque is improved by 173.9% and 83.6%, respectively. In addition, the power generated from the wind flow could reduce the CO2 emission. It has been observed that the Savonius turbine could reduce the annual CO2 emission by 3,738.9–19,857.8 kg and that of Darrieus turbines by 4,919.6–26,128.8 kg. This study demonstrated the benefits of adopting forward facing steps to improve wind turbine performance in a typical urban environment.

Energy optimization management of microgrid using improved soft actor-critic algorithm

To tackle the challenges associated with variability and uncertainty in distributed power generation, as well as the complexities of solving high-dimensional energy management mathematical models in mi-crogrid energy optimization, a microgrid energy optimization management method is proposed based on an improved soft actor-critic algorithm. In the proposed method, the improved soft actor-critic algorithm employs an entropy-based objective function to encourage target exploration without assigning signifi-cantly higher probabilities to any part of the action space, which can simplify the analysis process of distributed power generation variability and uncertainty while effectively mitigating the convergence fragility issues in solving the high-dimensional mathematical model of microgrid energy management. The effectiveness of the proposed method is validated through a case study analysis of microgrid energy op-timization management. The results revealed an increase of 51.20%, 52.38%, 13.43%, 16.50%, 58.26%, and 36.33% in the total profits of a microgrid compared with the Deep Q-network algorithm, the state-action-reward-state-action algorithm, the proximal policy optimization algorithm, the ant-colony based algorithm, a microgrid energy optimization management strategy based on the genetic algorithm and the fuzzy inference system, and the theoretical retailer stragety, respectively. Additionally, com-pared with other methods and strategies, the proposed method can learn more optimal microgrid energy management behaviors and anticipate fluctuations in electricity prices and demand.

A Solid Oxide Fuel Cell Stack Integrated With a Diesel Reformer for Distributed Power Generation

A Solid Oxide Fuel Cell Stack Integrated With a Diesel Reformer for Distributed Power Generation

Distributed Generation (DG) system using COPRAS method

Distributed Generation (DG) system. Distributed Generation (DG) power systems, Expansion of power systems in remote areas, and Very recently as a sustainable way of electrification popular. Depletion of conventional fossil fuels, Fuel price volatility, and emissions Awareness environment about reduction, Due to this its demand is increasing. DG systems have additional power quality challenges. There are many types of DG power sources that produce electrical power with different voltages at various frequencies. RES-Based Distributed Generation (DG) Systems are conventional energy systems In finding new modern solutions for planning have contributed Widespread use of DG is old and Defines new views, Current delivery system The only way to deal with the project Calling for more complex defenses. COPRAS (Complex Proportionality Assessment) is very Multiple criteria used in decision-making methods is one. This technique is different Decision making by researchers Used to solve problems. Investment cost, operating cost, Primary energy consumption, CO2 emissions. Energy storage system, fuel system, Wind Solar Hybrid System, Conventional System, PV energy storage system. Involvement of Distributed Generation (DG) system PV energy storage system ranked 1st, and the Conventional system also got 5th position.

Application of Fractional Order PI/PID Voltage Controllers for Three-Phase Voltage Source Inverter with Dynamic Load

Purpose: With the depletion of fossil fuels, the landscape of electrical energy generation has witnessed a transformative shift towards alternative sources such as fuel cells and photovoltaic (PV) systems that produce direct current (DC) electricity. In the realm of distributed power generation, three-phase voltage source inverters (VSIs) are extensively utilized for converting energy from DC sources to alternating current (AC) for the grid or loads. The pivotal objective of this study is to investigate and compare the performance of fractional-order Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) control structures against their integer-order counterparts in the voltage control loop of a VSI connected to a dynamic load system.
 Materials and Methods: The research employs frequency response analysis to design and implement both fractional-order PI/PID and integer-order PI/PID control structures for the voltage control loop. The simulation of the controlled system is conducted using MATLAB/Simulink, considering two distinct test scenarios – unstable and stable dynamic load conditions. The primary focus is on analyzing the inverter output voltage in the d-q axis under these scenarios.
 Findings: The analysis of the simulation results reveals noteworthy distinctions between the fractional-order and integer-order PI/PID controllers in the context of controlling the inverter system with dynamic loads. These findings shed light on the advantages of employing fractional order controllers, particularly in dynamic load scenarios, showcasing superior performance in comparison to their integer-order counterparts.
 Implications to Theory, Practice and Policy: The study's outcomes hold significant implications for the theory and practice of voltage control in distributed power generation systems. The superiority of fractional-order PI controllers underscores their potential for enhancing power quality, especially in systems with unstable and time-varying dynamic loads. These insights can inform the development of more effective control strategies for voltage source inverters, influencing both theoretical frameworks and practical applications. Policymakers may consider these findings when formulating regulations and incentives to promote the adoption of advanced control strategies in the evolving landscape of electrical energy generation.

PRINCIPLES OF FORMING THE OPTIMAL STRUCTURE OF THE ELECTRIC POWER SYSTEM WITH THE INTEGRATED USE OF DISTRIBUTED GENERATION SOURCES

Abstract. The article presents the results of developing the optimal configuration of a hybrid electric power system of distributed generation, taking into account the energy potential of alternative energy in Ukraine. The issues of further development of distributed energy based on the introduction of hybrid systems with renewable sources of distributed energy generation are considered. The potential of alternative energy technologies in Ukraine is analyzed. A comparison of the efficiency of implementation of different types of alternative energy sources by the method of hierarchy analysis is carried out in order to identify their level of prospects for use in complex systems of distributed generation. The general optimal structure of the electric power system of distributed generation is developed. A method for optimizing the composition of integrated distributed generation power systems with renewable energy sources based on expert analysis of energy efficiency and the potential for the development of modern alternative energy technologies in Ukraine is proposed. The application of the performed research will increase the reliability of distributed generation systems and their energy efficiency in the hybrid use of renewable energy sources, provided that the system control is fully automated and its structure is optimised.

Dual Timescales Voltages Regulation in Distribution Systems Using Data-Driven and Physics-Based Optimization

A large number of electric vehicles (EVs), distributed solar and/or wind turbine generators (WTGs) connected to distribution systems lead to frequent and sharp voltages fluctuations. The action rates of conventional adjustable devices and smart inverters are very different. In this context, a novel dual-timescale voltage control scheme is proposed by organically combining data-driven with physics-based optimization. On fast timescale, a quadratic programming (QP) for balanced and unbalanced distribution systems is developed based on branch flow equations. The optimal reactive power of renewable distributed generators (DGs) and static VAR compensators (SVCs) is configured on several minutes or seconds. Whereas, on slow timescale, a data-driven Markovian decision process (MDP) is developed, in which the charge/discharge power of energy storage systems (ESSs), statuses/ratios of switchable capacitors reactors (SCRs), and voltage regulators (VRs) are configured hourly to minimize long-term discounted squared voltages magnitudes deviations using an adapted deep deterministic policy gradient (DDPG) deep reinforcement learning (DRL) algorithm. The capabilities of the proposed method are validated with IEEE 33-bus balanced and 123-bus unbalanced distribution systems.

On the Possibility of Using CHP From a 1.4MW Direct Fuel Cell at Kettering University Engineering Building – A Demonstration Study

The concept of using a distributed power generation and a combined heat and power principle – CHP in public buildings, commercial facilities is widely gaining public acceptance as a result of reduced energy cost, reliable power supply and environmental and health issues. By using the exhaust heat from a high temperature fuel cell at 400 oC for cogeneration, space heating, to provide warm water for facility use - (swimming pool and sporting locker room) and cooling in chillers at no additional cost, we reduce energy cost and preserve the environment. By bottoming cycle, the efficiency of the entire system is increased. A study is conducted to compare the economic impact of using the CHP system against the conventional heating system using furnaces.

Combined Heat and Power (CHP) studies at the Flint Bio-Gas Complex Using a 1.4 MW Direct Fuel Cell – A Demonstration Study.

Future energy systems should include distributed power generation with combined heat and power. A study is conducted to evaluate the economic competitiveness of using a high temperature fuel cell with combined heat and power as a distributed power generation system against the conventional grid supplied power system at a sewage treatment facility. This report evaluates the economic benefits of using natural gas or biogas from the sewage treatment plant at the Flint-Biogas Complex to power a 1.4MW direct fuel cell which operates at a temperature of 400 oC. The waste recovery heat will be used for heating the sludge and the facility. Bottoming cycle options are proposed. The waste heat will be used to warm the sludge, heat up the reactants and provide warm water throughout the facility. This approach eliminates or reduces additional energy cost. The most important engineering and economic indicators would be used for evaluating the CHP system against the conventional furnace and power from the grid.

Influence of fault impedance on voltage quality in radial distribution systems with distributed synchronous generator: a sensitivity analysis

The power quality delivered to final consumers has deserved special attention on the part of the scientific community due to the increasing deterioration of voltage and current waveforms as a result of use of non-linear loads. Deployment of Distributed Generation Power is expected to have a range of effects (positive or negative) on the distribution grid. This paper presents a sensitivity analysis of voltage quality of a radial distribution system located in Guarulhos, Brazil, in a presence of a distributed synchronous generator in one of its bars. The sensitive analysis is done by varying the resistive fault impedance by considering the occurrence of different types of faults due to atmospheric discharging. The system is modelled and simulated in time domain through ATP software. It was verified that the impacts caused by the symmetrical and asymmetric faults on voltage levels are attenuated as the resistive fault impedance increases.