Decentralized Power Generation Research Articles

An Improved Residential Electricity Load Forecasting Using a Machine-Learning-Based Feature Selection Approach and a Proposed Integration Strategy

Load forecasting (LF) has become the main concern in decentralized power generation systems with the smart grid revolution in the 21st century. As an intriguing research topic, it facilitates generation systems by providing essential information for load scheduling, demand-side integration, and energy market pricing and reducing cost. An intelligent LF model of residential loads using a novel machine learning (ML)-based approach, achieved by assembling an integration strategy model in a smart grid context, is proposed. The proposed model improves the LF by optimizing the mean absolute percentage error (MAPE). The time-series-based autoregression schemes were carried out to collect historical data and set the objective functions of the proposed model. An algorithm consisting of seven different autoregression models was also developed and validated through a feedforward adaptive-network-based fuzzy inference system (ANFIS) model, based on the ML approach. Moreover, a binary genetic algorithm (BGA) was deployed for the best feature selection, and the best fitness score of the features was obtained with principal component analysis (PCA). A unique decision integration strategy is presented that led to a remarkably improved transformation in reducing MAPE. The model was tested using a one-year Pakistan Residential Electricity Consumption (PRECON) dataset, and the attained results verify that the proposed model obtained the best feature selection and achieved very promising values of MAPE of 1.70%, 1.77%, 1.80%, and 1.67% for summer, fall, winter, and spring seasons, respectively. The overall improvement percentage is 17%, which represents a substantial increase for small-scale decentralized generation units.

An evaluation on energy self–sufficiency model of a rural cluster through utilization of biomass residue resources: A case study in India

Lack of electricity access is a major deterrent to economic growth in rural areas of developing and underdeveloped countries. Until last decade, the government's focus for enhancing electricity access was on augmenting fossil fuels and increasing centralized grid infrastructure leading to environmental and economic concerns. This paper, through a case study (BB Nagar block, Uttar Pradesh, India) investigates biomass resources in a rural area for decentralized power generation to reduce the dependence on imported fossil fuels by making them self-sufficient for energy needs and mitigating greenhouse gas (GHG) emissions. The study outlines a methodology to evaluate regional biomass availability and its power generation potential and assess the associated uncertainties by considering different scenarios. It further estimates the GHG emissions from biomass power and compares them with biomass-equivalent coal-based power. Results for different scenarios show that biomass power potential in the block varies from 6783.7 to 21,852.5 kW, with a baseline potential of 10,637 kW.Similarly, GHG emissions saving potential by using biomass for power instead of coal varies from 33,267.8 to 106,459.5 t CO2eq.y−1 with a baseline saving of 51,956.4 t CO2eq.−1 (i.e., ~74% emission savings vis-à-vis coal). The biomass-based per-capita electricity potential for the block is estimated to be 655.1 kWh/capita, which is much higher than the current per-capita electricity consumption indicating that the block can be made self-sufficient using surplus biomass. The paper also highlights the obstacles that exist in the introduction of biomass as a replacement of fossil fuels and suggests recommendations for its greater implementation as a resource for power generation. The findings can help boost decentralized planning for energy self-sufficiency in rural areas by mapping bioenergy and emissions profiles covering diverse feedstocks.

Medium-Term Regional Electricity Load Forecasting through Machine Learning and Deep Learning

Due to severe climate change impact on electricity consumption, as well as new trends in smart grids (such as the use of renewable resources and the advent of prosumers and energy commons), medium-term and long-term electricity load forecasting has become a crucial need. Such forecasts are necessary to support the plans and decisions related to the capacity evaluation of centralized and decentralized power generation systems, demand response strategies, and controlling the operation. To address this problem, the main objective of this study is to develop and compare precise district level models for predicting the electrical load demand based on machine learning techniques including support vector machine (SVM) and Random Forest (RF), and deep learning methods such as non-linear auto-regressive exogenous (NARX) neural network and recurrent neural networks (Long Short-Term Memory—LSTM). A dataset including nine years of historical load demand for Bruce County, Ontario, Canada, fused with the climatic information (temperature and wind speed) are used to train the models after completing the preprocessing and cleaning stages. The results show that by employing deep learning, the model could predict the load demand more accurately than SVM and RF, with an R-Squared of about 0.93–0.96 and Mean Absolute Percentage Error (MAPE) of about 4–10%. The model can be used not only by the municipalities as well as utility companies and power distributors in the management and expansion of electricity grids; but also by the households to make decisions on the adoption of home- and district-scale renewable energy technologies.

Investigation on the combustion characteristics of different plant parts of Cassia siamea by DSC-TGA

Plant parts like root, wood, twig and leaf of Cassia siamea, a fast-growing tree in the abandoned mines of Jharkhand, India, have been considered here as a possible fuel source for decentralized power generation. This is a low greenhouse gas emission pathway to cater the electricity need of the adjoining locality. Seasonal availability of the plant parts originated interests of studying the basic combustion characteristics of the plant parts separately. Finding out the roles of cellulose and lignin to regulate the combustion behavior of plant parts was another objective. Cellulose and lignin were extracted from each plant part, and their burning performances were evaluated against those of respective plant parts with the help of DSC-TGA. Cellulose and lignin were found to influence the combustion processes of plant parts differently. Lignin in case of leaf combustion and cellulose for wood combustion regulated the combustion process. Both lignin and cellulose were competitive in regulating the combustion of twig and root. Burning characteristics of cellulose or lignin extracted from different plant parts varied. Higher heating value (HHV) was low for celluloses (~ 16.8 ± 1 MJ kg−1) as compared to lignin (HHV ~ 23.0 ± 1 MJ kg−1). Leaf having substantial lignin and extractives showed the highest HHV around 23.5 MJ kg−1, while the lowest HHV (16.0 MJ kg−1) was observed for wood. Results are interesting for considering each plant part as a single fuel or as a potential component of coal–biomass blended fuel, where locally available low-grade high ash coal may be the other component.

Performance Benchmark of Planar Solid Oxide Cells Based on Material Development and Designs

Solid oxide cell (SOC) technology currently attracts great attention due to its unique potential for substantially contributing to a carbon‐neutral power supply. The variety in possible designs and applications—covering oxygen ion and proton conductors and the ability to convert surplus electricity to easily storable synthetic fuels, as well as to produce electricity from these fuels according to demand and availability—provides the excellent position of SOCs with regard to decentralized power generation and distribution. Herein, a reference work on cell performance is provided by highlighting specific advantages of the different cell types, designs, and materials with regard to certain operating conditions, including challenges concerning operational modes, processing, and degradation. In conjunction with a critical examination in terms of relevance and technical feasibility, the data provided enable an assessment of the general potential of the cell types for technology development and connect scientific research to industrial considerations.

Investigation on the yield of producer gas from tamarind shell (Tamarindus Indica) as feedstock in an Imbert type biomass gasifier

Thermochemical gasification technology is given priority in recent years to meet the needs of decentralized power generation, and also to develop alternative energy sources for conventional thermal applications. The continuous operation of a gasifier becomes a challenge when there is scarcity for specific type of biomass in a particular region. To overcome this challenge and to establish gasification technology in rural areas, the suitability of gasifier in making use of commonly available biomasses in a region must be confirmed. Tamarind tree is common in many countries and the shell of its fruit can be a promising feedstock for a gasifier. Therefore, yield and CV of the producer gas during the thermochemical conversion of TS, in an Imbert-type gasifier are studied in this paper. The performance parameters are analysed to check whether the values are in accordance with the specifications of the gasifier. In this study, Species-transport CFD model is used to forecast the reliability of a gasifier, and an experimental study is also conducted to confirm the predictions and to identify operational issues. The result shows that the best equivalence ratio is 0.30. At this condition, the average CV and yield of producer gas are 5.76 MJ/Nm3 and 1.95 Nm3/kg. Moreover, the CO2/CO ratio and the conversion efficiency are 0.69 and 78.23% respectively. The coherence of the predicted values with the specifications of the gasifier, and also the observations noted during experimentation, confirms that TS could be an appropriate feedstock for the tested gasifier.

A pathway towards sustainable development of small capacity horizontal axis wind turbines – Identification of influencing design parameters & their role on performance analysis

Presently small wind turbines are receiving greater attention, due to the extensive promotion of decentralized power generation in a sustainable way by national and international organizations. However, there are many obstacles in commercializing these turbines on a large scale due to lower efficiencies of turbines associated with high vibrational losses, lack of technical knowledge with the manufacturers, cost criteria and lack of awareness among the end-users. This paper reviews the research works done in the design and development of small wind turbine blades, including diffusers and winglets addition. Performance & parametric analysis of airfoils, blades & wind turbines are presented comprehensively. Impact of maximum power point technique, effects of ambiance on the turbine performance, environmental impacts of small wind turbines and some novel concepts are presented in this review. Future research works to enhance the efficiency of small wind turbines using materials with high strength to weight ratio would pave the way for efficient utilization of available wind energy in the earth’s crust.

Spent tea waste as a biomass for co-gasification enhances the performance of semi-industrial gasifier working on groundnut shell

An effective utilization of agricultural waste as an energy source for decentralised power generation and thermal applications can meet the increasing energy demand in rural areas. A substantial number of thermo-chemical conversion systems are used for this purpose; nevertheless, it is significant to improve their efficiency to widen the implementation of this technology for various applications. Groundnut shell is one of the popular agricultural wastes available in many countries like India. Due to its low bulk density and physical nature co-gasification of this feedstock with another biomass is not popular. However, a high carbonaceous powdery biomass like Spent Tea Waste (STW), a waste after brew tea can be suitably mixed with groundnut shell along with some moisture to accomplish this task. To prove this strategy an experimental study has been conducted at various combinations of these two types of biomass as feedstock in a 115 kWth semi-industrial type gasifier, and its performance parameters are studied for possible operating conditions of the gasifier. The observations show that the wet STW can maintain a uniform consistency, when mixing both the biomasses until its composition is 40% of the blend. The results show that the increase in hydrogen composition, calorific value and cold gas efficiency is in the ranges of 9.9–21.5%, 4.1–10.4% and 3.9–9.9% respectively as compared to groundnut shell. Besides, the maximum calorific value of producer gas is 6.68 MJ m−3.

Применение асинхронизированных генераторов в электрических сетях с пониженным качеством электроэнергии

For decentralized power generation, small-capacity asynchronized generators (AGs) can be used, which are able to yield a number of positive effects in comparison with conventional synchronous machines: higher stability limits, wider reactive power adjustment ranges, simpler synchronization with the grid due to the ability to control the EMF phase, and the possibility to maintain synchronous operation in case of failure in one of the field windings. The article describes the model of a grid equipped with asynchronized generators with automatic excitation and rotor speed control systems, which is developed in the MATLAB software package environment. Normal and emergency operation modes of a 35 kV grid with distributed generation plants based on asynchronized machines under the conditions of degraded electric power quality due to the presence of electric traction loads are simulated. The influence of AGs on emergency and post-emergency modes are determined, and the harmonic distortion levels are estimated. For comparison, the grid operation modes are simulated for the case of using synchronous machines as generation sources. The influence of higher harmonic components on the performance of the proposed automatic control system is analyzed. The obtained study results have shown that with using asynchronized generators, better control processes and better quality of electric power are obtained in comparison with those in a grid equipped with synchronous machines; in addition, the stability limits are increased, and the synchronization processes are simplified.

Demand Response Management Algorithm for Distributed Multi-Utility Environment in Smart Grid

Effective usage of Information and Communication Technologies (ICT) has started with a paradigm shift in the energy management and functioning of the conventional power grid. It also aids in the maintenance of the complete information about consumer usage pattern, power storage, supply and regulation. Blending of information and communication technologies with energy management creates a smart grid environment which makes it move to the next horizon. The smart grid environment, uplifts renewable energy sources and brings out novel strategies in the energy market. The new functioning of the energy market attracts more utility companies for decentralized power generation and optimizes the power price for the consumer. The consumer plays an active role in the demand response modelling to maximize the welfare of the utility and to obtain the optimized price for their demand. In this paper, a novel demand response management scheme is proposed for multi-utility environment. The utility companies function in a peer to peer manner to communicate effectively and to select a specific utility from a set of utilities for the power supply. The selection of single utility is based on a non-cooperative game theory algorithm where the demand and generated power should be balanced to maximize the welfare of the utility and the residential consumers. The power price can be updated in an equal interval to allow all the utilities to participate in the Distributed Multi-Utility Demand Response Management (DMDRM) system. The simulated results justify that the distributed noncooperative game theory algorithm certainly maximizes the welfare of the utility companies and residential consumers.

A Multidimensional High-Resolution Assessment Approach to Boost Decentralised Energy Investments in Sub-Saharan Africa

There are over 650 million people in Africa who have no access to electricity; this is in sharp contrast to the continent’s vast untapped renewable energy potential and reflected by the lack of investments in energy infrastructure. New investments in decentralised power generation within Sub-Saharan African play a progressively important role in increasing energy access and addressing the continent’s electricity supply shortages. Tracking the performance of Sub-Saharan African countries along various socio-political and economic axes can spur the mobilisation of private, public and international sectors in decentralised energy technologies. An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key multidimensional indicators are mainly still independently provided only at national level. To this end, we present a comprehensive and consistent analysis of the attractiveness for decentralised photovoltaic technologies at an unprecedented level detail. We develop and build a new composite indicator that considers the interplay between social, political, environmental and financial factors at a granular regional level for Sub-Saharan Africa and embeds within it the importance of the local production costs at high-spatial resolution.

Proposed Fuzzy Logic System for Voltage Regulation and Power Factor Improvement in Power Systems with High Infiltration of Distributed Generation

Recently, the awareness of the severe consequences of greenhouse gases on the environment has escalated. This has encouraged the world to reduce the usage of fossil fuels for power generation and increase the use of cleaner sources, such as solar energy and wind energy. However, the conventional power system itself was designed as a passive power system, in which power generation is centralised, and power flows from substations towards the loads. Decentralised renewable energy sources, also called distributed generators, were introduced to create an active power system in which power generation can occur anywhere in the power system. Decentralised power generation creates challenges for the conventional power system, such as voltage fluctuations, high voltage magnitudes, reverse power flow, and low power factor. In this paper, an adaptive control system that coordinates different distributed generators for voltage regulation and power factor correction is introduced and designed. The control system will decrease the total reactive power that flows in the transmission network through a reactive power exchange between distributed generators. Therefore, power factor will improve, power system losses will reduce, and the total apparent power on lines will reduce, giving more room to active power to flow. The results obtained showed that the control system is effective in regulating voltage and improving the power factor when multiple distributed generators are connected.

Implementation of Distributed Generation with Solar Plants in a 132 kV Grid Station at Layyah Using ETAP

Decentralized power generation efficaciously merges technological advances in a rapidly changing face of power networks introducing new power system components, advanced control, renewable sources, elegant communication, and web technology paving the way for the so called smart grids. Distributed generation technology lies at the intersection point of power systems, power electronics, control engineering, renewable energy, and communication systems which are not mutually exclusive subjects. Key features of renewable integration in a distribution network include loss minimization, voltage stability, power quality improvement, and low-cost consumption resulting from abundant natural resources such as solar or wind energy. In this research work, a case study has been carried out at a 132 kV grid station of Layyah, Pakistan, which has active losses, reactive losses, low power factor, low voltage on the demand side, and overloaded transformers and distribution lines. As a result, power outage issue is frequent on the consumer side. To overcome this issue, a simulation of load flow of this system is performed using the Newton-Raphson method due to its less computational time, fewer iterations, fast convergence, and independence from slack bus selection. It finds the harsh condition in which there were 23 overloaded transformers, 38 overloaded distribution lines, poor voltage profile, and low power factor at the demand side. There is a deficit of 24 MW in the whole system along with 4.58 MW active and 12.30 MVAR reactive power losses. To remove power deficiency, distributed generation using solar plants is introduced to an 11 kV distribution system with a total of 24 units with each unit having a capacity of 1 MW. Consequently, active and reactive power losses are reduced to 0.548 MW and 0.834 MVAR, respectively. Furthermore, the voltage profile improves, the power factor enhances, and the line losses reduce to a great extent. Finally, overloaded transformers and distribution lines also return to normal working conditions.

Modelling and compensation of dead time in three-phase dual-active bridge DC-DC converter

ABSTRACT With growing decentralized power generation, medium-voltage (MV) dc-dc converters are becoming increasingly important. A three-phase dual-active bridge (DAB3) is a promising topology for high-power MV applications. The semiconductor devices used in such converters at multi-megawatt level tend to be slow in switching. Hence, a considerable dead time between switching instants is required to avoid shoot-through in phase legs. This dead time forces the current to commutate to the freewheeling diodes and introduces a current dependence of the phase voltages. In this work, the effects of dead time on the operation of DAB3 are analysed in detail. The derived analytical expressions are used in the control development to compensate for the effects of dead time and hence achieve superior control performance. Measurements are carried out on a small-scale laboratory prototype to validate the derived operational modes and the effectiveness of the proposed dead time compensation.

Design, manufacture and test of a micro-turbine renewable energy combustor

The ever-increasing demand on highly efficient decentralized power generation with low CO2 emission has made microturbines for power generation in micro gas turbine (MGT) systems popular when running on biofuels as a renewable source of energy. This document presents a state-of-the-art design, and optimization (in terms of design, performance and emission control) of a micro-turbine renewable energy combustor that fits into the existing Bladon 12kWe recuperated microturbine plenum while running on a range of biofuels as it can successfully provide the required power of the MGT. Governing equations for in-depth analysis of the combustor consist of manufacturer empirical data to simulate system-level operation with respect to replacement of the fossil with biofuels. The Model developed and validated at the company’s ISO conditions confirms the output power of the new combustor fits the conventional system with slight eco-energy improvements. The modeling of the combustor in a complete microturbine assembly system is performed, then was utilized to further analysis of the microturbine with the designed combustor. The results gave on average 46.7% electrical efficiency, 83.2% system efficiency, 12 kWe electrical power, and 90% recuperator effectiveness at nominal operating conditions of microturbine (MT). Sensitivity analyses evaluate changes in performance with respect to fuel phase (e.g., liquid or gaseous) and design variables (e.g., orientation, shape, and dimensions of combustor), leading to energy optimization of the unit. Findings demonstrate that the combustor in microturbine can meet the target performance specifications of a company conventional diesel microturbine with significant savings. An objective function including both combustor and recuperator technical energy data is defined for finding the best ratio of fuel and air and their flow rates to find the most effective operating points for the operation of MT. Annual time series simulations completed for Coventry, West Midlands, United Kingdom indicate a new combustor can reduce operational costs of diesel fuel combustor by 8%, 2%, 36%, and 25% when supplying bioethanol, DME, biogas, and NG, respectively. Annual operating time of the renewable microturbine combustor at rated capacity included an 11% reduction in exergy loss with biogas fuel relative to diesel fuel.

Reduction of Cold-Start Emissions for a Micro Combined Heat and Power Plant

Decentralized power generation by combined heat and power plants becomes increasingly popular as a measure to advance the energy transition. In this context, a substantial advantage of small combined heat and power plants is based on the relatively low pollutant emissions. However, a large proportion of the pollutant emissions is produced during a cold-start. This fact is not reflected in governmental and institutional emission guidelines, as these strongly focus on the emission levels under steady-state conditions. This study analyzes the spark advance, the reference air/fuel ratio and an electrically heated catalyst in terms of their potential to reduce the cold-start emissions of a micro combined heat and power plant which uses a natural gas fueled reciprocating internal combustion engine as prime mover and a three-way catalytic converter as aftertreatment system. Based on these measures, control approaches were developed that account for the specific operating conditions of the class of small combined heat and power plants, e.g., full-load operation and flexible, demand-driven runtimes. The experimental data demonstrates that even solutions with marginal adaptation/integration effort can reduce cold-start emissions to a great extent.

Statistical Assessment of Whale Optimization Algorithm for Sizing and Placement of DG Considering Multi-Objective Function with PSO and CSA Algorithm

Distributed or decentralized power generation (DGEN) technology is popularized in the 21st century and it emerged has an effective alternative solution to meet the forecasted energy demand for restructured power system by putting restriction on power plants and transmission lines of the of the next decade generation. Modified state policies and increased technological innovation for low-capacity production promotes increased development and investment of DGEN. The use of distributed renewable energy generation has been driven by environmental concerns. DGEN's incorporation into the distribution side of the network offers critical system advantages such as voltage assistance support, reduction in loss, transmission power increase, strengthened system performance, etc.This paper presents the optimized DG placement (ODGP) and sizing solution in distribution side of the network for the multiobjective formulation includes the objective of minimizing the losses, maximization of voltage stability and also includes the cost requirement. The new Meta-heuristic based Approach named as Whale optimization algorithm is used for optimal placement and Sizing of DGEN is considered in this work and the solution of the proposed optimization algorithm is compared with two most popular optimization techniques such as Particle Swarm Optimization (PSOA), Cuckoo Search Algorithm (CSOA). The comparative analysis of these above said optimization techniques is developed and compared for performance comparison can be done with 69 bus IEEE standard radial system to validate the results of the proposed multi objective problem.

Analysis of interactions between regulated distribution transformers (RDT) and local voltage control Q(V) by means of the harmonic balance method

The increase of decentralized power generation in low voltage grids imposes new challenges on the conventional operating strategies for electrical grids, as power transmission used to predominantly pass from high voltage levels to low voltage levels. Distributed generation in low voltage grids lead to unprecedented voltage limit violations, which can efficiently be solved by implementing new control systems e.g. regulated distribution transformers (RDT) or local voltage control (e.g. Q(V)). Both correspond to closed-loop control systems and thus, are prone to stability issues and possible interactions with other control elements. Furthermore, the nonlinear characteristics of RDTs complicate the systems' stability analysis. This paper introduces the harmonic balance method as an approach to characterize the nonlinear behavior of an RDT and assess the system stability as well as possible interactions with other linear controllers in the electrical grid.

Assessment and Scope of Decentralised Power Generation Using Renewable Energy Resources

Decentralized power generation is an alternative and reliable resource of energy where the domestic electricity grid fails to provide rural communities with a reliable supply of electricity. We have more dependent on conventional sources like coal and petroleum fuels to generate energy, it is a determinate resource and also primes to GHG discharges and toxins in our air and water. Renewable energy sources like biomass, biogas, solar photovoltaic, hydro and wind are available abounded in nature.it also shields our world by considerably dipping the number of carbon emissions that we produce. These vitalities can be expended as separate or in a permutation of these resources known as a hybrid renewable energy system (HRES). We can also combine diesel generator with HRES as per the load demand and availability of the resources. The various case studies are reviewed related to the need for electricity in rural areas, benefits of decentralized energy generation, hybrid renewable energy system to fulfill household needs, to light up rural lives by off-grid electricity generation and employment opportunities to local youth, etc. which are optimized with the help of different software like HOMER, LINDO, HYPORA, VIPOR, etc. Performance of these hybrid systems can be compared on the basis of parameters like cost of energy (COE), net present cost (NPC), levelised cost of energy (LCOE), Levelised unit electricity cost (LUEC), Per unit electricity cost (PUEC) and Life cycle cost (LCC) with respect to grid-connected systems and extension of grid. The purpose of this work is to propose the best hybrid technology combination for energy production from a blend of RE sources to sate the energy essential of an off-grid village which is cost-effective, sustainable, techno-economically viable and environmentally sound.

Design and analysis of a new axial flux permanent magnet synchronous generator for wind

The paper deals with a new design of a low-speed disk permanent magnet axial flux synchronous machine for decentralized power generation, which has improved weight-size parameters. In the new design the value of the air gap value is reduced by removing all inter-coil connections from the gap and also a concentrated winding with a high winding coefficient is applied. A two-rotor prototype of this design is created (150 W, 83 V, 250 rpm) and its magnetic circuit and the concentrated windings arrangement are described, as well as the results of the machine experimental study. The 2D finite element analysis is used to determine the effect of the air gap value effect on the disk slotless generator parameters. The method of rational choice of the machine main dimensions and the parameters of its winding according to nominal data and electromagnetic loads limitations are presented. Comparison of parameters and characteristics of a 20-pole-pair 5 kW synchronous wind generator with the new design and cylindrical one with tangential magnetization is performed. The proposed slotless design exceeds the cylindrical one in efficiency and requires less material costs. The limitations are the higher value of the outer machine diameter and the required large magnets mass.