Renewable-based Power Research Articles

Optimum Design of a Renewable-Based Integrated Energy System in Autonomous Mode for a Remote Hilly Location in Northeastern India

Integration of a grid with an under-developed remote hilly area faces various technical and geographical challenges. Thus, generation of power from renewable resources in off-grid conditions has become one of the most cost-effective and reliable solutions for such areas. The present research deals with the possible application of an integrated solar/hydro/biomass/battery-based system to generate power in autonomous mode for a remote hilly town of a northeastern Indian state. Four different cases of the integrated energy system (IES) were designed using the hybrid optimization model for electric renewable (HOMER Pro), examining the performance of each case. The best combination of the integrated system was chosen out of several cases depending upon the optimized solution that can meet the load demand of the proposed hilly town sustainably, reliably and continuously. The simulation results show that the integrated battery/biomass/hydro/solar-based system is the best optimized, cheapest and most suitable solution to generate renewable-based power for the specified location, having the lowest net present cost (NPC) of USD 644,183.70 with a levelized cost of energy (COE) of 0.1282 USD/kWh. Further, the result also indicates that the optimized configuration reduces the emission of CO2 gas in the environment compared to the battery/biomass/hydro system having the worst emission rate. A sensitivity study was also carried out with variation in load, hydro stream flow and solar irradiation, respectively that may largely affect the technical as well as economical aspect of an integrated energy system.

Dual-mode Switching Fault Ride-through Control Strategy for Self-synchronous Wind Turbines

The installed capacity of renewable energy generation has continued to grow rapidly in recent years along with the global energy transition towards a 100% renewable-based power system. At the same time, the grid-connected large-scale renewable energy brings significant challenges to the safe and stable operation of the power system due to the loss of synchronous machines. Therefore, self-synchronous wind turbines have attracted wide attention from both academia and industry. However, the understanding of the physical operation mechanisms of self-synchronous wind turbines is not clear. In particular, the transient characteristics and dynamic processes of wind turbines are fuzzy in the presence of grid disturbances. Furthermore, it is difficult to design an adaptive fault ride-through (FRT) control strategy. Thus, a dual-mode switching FRT control strategy for self-synchronous wind turbines is developed. Two FRT control strategies are used. In one strategy, the amplitude and phase of the internal potential are directly calculated according to the voltage drop when a minor grid fault occurs. The other dual-mode switching control strategy in the presence of a deep grid fault includes three parts: vector control during the grid fault, fault recovery vector control, and self-synchronous control. The proposed control strategy can significantly mitigate transient overvoltage, overcurrent, and multifrequency oscillation, thereby resulting in enhanced transient stability. Finally, simulation results are provided to validate the proposed control strategy.

Investigating the participation of battery energy storage systems in the Nordic ancillary services markets from a business perspective

Battery energy storage systems (BESSs) are gaining potential recognition in renewable-based power systems. To maintain the stability of such systems, BESSs units are being deployed for the provision of ancillary services (ASs). For BESS owners, it is vital to assess the business value of providing ASs to engage in a profitable trade. However, studies so far have mainly focused on the operational control of BESS units in ancillary services markets (ASMs) while ignoring investigations from a business viewpoint. Therefore, in this paper, we analyse the BESS-based provision of Nordic ASs from a BESS-business perspective. To this aim, we identify the profitable bidding hours for the BESS units by investigating hourly patterns in the market prices of the past six years. We also analyse the monthly and yearly trends in historic price datasets of ASs to help BESS owners develop long-term business plans. Moreover, for the BESS owners to choose between different markets, we investigate the revenue streams associated with each ASs and determine the yearly income from their availability and capacity payments. Our findings imply that BESS business viability in the Nordic ASMs can be increased by stacking ASs based on their availability payments, energy content, and activation requirements.

A Comparative Review on Energy Storage Systems and Their Application in Deregulated Systems

Electrical energy is critical to the advancement of both social and economic growth. Because of its importance, the electricity industry has historically been controlled and operated by governmental entities. The power market is being deregulated, and it has been modified throughout time. Both regulated and deregulated electricity markets have benefits and pitfalls in terms of energy costs, efficiency, and environmental repercussions. In regulated markets, policy-based strategies are often used to deal with the costs of fossil fuel resources and increase the feasibility of renewable energy sources. Renewables may be incorporated into deregulated markets by a mix of regulatory and market-based approaches, as described in this paper, to increase the systems economic stability. As the demand for energy has increased substantially in recent decades, particularly in developing nations, the quantity of greenhouse gas emissions has increased fast, as have fuel prices, which are the primary motivators for programmers to use renewable energy sources more effectively. Despite its obvious benefits, renewable energy has considerable drawbacks, such as irregularity in generation, because most renewable energy supplies are climate-dependent, demanding complex design, planning, and control optimization approaches. Several optimization solutions have been used in the renewable-integrated deregulated power system. Energy storage technology has risen in relevance as the usage of renewable energy has expanded, since these devices may absorb electricity generated by renewables during off-peak demand hours and feed it back into the grid during peak demand hours. Using renewable energy and storing it for future use instead of expanding fossil fuel power can assist in reducing greenhouse gas emissions. There is a desire to maximize the societal benefit of a deregulated system by better using existing power system capacity through the implementation of an energy storage system (ESS). As a result, good ESS device placement offers innovative control capabilities in steady-state power flow regulation as well as dynamic stability management. This paper examines numerous elements of renewable integrated deregulated power systems and gives a comprehensive overview of the most current research breakthroughs in this field. The main objectives of the reviews are the maximization of system profit, maximization of social welfare and minimization of system generation cost and loss by optimal placement of energy storage devices and renewable energy systems. This study will be very helpful for the power production companies who want to build new renewable-based power plant by sighted the present status of renewable energy sources along with the details of several EES systems. The incorporation of storage devices in the renewable-incorporated deregulated system will provide maximum social benefit by supplying additional power to the thermal power plant with minimum cost.

Province-level techno-economic feasibility analysis of baseload supply from hybrid renewable energy systems in China

To promote the large-scale deployment and grid integration of renewable-based power system, this paper investigates the province-level techno-economic feasibility of wind-photovoltaic-battery hybrid renewable energy system (HRES) for baseload supply application around China. Firstly, the power generation cost and grid parity potential of province-level standalone wind and photovoltaic power plants are assessed. Then, the optimal sizing of province-level HRESs aims to minimize the net present cost and meet the reliability constraint for baseload supply, which is solved by teaching and learning-based optimization. Finally, the techno-economic comparison between different system configurations, the correlation between HRES cost-effectiveness and resource potential as well as resources complementarity, and the grid parity potential of HRES for baseload supply are quantitatively analyzed. The results reveal that: (i) 84.4% of regions in China can achieve solar photovoltaic plant-side grid parity in 2022, while only 15.6% of regions can achieve wind power plant-side grid parity; (ii) HRESs in all regions are technically feasible but not cost-effective for baseload supply; (iii) wind-photovoltaic-battery HRES is the optimal configuration for most regions, indicating that the wind-solar hybridization is more reliable and cost-effective than standalone power plants; (iv) the economic performance of HRES depends mainly on the wind-solar joint resource potentials and the supply-demand relative deviation; (v) investment cost reduction and utilization of energy curtailment are promising to help HRES achieve plant-side grid parity for baseload supply. The findings of this paper can help policy-makers and investors optimally determine the national pathway of renewable energy transition.

Exergoeconomic analysis and optimization of a high-efficient multi-generation system powered by Sabalan (Savalan) geothermal power plant including branched GAX cycle and electrolyzer unit

Employing suitable subsystems to reach high efficiency and low cost in renewable-based power plants is more crucial. The geothermal energy heat source is located in many countries, but this has never been investigated to run a multi-generation system, including a branched GAX cycle and an electrolyzer. In this path, a high-efficient multi-generation system powered by a Sabalan (Savalan) geothermal power plant consisting of a single flash cycle, a branched GAX cycle, and an electrolyzer is presented and scrutinized from thermodynamic and exergoeconomic viewpoints. In the end, a two-objective optimization, by using the Total Unit Cost of Product (TUCP) and energy efficiency as objectives, is utilized to find the optimum operating conditions. Critiques and studies of variables reveal that the produced hydrogen rate remains unchanged at 5.655 kg/h by changing the degassing value and temperature of the generator, condenser 2, and evaporator. By increasing the flash tank pressure from 5.2 bar to 7 bar, the cooling and heating loads rise about 108.4%, while the net electricity falls from 3977 kW to 3506 kW. Interestingly, the TUCP has a minimum value at the evaporator temperature of 273 K and condenser 2 temperature of 322.3 K. The optimization results indicate the values of the produced hydrogen rate and net electricity with 5.85 kg/h and 4187 kW are more than those of the base case. Also, the optimal values are 7.046 $/GJ, 36.82%, and 65.42% for the TUCP and energy and exergy efficiencies, respectively.

Carbon-Oriented Expansion Planning of Integrated Electricity-Natural Gas Systems With EV Fast-Charging Stations

Under the pressure of climate change and the energy crisis, electric vehicles (EVs) have experienced a marked growth in many countries recently. However, the environmental benefits of EVs cannot be achieved if the charging power from the electricity grid is still mainly provided by fossil-fueled power plants. How to construct a low-carbon fast-charging system has become an emerging research topic. In this context, a novel carbon-oriented expansion planning model of the integrated electricity and natural gas system (IEGS) with EV fast-charging stations (FCSs) is proposed to determine the optimal alternatives, locations, and sizes for ecofriendly candidate assets, including roof-top photovoltaic (PV) panels and fuel cell (FC) units in each FCS, as well as renewable energy units and carbon capture and storage (CCS) systems in IEGS. To guarantee the carbon reduction performance of the planning scheme, the carbon emission cap of the EV charging system is specified by the planner and optimally allocated among multiple FCSs according to their carbon reduction abilities. Furthermore, the proposed model can not only consider the initial investment and operation costs but also take into account the expected adaptation cost to future scenarios that are generated in line with three uncertainties, namely, the traffic flow levels, conventional load levels, and renewable-based power generation levels. Finally, the proposed expansion planning method is illustrated by conducting numerical experiments in case studies.

Transient stability and FRT technologies of different synchronous wind turbine

With the global energy transformation towards to a 100% renewable-based power system, the installed capacity of renewable energy generation has continued to grow rapidly in recent years. At the same time, due to the loss of synchronous machines, the grid-connected large-scale renewable energy bring great challenges to the safe and stable operation of power grid. In order to improve the stability of power grid, different synchronous wind turbine have widely attracted the attention of academia and industry. That is totally different on transient stability of vector synchronous wind turbine and self-synchronous wind turbine, and the fault ride through (FRT) control strategy is also different. Thus, the transient stability and FRT technologies of vector synchronous wind turbine and self-synchronous wind turbine are studied separately. There are many solutions for the FRT of vector synchronous wind turbine from different technical schemes. According to the different scope of application and implementation methods, it can be roughly divided into two categories: software improvement and hardware addition. Different FRT strategy of self-synchronous wind turbine are used under a smaller grid fault and serious grid fault, self-synchronous wind turbine recalculate the voltage and phase angle of the potential in the converter according to the PCC voltage, PCC phase angle, reactive power demand and residual active capacity under a smaller grid fault. When there is serious grid fault, the vector control and self-synchronous control modes switching FRT strategy is necessary.

Effects of the hydropower regulation on dynamic stability of a renewable-based power system

Renewable energy, particularly solar photovoltaic power integrated with hydropower, has become a remedy for replacing conventional electricity to provide important opportunities for the safety utilization of electric power. However, the solar photovoltaic power is intermittent and stochastic due to the uncertain solar irradiance, which can lead to the unstable operation of the complementary power system. For this consideration, this paper focuses on the stability mechanism of the hydropower regulation responding to the volatility of solar photovoltaic power. To achieve the analysis, a hydro-PV hybrid power system is established. Then, the effect of the hydropower regulation on dynamic stability of a hydro-photovoltaic hybrid system is investigated considering two hydropower regulation factors such as the optimization of hydropower control parameters and the performance of dynamic hydro regulation indicators. Finally, the optimized proportional, integral and derivative adjustment parameters are obtained, and the dynamic rule of regulation indicators responding to the volatility of photovoltaic power is also revealed. The obtained results not only help make an optimal decision for the coordinated operation of renewable-based power systems, but also benefit for the reduction of the operational cost and power curtailment.

Variable structure model predictive controller based gain scheduling for frequency regulation in renewable based power system

AbstractThis paper presents a load frequency control (LFC) design using the variable structure model predictive controller (VSMPC) for gain scheduling (GS) of PI controller in PV connected thermal for multi‐area system. Due to the increasing impact of renewable energy sources into the grid system, the system frequency deteriorates. The proposed PV connected thermal system is evaluated under varying load conditions under increased penetration of the PV source. The combination of renewable energy into the thermal power system aggravates the frequency and it is indispensable to mitigate such a problem by introducing an optimal controller. Perturbation in load greatly affects the system frequency and this problem is addressed by using VSMPC based gain scheduling knowing the effect of proportional and integral in transient and steady‐state conditions. The oscillations in frequency are controlled by a proposed controller and the impact of frequency under penetration of PV is monitored. Further verification of the proposed technique is accomplished through communication delay in the governor and turbine. The Hardware in the loop (HIL) which validates the accuracy and real time performance of the controller. Finally, the validation of the proposed controller is compared with MPC to tune PI controller and renowned evolutionary tuned techniques like particle swarm optimization (PSO), genetic algorithm (GA) and firefly algorithm (FA) to optimize PI controller. The VSMPC with GS of PI controller shows promising results.

An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.

Power-balancing Coordinated Control of Wind Power and Demand-side Response Under Post-fault Condition

As the global energy transforms to renewable-based power system, the wind power generation has experienced a rapid increase. Due to the loss of synchronous machines and its frequency control mechanisms, the gradual evolution leads to critical challenges in maintaining the frequency stability. Under post-fault condition, the wind power generation has a slow recovery due to the fault ride-through (FRT) control strategy and may cause a larger frequency deviation due to the power imbalance between the supply and demand. Then, the impacts of the frequency deviations would further cause inaccuracy and instability in the control system for wind power generation. Considering the long parking time of electric vehicles (EVs), the demand-side response is provided to support the power grid via load-to-grid technology. Thus, a power-balancing coordinated control strategy of the wind power and the demand-side response is developed. It can significantly mitigate the power imbalance, thereby resulting in the enhanced frequency stability. Finally, the simulation results are provided to validate the power-balancing coordinated control strategy.

Activating Electrolytic Hydrogen in Renewable-Based Power Systems for a Hydrogen Economy

Activating Electrolytic Hydrogen in Renewable-Based Power Systems for a Hydrogen Economy

Flexibility Potential of a Smart Home to Provide TSO-DSO-level Services

The high penetration of intermittent renewable-based power into modern power systems increases the need for more technical ancillary services from flexible energy resources. Smart homes could provide different flexibility services related to active power control services and therefore fulfill a part of the flexibility needs of system operators. In this regard, the estimation of the flexible capacities of each smart home's flexible device is of key importance. Correspondingly, this paper first estimates the flexible capacities of a smart home with controllable devices as flexible resources. The flexible capacity of each appliance is estimated considering its flexible and non-flexible operations. Besides, the local and system-wide flexibility services are introduced and the paper discusses whether a smart home can provide these types of services. In the simulations of this paper, the flexible capacity of each household appliance is estimated and compared to each other. Finally, the profitability of the smart home's battery energy storage multi-use is analyzed when it is providing three different types of flexibility services for the transmission system operator's needs. The results demonstrate that in some scenarios, the smart home's battery energy storage can increase its profits by providing transmission-system-level flexibility.

Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

Two-objective optimization of a hybrid solar-geothermal system with thermal energy storage for power, hydrogen and freshwater production based on transcritical CO2 cycle

In the light of increasing negative impacts on environment of fossil fuels, development of renewable energy utilization is a high priority. In this regard, hybridization of geothermal and solar energies (as two types of abundant renewable resources) has been proved to be a promising combination for renewable-based power generation systems. For power generation from low-grade renewable resources, the transcritical CO2 (TRCC) power cycle has been considered as an ambitious competitor against ORC and Kalina cycle. This paper aims at development and proposal of a novel efficient trigeneration system based on TRCC cycle for production of power, hydrogen, and freshwater driven by hybrid solar-geothermal energies. In proposed system, thermoelectric generators and HDH desalination unit are employed for waste heat utilization of TRCC cycle. Thermodynamic and thermoeconomic analyses and two-objective optimization are conducted and monthly performance of the system is estimated for real environmental data. Results showed that, the system yields highest values of power, hydrogen and freshwater in May, respectively as 1286 kW, 1.989 kg/h, and 13.38 m3/day. Under the optimized conditions, the system yields energy efficiency of 23.35% with a unit product cost of 17.07 $/GJ. Also, the results revealed efficiency improvement via increasing the solar energy share. In addition it is shown that, developed system in this work can yield higher efficiency compared to a similar trigeneration system based on the Kalina cycle.

Net Zero Energy Communities: Integrated Power System, Building and Transport Sectors

A Net Zero Community (NZC) concept and its energy characteristics are presented in this paper. NZC is an emerging topic with multiple variations in terms of scope and calculated methods, which complicates quantifying its performance. This paper covers three key barriers in achieving NZC targets: (1) the main focus of current definitions on buildings, disregarding community power systems and energy use in transportation; (2) different requirements (source, supply, metrics, etc.) in the existing definitions; and (3) lack of updated published reports to track the progress of committed NZC targets. The importance of this research is summarized as due to increased savings in primary energy and greenhouse gas emissions related to the three main energy sectors, namely power systems, buildings, and transportation (PBT). To clarify the current NZC, this paper reviews: (1) variations in the existing definitions and criteria from peer-reviewed publications; (2) the latest climate projection models by policymakers to achieve net zero by 2050; (3) the literature on renewable-based power systems; and (4) three planned NZC cases in international locations, in order to study their NZC targets, energy performance, and challenges. The outcome highlights NZC design guidelines, including energy efficiency measures, electrification, and renewables in PBT sectors that help stakeholders including policymakers, developers, designers, and engineers speed up achievement of NZC targets.

Performance assessment of hybrid active filtering technique to enhance the hosting capacity of distorted grids for renewable energy systems

Increased green energy presence in distribution power networks can resolve rising energy demands while also reducing fossil fuel consumption, as well as providing economic and technical merits. However, the quantity of power delivered to customers cannot be allowed to take precedence over the quality of that electricity. This is because the high penetration of the renewable-based power generation comes at the cost of power quality (PQ) deterioration, especially at the point of common coupling (PCC), owing to nonlinear characteristics of renewable-based distributed generation (DG) systems and pre-contamination of modern distribution grids. So, the function of PQ improvement technologies unavoidably comes into the picture when the hosting capacity (HC) of renewable energy systems is constrained by any of the grid PQ performance indices. This paper investigates the application of a hybrid active power filter (HAPF) to improve the harmonic-constrained HC (HC-HC) of renewable DG systems in harmonically polluted distribution systems. A shunt type HAPF designing to achieve maximum HC-HC is considered as an optimization problem and solved by the firefly algorithm under several constraints the system particularly related to individual and total harmonic distortion limits in line current and voltage at PCC, harmonic currents overloading of distribution feeder. Aside from harmonics, constraints related to voltage rise and drop limits, as well as power factor, are also taken into account to ensure the optimal use of the HAPF as a compensator. The proposed HAPF-based HC-HC improvement approach's findings and efficacy are compared to those acquired from one of the literature's recently proposed techniques. Besides, the study is extended for HC-HC enhancement by HAPF, under changing the utility-side's background voltage distortion and the load-side's nonlinearity level conditions. The performed extended investigation of the system shows that HC-HC enhancing the effectiveness of the proposed approach is rather less susceptible to utility or customer side contribution to background distortion at the PCC. Highlights Hybrid harmonic filtering is investigated for enhancing the harmonic-constrained hosting capacity of distributed generation in distorted grid conditions. A hybrid filter has been found as a better alternative to achieve an advanced level of renewable energy penetration in distorted distribution grids. Along with increasing the penetration level of distributed generation the harmonic distortion is also substantially reduced instead of being at the verge of the standard limit. With the increase in background voltage distortion, the percentage enhancement in HC-HC degrades. High load-side's nonlinearity also results in a relatively lower enhancement in HC-HC. Background nonlinearity negatively influences the percentage of HC enhancement more than the load-side's nonlinearity. Though the utility, as well as customer-side nonlinearity, affect the performance of the hybrid filter also yet the variation is significantly lesser than the purely passive filtering-based approach.

The Comparative Economic Study of the Grid and Renewable-Based Off-Grid Power Supply for Residential Load: A Case of Coal-Rich Area

The Comparative Economic Study of the Grid and Renewable-Based Off-Grid Power Supply for Residential Load: A Case of Coal-Rich Area

Spatio-Temporal and Power–Energy Scheduling of Mobile Battery Storage for Mitigating Wind and Solar Energy Curtailment in Distribution Networks

Several technical, computational, and economic barriers have caused curtailing a share of renewable-based power generation, especially in systems with higher penetration levels. The Mobile Battery Energy Storage (MBES) can cope with this problem considering the spatial and temporal distribution of the curtailed energy. Accordingly, a new operation model is proposed for optimal scheduling of the MBES in a distribution network with wind and photovoltaic (PV) resources. The network experiences curtailment situations because of bus overvoltage, feeder overload, and power over-generation. The MBES is a truck-mounted battery system compacted in a container. The proposed model seeks to determine the optimal spatio-temporal and power–energy status of the MBES to achieve a minimum curtailment ratio. The model considers transportation time and cost of the MBES efficiently while both active and reactive power exchanges are modeled. The model is linear, without convergence and optimality problems, applicable to real-life large-scale networks, and can be easily integrated into the commercial distribution management software. The implementation results on a test system demonstrate its functionality to recover a considerable share of the curtailed energy for both wind and PV resources at all curtailment patterns and scenarios.