Regenerative Sources Research Articles

Review of Hydrogen Production Techniques from Water Using Renewable Energy Sources and Its Storage in Salt Caverns

Hydrogen is becoming an increasingly important energy carrier in sector integration for fuel cell transportation, heat and electricity. Underground salt caverns are one of the most promising ways to store the hydrogen obtained from water electrolysis using power generation from renewable energy sources (RES). At the same time, the production of hydrogen can be used to avoid energy curtailments during times of low electricity demand or low prices. The stored hydrogen can also be used during times of high energy demand for power generation, e.g., with fuel cells, to cover the fluctuations and shortages caused by low RES generation. This article presents an overview of the techniques that were used and proposed for using excess energy from RES for hydrogen production from water and its storage techniques, especially in underground salt caverns, for the aforementioned purpose, and its feasibility. This paper compares and summarizes the competing technologies based on the current state-of-the-art, identifies some of the difficulties in hydrogen production and storage, and discusses which technology is the most promising. The related analysis compares cost and techno-economic feasibility with regard to hydrogen production and storage systems. The paper also identifies the potential, technical challenges and the limitations associated with hydrogen integration into the power grid.

Optimal energy management for multi-energy multi-microgrid networks considering carbon emission limitations

Multi-energy multi-microgrid (MMG) networks are considered as a promising form of energy systems that can integrate various energy resources and improve energy utilization efficiency. Carbon emission limitation, regarded as a significant factor in energy management, has received increasing attention in recent years. By taking into account both economic and environmental factors, MMG networks can offer a great opportunity to reduce operation costs and carbon emissions. In this paper, we propose an optimal energy management strategy for minimizing the operation cost of an MMG network, considering operation constraints and carbon emissions. The energy management strategy is designed to consist of a day-ahead phase and an intra-day phase to overcome the uncertainty effects of renewable energy sources (RESs) generation and load demands. We first present a day-ahead scheduling strategy for the MMG network, in which microgrids operate in a distributed manner and share electricity while preserving their privacy. We then present an intra-day scheduling strategy for each microgrid, in which the operation costs and penalty costs caused by the adjustment of energy devices and energy procurement are minimized sequentially using a rolling horizon method. Simulation results demonstrate the effectiveness of the proposed energy management strategy in lowering operation costs and carbon emissions.

Optimal islanding operation of hydrogen integrated multi-microgrids considering uncertainty and unexpected outages

Nowadays, with the increasing demand for hydrogen in developed countries, the optimization problems of multi-microgrids (MMG) equipped with hydrogen-based facilities, e.g. power-to-hydrogen technology and hydrogen storage, have attracted tremendous attention. On the one hand, the unpredictable occurrence of contingencies makes the optimal operation of MMG systems more challenging. On the other hand, MMG operators should use powerful techniques to appropriately model different uncertain parameters in their energy management problems. In this respect, this paper aims to propose a contingency-constrained optimal operation model for an islanded MMG system based on power and hydrogen considering multiple uncertainties, electrical storage, and demand response (DR) resources. In order to make the proposed model more realistic, the impact of contingencies such as the unexpected outage of tie lines or generation units on the economic performance of the MMG system is evaluated. To appropriately model the uncertain nature of the electrical load, and power generation of renewable energy sources, a scenario-based approach is used. Moreover, incentive-based DR programs are employed to reduce the operating cost of the MMG system. With the implementation of such programs, flexible electricity consumers of the microgrids are motivated to curtail a portion of their load in peak hours. The extracted results demonstrate that DR employment improves the operating cost of the MMG system by about 26.8%. Furthermore, the consideration of unexpected outages, which makes the scheduling model more realistic, increases the operational cost of the system by about 1.51%.

Power generation control of restructured hybrid power system with FACTS and energy storage devices using optimal cascaded fractional‐order controller

AbstractThis work presents power generation control of a two‐area hybrid restructured power system, initially integrated with renewable energy source (RES) and electric vehicle (EV). For further analysis, additional inclusion of FACTS and energy storage devices in the two‐area hybrid restructured power system is to be analyzed for improved system dynamics. The hybrid restructured power system is a complex nonlinear system that brings light to the major problem of system dynamic control due to insufficient damping under varying loading circumstances. To solve this problem, a robust control approach with rapid acting controllable and storage devices are an immediate need for advanced power system. Motivated from the fact that cascaded fractional order controllers exhibit better performance in comparison to classical controllers, this article proposes an advanced cascaded fractional‐order ID‐fractional‐order PD (cascaded FOID‐FOPD) controller for system performance enhancement of hybrid restructured power system. The maiden application of satin bower bird optimizer technique to optimize the secondary controller gains is employed. The proposed controller's superiority is demonstrated by comparing the results to the other existing controllers. The impact of RES's generation and EVs on system dynamics for cascaded FOID‐FOPD controller is also explored. Furthermore, the sensitivity analysis is done to reflect that optimized gains of cascaded FOID‐FOPD controller are supportive enough for variations in RESs, load perturbations, capacity ratio, and disco participation matrix.

Відносне оцінювання засобів балансування режимів електроенергетичних систем з відновлюваними джерелами енергії

The method of research of measures of compensation of instability of generation of renewable energy sources in electric power systems is developed in the work. The process of electricity generation by solar and wind power plants depends on natural conditions, which causes problems in the process of balancing regimes in the power system. It is unrealistic for them to fulfill the planned and approved generation schedule for the next day. For this reason, the power system is forced to keep a reserve of power to compensate for deviations of renewable energy sources from the projected generation schedule. Since these deviations can be both to a greater or lesser extent than permissible, it accordingly forms the means to balance the regimes of the power system. The general system reserve is mainly used (mainly shunting capacities of thermal and hydroelectric power plants). As the reserve is not enough, to use the currently available means of electricity backup, so additionally use: electrochemical energy storage, hydrogen and biogas technologies. Mathematical models based on the theory of similarity and the criterion method have been developed to analyze the technical and economic efficiency of individual means of reservation. This method is preferable because, with the least available source information, it makes it possible to compare different ways of backing up the instability of renewable energy production, assess their proportionality and determine the cost sensitivity to the power of backup methods. Such dependencies make it possible to choose more reasonably at the first stage certain methods of redundancy in accordance with the characteristics and requirements of the electricity system. They can be clarified if the current and short-term price indicators are known.

Dynamic Virtual Power Plant: A New Concept for Grid Integration of Renewable Energy Sources

The concept of Virtual Power Plant (VPP) has arisen over a decade ago from the relatively low competitiveness of the back then emerging non-dispatchable RES. A set of smaller generators imitates the behavior of large synchronous generators. So far, static aspects such as generation or slow dynamics have been of interest, as it is the case for the zonal secondary frequency control scheme in Spain, which can be viewed as a VPP. However, considering dynamic aspects is of high importance, especially to further increase the current penetration level of Renewable Energy Sources (RES). Indeed, one should deal with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full</i> participation of RES in grid ancillary services. This means not only to get some positive impact on grid voltage and frequency dynamics but to bring concepts which allow integrating RES to existing secondary regulation schemes on the same level as classic synchronous generators. For that, we propose here a new concept called Dynamic VPP (DVPP) which fully integrates the dynamic aspects at all levels: locally (for each RES generator), globally (for grid ancillary services and interaction with other close-by elements of the grid) and economically (for internal optimal dispatch and participation in electricity markets). A DVPP is a set of dispatchable and non-dispatchable RES along with a set of common control and operation procedures. The latter procedures include the choice of dispatchable and non-dispatchable RES constituting the DVPP, the control of DVPP generators for local objectives and participation of the DVPP as a single unit in ancillary services (especially in case of loss of natural resources - e.g., wind, sun - on a part of the DVPP), the limitation of the risk of adversely interaction with close-by elements and the feasibility in both current power systems scenarios and future ones with large share of RES. This new DVPP framework and approaches developed for its implementation allows ensuring optimal operation of a mixed portfolio of dispatchable and non-dispatchable RES generators for planning, participation to the markets and real-time control. For the control, all time-scale dynamics are considered to improve RES management (internal re-dispatch inside the DVPP to take advantage of dispatchable/non-dispatchable nature of each RES and to optimally manage the lack of natural resources in some regions of the DVPP) and their participation to grid ancillary services. Concrete structures of DVPP as well as ways to address the other control and economical aspects will be shown. This new DVPP concept is now under development in the H2020 POSYTYF project (https://posytyf-h2020.eu/).

A Linear Stochastic Formulation for Distribution Energy Management Systems Considering Lifetime Extension of Battery Storage Devices

Recently, the number of Battery Energy Systems (BESs) connected to the grid has grown significantly. These assets can alleviate some operational issues such as demand surges and occasional power fluctuations associated with the Renewable Energy Sources (RESs) connected to the grid. Nonetheless, both overcharging and frequent usage severely affect their health status and shorten their life expectancy. In this paper, an Energy Management System (EMS) framework with a linearised algorithm and in-depth analysis on BES life extension is presented, which optimises the techno-economic aspects of an Active Distribution Network (ADN) connected to RESs. By applying a mathematical linearisation formulation, a Mixed-Integer Linear Programming (MILP) model is proposed for linearising the Optimal Power Flow (OPF) problem. This technique, which has the merit of fair accuracy while having high speed, is used for scheduling BESs to increase their durability and decrease grid costs. To consider the inherent uncertainty associated with demand and RES generation, a two-stage Stochastic Programming (SP) method is implemented in the proposed model. In terms of battery Loss of Health (LoH) assessment, a linearised battery lifetime method is introduced. Ultimately, a modified 33-bus radial distribution test system with a day-ahead Real-Time Pricing (RTP) program was chosen to apply the proposed algorithm and assess its efficiency.

Solvability region of AC–DC power systems with volatile renewable energy sources

The high voltage direct current (HVDC) is widely incorporated into today’s AC power grids. It is a key technology to address the issues for large power transmission and power flow control. However, the HVDC may influence the consumption-ability of systems for renewable energy sources (RES). This paper studies the solvability region in the AC–DC system with HVDC under the volatile RES generation and system operation constraints. The set of all admissible injection patterns of RES is termed dispatchable region, which is depicted by the Pareto frontier of multi-objective optimization problems. An adopted ε-constraints method is used to solve the multi-objective optimal power flow problem. Cases study on an adopted IEEE-30 bus system are provided to analyze the impaction of HVDC control strategies and parameters.

Data‐driven cooperative load frequency control method for microgrids using effective exploration‐distributed multi‐agent deep reinforcement learning

To reduce the total power generation cost and improve the frequency stability of an island microgrid integrating renewable energy generation sources, a data-driven cooperative load frequency control (DC-LFC) method is proposed for solving the coordination control problem occurring between the controller and power distributor of the system. A novel algorithm, termed the effective exploration-distributed multiagent twin-delayed deep deterministic policy gradient (EED-MATD3) algorithm, is further proposed, the design of which is structured based on the concepts of imitation learning, ensemble learning, and curriculum learning. The EED-MATD3 method employs various exploration strategies, and the controller and power distributor are treated as two agents. Through centralized training and decentralized execution, a robust cooperative control strategy is realized. The performance of the proposed algorithm is verified in an LFC model of Zhuhai Tandang Island, an island microgrid in the China Southern Power Grid.

A New Tool to Assess Maximum Permissible Solar PV Penetration in a Power System

With diminishing fossil fuel resources and increasing environmental concerns, large-scale deployment of Renewable Energy Sources (RES) has accelerated the transition towards clean energy systems, leading to significant RES generation share in power systems worldwide. Among different RES, solar PV is receiving major focus as it is most abundant in nature compared to others, complimented by falling prices of PV technology. However, variable, intermittent and non-synchronous nature of PV power generation technology introduces several technical challenges, ranging from short-term issues, such as low inertia, frequency stability, voltage stability and small signal stability, to long-term issues, such as unit commitment and scheduling issues. Therefore, such technical issues often limit the amount of non-synchronous instantaneous power that can be securely accommodated by a grid. In this backdrop, this research work proposes a tool to estimate maximum PV penetration level that a given power system can securely accommodate for a given unit commitment interval. The proposed tool will consider voltage and frequency while estimating maximum PV power penetration of a system. The tool will be useful to a system operator in assessing grid stability and security under a given generation mix, network topology and PV penetration level. Besides estimating maximum PV penetration, the proposed tool provides useful inputs to the system operator which will allow the operator to take necessary actions to handle high PV penetration in a secure and stable manner.

Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy

In this paper, a risk-constrained stochastic mixed-integer linear programming (MILP) model is proposed for optimal bidding strategy of a grid-connected CHP-based multi-microgrid (MMG) system in energy and reserve markets considering environmental restrictions. A reward-based demand response program is considered in the proposed framework to realize demand-side management and boost the economic performance of the MMG system. Besides, conditional value-at-risk as a proper risk-averse index is incorporated into the developed mixed-integer programming formulation to hedge the risk of the low profits associated with worst scenarios. For this study, the uncertainty of energy market price, electrical load, and power generation of renewable energy sources are taken into account through employing stochastic programming. Meanwhile, given the global policy for emissions reduction, an emission constraint is considered into the model, ensuring a more green trading strategy. The obtained simulation results over a 24-h time horizon, demonstrate that increasing the risk factor leads to the profit decrement by almost 30.37% while the conservativeness of the MMG against the risk is improved. Also, the results reveal that by increasing the value of emission factor, the system's profit is decreased by about 30.03% while the MMG would be operated more environmental-friendly.

Correlation of Day Ahead Electric Energy Market Price with Renewable Energy Sources Generation and Load Forecast

Abstract An increase in the share of renewable energy sources has an impact on generation variability and generation forecast error, which is also reflected in the formation of the day ahead electric energy market price. This paper analyses the impact of variable renewable energy sources and load forecast on the day ahead German electric energy market. A correlation between the market price, renewable energy sources generation and load forecasts was analysed. Results show that there is a significant correlation between the forecast of renewable energy sources generation as well as the load on day ahead electric energy market price. However, a residual load, which represents the difference between the load and the renewable generation, has the biggest impact on the day ahead price.

Assessment of electricity network investment for the integration of high RES shares: A Spanish-like case study

In the course of the energy transition, the EU member states’ National Energy and Climate Plans seek to install significant amounts of intermittent renewable generation capacity over this decade. Previous studies underline the social, political, and economic benefits of the electricity sector decarbonisation. The economic analysis of renewable energy sources (RES) integration is commonly performed with single-bus generation expansion models that seek the cost-optimal expansion of RES generation capacity to reduce operational expenses. However, electricity grids will require investments to adapt to the integration of high amounts of RES capacity. This paper contrasts the cost-optimal generation capacity mix obtained from a single-bus expansion model with a conservative estimation of electricity network investment requirements for an exemplary Spanish-like case study. RES network investment costs are put in context with an alternative non-RES generation expansion pathway. Network investment costs considered include expansion costs for both transmission and distribution grids. Electricity network expansion costs represent 6 to 10% of the corresponding generation capacity investment. Despite increasing network investment costs, the integration of high RES shares into electricity grids reduces operating costs when compared to non-RES pathways. Fuel and emission savings exceed total investments (generation capacity, network expansion, and connection costs). • We quantify the grid investments needed to integrate high amounts of RES. • Results show that RES drive significant grid expansion and connection costs. • However, incremental grid investments represent only 6%–10% of RES investment costs. • RES-driven reduction in operating costs compensate for incremental grid costs. • High RES penetration is found to reduce total system costs (investment + operation).

Criterion modelling of the process of redundancy of renewable energy sources power generation instability by electrochemical accumulators

The paper analyzes the methods and ways for the redundancy of renewable energy sources (RESs) instability in electric power systems (PS). It is shown that these can be maneuverable capacities, in particular, thermal and hydropower plants, accumulators, hydrogen technologies, biogas plants. It is substantiated that, for various reasons, for the RESs to be developed and their capacity to be increased in power systems, electrochemical accumulators and highly maneuverable capacities existing in the PS are the most prepared for implementation. Mathematical models based on similarity theory and the criterion method have been developed for them. This approach is preferable due to the fact that with the minimum available information, it provides the opportunity to compare different ways of compensation of RESs generation instability, to assess their proportionality, as well as to determine the sensitivity of costs to the capacity of the redundancy methods. Criterion models which allow us to design dependences of the costs for the redundancy of RESs generation instability on the capacity of electrochemical accumulators, on the capacity of the system reserve, as well as on the capacity of power lines have been formed. Such dependencies make it possible to more reasonably choose certain methods of redundancy in accordance with the characteristics and requirements of PS.

Electric Vehicles Charging Management System for Optimal Exploitation of Photovoltaic Energy Sources Considering Vehicle-to-Vehicle Mode

The growing penetration of distributed renewable energy sources (RES) together with the increasing number of new electric vehicle (EV) model registrations is playing a significant role in zero-carbon energy communities’ development. However, the ever-larger share of intermittent renewable power plants, combined with the high and uncontrolled aggregate EV charging demand, requires an evolution toward new planning and management paradigms of energy districts. Thus, in this context, this paper proposes novel smart charging (SC) techniques that aim to integrate as much as possible RES generation and EV charging demand at the local level, synergically acting on power flows and avoiding detrimental effects on the electrical power system. To make this possible, a centralized charging management system (CMS) capable of individually modulating each charging power of plugged EVs is presented in this paper. The CMS aims to maximize the charging self-consumption from local RES, flattening the peak power required to the external grid. Moreover, the CMS guarantees an overall good state of charge (SOC) at departure time for all the vehicles without requiring additional energy from the grid even under low RES power availability conditions. Two methods that differ as a function of the EV power flow direction are proposed. The first SC only involves unidirectional power flow, while the second one also considers bidirectional power flow among vehicles, operating in vehicle-to-vehicle (V2V) mode. Finally, simulations, which are presented considering an actual case study, validate the SC effects on a reference scenario consisting of an industrial area having a photovoltaic (PV) plant, non-modulable electrical loads, and EV charging stations (CS). Results are collected and performance improvements by operating the different SC methods are compared and described in detail in this paper.

Stochastic Modelling and Stability Analysis of Large-Scale Wind Power Generation System with Dynamic Loads

As a result of dwindling fossil fuel reserves and the negative impact of greenhouse gases (GHGs) on the environment, it is important that the search for a power grid that will comprise of only variable renewable energy (VRE) generation sources such as wind or solar energy which is available everywhere for free is given much attention. The main challenge associated with these sources of energy is their variability and random nature. It is as a result of instability introduced by the VRE generation sources, that is why there is a strict control measures put in place by the regulators as to how much VRE generation sources can feed into the power grid in the case of its integration into an existing power grid. It becomes imperative to consider implications for grid stability and reliability when considering a power grid that will consist of VRE generation only. Eigenvalue approach was used to analysed the performance of anticipated large-scale VRE grid to ascertain its behaviour. Eigenvalue approach is one of the methods to examine the stability of a power system’s dynamic performance. The results indicated that it is possible to attain the necessary stability provided the assumptions made during the modelling stage is revised to improve upon the model.

DSO Strategies Proposal for the LV Grid of the Future

A significant challenge for the DSO (Distribution System Operator) will be to choose the optimum strategy for flexibility service in the LV area with high RES (renewable energy sources) penetration. To this end, a representative LV grid operated in Poland was selected for analysis. Three research scenarios with RES generation were presented in the range of 1–8 kW for the power factor from 0.9 to 1. The grid PV capacity was determined for four load profiles. Based on this factor, optimum RES volume management service types were determined. Under the flexibility service, the proposed power conversion services and active RES operations for DSO were proposed. The research was conducted using the Matlab and PowerWorld Simulator environment. Optimum active power values were obtained for the RES generation function for single and dual operation systems of the power conversion system. In future, the knowledge in the field of grid capacity will enable the DSO to increase the operating efficiency of the LV grid. It will enable the optimum use of the RES generation maximisation function and proper strategy selection. It will improve the energy efficiency of the power input through the MV/LV node.

Designing the power supply system of the region with the integration of hydrogen energy facilities

The paper considers the methodology of designing a distribution network by the example of the Penza region in Russia. We performed a simulation of operating modes and optimization of the distribution network topology. The power balance in the power system was performed in autonomous mode. Recommendations were given on the placement of renewable energy sources (RES) on the ground and the selection of their capacity. The total capacity of renewable energy generation facilities exceeds the design load 3 times. A balancing load is included in the power system to increase the efficiency of renewable energy generation facilities. Electrolysis hydrogen stations consume excess electricity generation during the periods of favourable weather conditions. Hydrogen is stored in the warehouses and can be used at the thermal power plants during periods when weather conditions are unfavourable and the generation of renewable energy sources is insufficient to supply the region.

Frequency control of fully-renewable interconnected microgrid using fuzzy cascade controller with demand response program considering

The main purpose of this paper is to design a good fuzzy cascade controller for interconnected microgrids (μGs) with supporting a frequency perturbation-based demand response program. A fuzzy PD-(1+I) controller is optimally designed to perform the load frequency task in a fully-renewable interconnected μGs. In the proposed control strategy, exact adjusting of controller parameters and membership functions has a key role to achieve the robust performance. Thus, the fuzzy PD-(1+I) controller is automatically designed and updated using a nature-inspired mayfly optimization algorithm for finding a better controller and reducing system control cost. It combines the fuzzy theory and cascade control advantages to enhance load disturbance rejection effort in each μG and dump frequency fluctuations considering system parametric uncertainties and renewable energy sources (RESs) generation changes. The studied two-area islanded μG system by applying a fuzzy PD-(1+I) controller has been investigated in six different situations in comparison with the fuzzy PID and PD-(1+I) cascade controllers to demonstrate capability of load disturbance rejection, RESs generation changes and system parameters variation. The results in all cases show the decisive superiority of the fuzzy PD-(1+I) controller and its high adaptability than the other controllers.

Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids

Electric spring (ES) as a breakthrough in power electronics has led to a revolution in demand-side management. This paper presents flexible power management (FPM) of a networked microgrid (MG) in the presence of renewable energy sources (RESs) and flexibility sources (FSs). The FSs include the novel topology of the integrated unit of ES with electric vehicles (EVs) parking (IUEE) and incentive-based demand response program (DRP). The proposed FPM model is formulated as an optimization problem that minimizes the difference between the expected energy cost and the expected profit of FSs' flexibility subject to the AC optimal power flow (AC-OPF), RESs, FSs, and MG flexibility constraints. In the proposed model, flexibility pricing is performed for both upward and downward flexibility services in which the expected flexibility profit is proportional to the product of the FSs' flexibility and flexibility incentive price (FIP). Further, this paper uses a stochastic programming to model uncertain parameters associated with load demand, energy prices, maximum RES generation capacity, and EVs’ parameters. Finally, the potential of the proposed FPM model in improving the economic, operational and flexibility conditions of the MG is investigated through implementation of the proposed model on the 32-bus radial MG.