Distributed Energy Resource Systems Research Articles

Integrated Active and Reactive Power Control Methods for Distributed Energy Resources in Distribution Systems for Enhancing Hosting Capacity

Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, leading to overvoltage issues and exceeding thermal limits of the distribution lines. To address these issues, it is necessary to limit the output of DERs to a certain level, which results in constraining the hosting capacity of DERs in the distribution system. In this paper, coordination control methodologies of DERs are developed and executed to mitigate the overvoltage and overcurrent induced by DERs, thereby increasing the hosting capacity for DERs of the distribution system. This paper proposes three coordinated approaches of active and reactive power control of DERs, namely Var Precedence, Watt Precedence, and Integrated Watt and Var Control. The Var and Watt Precedence prioritizes reactive power for voltage (Q–V) and active power for current (P–I) to address network congestion, thereby enhancing hosting capacity. Conversely, the Integrated Var and Watt Precedence propose a novel algorithm that combines four control indices (Q–V, P–V, Q–I, and P–I) to solve network problems while maximizing hosting capacity. The three proposed methods are based on the sensitivity analysis of voltage and current to the active and reactive power outputs at the DER installation locations on the distribution lines, aiming to minimize DER active power curtailment. Each sensitivity is derived from linearized power equations at the operating points of the distribution system. To minimize the computation burden of iterative computation, each proposed method decouples active and reactive power and proceeds with sequential control in its own unique way, iteratively determining the precise output control of distributed power sources to reduce linearization errors. The three proposed algorithms are verified via case studies, evaluating their performance compared to conventional approaches. The case studies exhibit superior control effectiveness of the proposed DER power control methods compared to conventional methods when issues such as overvoltage and overcurrent occur simultaneously in the distribution line so that the DER hosting capacity of the system can be improved.

Investment in vehicle-to-grid and distributed energy resources: Distributor versus prosumer perspectives and the impact of rate structures

Photovoltaic panels, electric vehicles, and vehicle-to-grid technologies are becoming more common and hold significant promises to improve the grid and foster the energy transition. However, significant questions remain unanswered with respect to who should invest in this equipment and what tariff should be used. This paper examines whether the distribution company or prosumer should invest in and manage Distributed Energy Resources (DER), the ideal combination of DER to utilize, and the appropriate tariff to implement. Central to this analysis is the assessment of different stakeholder objectives, particularly from the investor's perspective, where net present value is used as the primary criterion for evaluating the different investment scenarios. Additionally, the impact of these scenarios on the annual system cost is calculated. A mathematical scenario analysis model is developed to simulate the operation of DER and energy management systems. This model utilizes the Vermont electricity grid's real-world consumption, generation data, and cost structures. The results underscore the significance of incorporating vehicle-to-grid technology to enhance the profitability of DER investments. This inclusion of specific data sources and stakeholder criteria aims to provide insight into the complex dynamics of smart-home deployment.

Techno-Economic Comparison between Centralized and Distributed Energy Resource Systems: A Case Study of an Underground Transportation Infrastructure System in Changsha, China

Due to their higher energy efficiency and better economic performance, distributed energy resource (DER) systems are expected to be one of the main energy supply forms in the future and have gained increasing attention in recent years. Thus, there is a need to boost our understanding of how to apply DER systems in different types of actual cases. This paper investigates a techno-economic analysis of a DER system applied in a real case in a hot-summer and cold-winter zone in China, where the climate is considered to be Cfa according to the Köppen–Geiger climate classification system. An urban underground transportation infrastructure system located in Changsha (China) was chosen to analyze the techno-economic performance of a natural-gas-fired DER system in comparison with a centralized energy system (CES). First, a scientific and reasonable application program of the natural-gas-fired DER system was developed by an overall load analysis (electric load, air-conditioner load, and domestic hot water load during the operating period). Based on this load analysis, this research combined the energy consumption and the actual operating situation and then compared and analyzed different types and capacities of equipment in this case. Moreover, a comprehensive analysis of the economic benefits was estimated by comparing the natural-gas-fired DER system with conventional CESs. Overall, the total annual cost of the DER system was reduced by 18.73%, and its additional investment can be paid back within about 2.2 years. A better economic benefit was achieved by applying the natural-gas-fired DER system in an actual case, which will help encourage the widespread application of DER systems.

Impact of Ergodic and Nonergodic Ground Motion Estimation on the Earthquake Resilience of Shared Distributed Energy Resource Systems

Impact of Ergodic and Nonergodic Ground Motion Estimation on the Earthquake Resilience of Shared Distributed Energy Resource Systems

Active Disturbance Rejection Control for Distributed Energy Resources in Microgrids

Motivated by the significant efforts developed by researchers and engineers to improve the economic and technical performance of microgrids (MGs), this paper proposes an Active Disturbance Rejection Control (ADRC) for Distributed Energy Resources (DER) in microgrids. This approach is a nonlinear control that is based on a real-time compensation of different estimated disturbances. The DER operates along with the electrical grid to provide the load requirements. This load has a nonlinear and uncertain character, which presents a source of unmodeled dynamics and harmonic perturbations of the MG. The main objective of this paper is to ensure the stability and the continuity of service of the distributed generation resources by controlling the DC-AC converter. The ADRC as a robust control technique is characterized by its ability to compensate for the estimated total disturbances caused by the load variation and the external unmodeled perturbations to guarantee the high tracking performance of sinusoidal reference signals in the DER system. The ADRC technique is characterized by its nonlinear function, which provides a high robustness to the controlled system. However, in order to simplify the control structure by keeping its high reliability, this paper proposes to replace the nonlinear function with a simple error (termed linear ADRC), compares the impact of this modification on the system performances, and evaluates its operation in the presence of linear and nonlinear load variations. Simulation results are presented to demonstrate the efficiency of the proposed control approach for a three-phase DER.

Decentralized Control for Multiple Network-Forming Inverters in a Solar PV-BESS Based Standalone Microgrid System

—This research paper focuses on decentralized control of an AC microgrid in standalone mode. The microgrid includes three solar PV arrays accompanied by three battery energy storage systems (BESS), utilizing renewable distributed energy resources (DERs). The connection between each DER system and the microgrid is established through a network-forming three-phase voltage source inverter (VSI). The microgrid’s operation is regulated using modified droop control, incorporating virtual impedance and feed-forward derivative in primary control, along with a phase-locked loop (PLL) system for inverter synchronization. A master-slave control configuration is employed between the VSIs to mitigate voltage amplitude and frequency deviations induced by primary control. These enhancements ensure smooth power distribution and maintain voltage amplitude and frequency within specified limits across different operational scenarios. Control operations are performed in a stationary frame ( frame) using Clarke’s transformation, and PR controllers regulate VSI’s output voltage and current. The research paper shows the effectiveness of controlled microgrid operations using MATLAB/Simulink software in various conditions including intermittent PV system behavior, load dynamics, and DER connection/disconnection challenges. Simulation results show that the proposed approach enhances stability and performance of the microgrid system, especially in managing power fluctuations and maintaining a constant frequency response.

Analysis of reverse fault current regarding the impact of transformer core types on the two most common winding connections of distributed energy resources in distribution systems

As many DERs with solid grounding are connected to the distribution system, unwanted reverse fault current is generated during a single-line-to-ground fault. Therefore, it often causes protection problems such as protection blinding and sympathetic tripping. To ensure reliable protection coordination between protective devices, fault current should be calculated accurately. Although three-limb core transformers are utilized for DERs for economic and spatial reasons, the conventional method that assumes five-limb core transformers for DERs is still used to calculate fault current. The zero-sequence impedance of a three-limb core transformer is often unknown. For this, a methodology for evaluating the zero-sequence impedance according to the core-type of transformer is presented with IEC 60076-8 standard. Then, a methodology for evaluating fault current is proposed considering the impact of DERs, loads, and transformer core types. The proposed methodologies are used for a comprehensive analysis of fault current discrepancies according to the core-type of transformers. The results indicate that significant discrepancies exist in fault current evaluated with five- and three-limb core transformers. Therefore, to accurately calculate the fault current, utility engineers should use the proper zero-sequence impedance of three-limb core transformers instead of five-limb core transformers.

Co-Optimization of Distributed Renewable Energy and Storage Investment Decisions in a TSO-DSO Coordination Framework

As Distributed Energy Resources (DER) penetration levels and distributed flexibility investments are continuously growing, various smart grid actors need to coordinate their decisions towards optimal DER siting and sizing: First, profit-based Energy Service Providers (ESPs) want to secure their long-term profits and avoid economically unsustainable DER investments. Second, Distribution System Operators (DSOs) need to ensure the reliable operation of their networks in an economically optimal way. Third, Transmission System Operators (TSOs) want to optimally exploit the available “clean” DERs in close collaboration with the downstream DSOs. In this paper, we propose a novel ESP-DSO-TSO coordination scheme to co-optimize distributed renewable energy and storage planning at the distribution network level, while modeling the coordinated TSO-DSO operations. We formulate a bi-level program, the upper-level of which minimizes the DSO's costs, ensuring a minimum rate of return on ESP's investments, while the lower-level models the transmission network-constrained wholesale market. A nested decomposition technique is used to achieve computational tractability. Simulation results showcase a trade-off analysis between sustainable DER investments and system cost minimization and prove that an ESP-DSO-TSO interaction can benefit all involved actors to a certain extent. Finally, the computational efficiency of the proposed nested decomposition algorithm is demonstrated via numerical results.

A conditionally constrained compound sub‐gradient method for distributed energy coordination

AbstractA conditionally constrained compound (CCC) sub‐gradient method typically involves solutions by multi‐agents, which have important applications in distributed energy resources (DER). The proposed DER system structure model uses operating state switching to analyze the characteristics of the model transformation. The work proposes that energy storage (ES) transformation is the main factor that influences the transformation in the DER model. For solving this optimization problem, this study uses a compound sub‐gradient method that is distributed among the agents. Compared with the conventional analysis methods, a system configuration and equivalent model of distributed power is obtained using the sub‐gradient method, and the power distribution characteristics of the DER in the off‐grid state are further given. Using a time‐based representation, this method can be applied to complex distributed new energy access applications and uses an iterative compound step ladder algorithm with a specific step size for switching. The compound distributed gradient algorithm further determines the selected range of algorithm parameters. Finally, the results of the convergence rate explicitly characterize the effectiveness of the method.

Raising the Resilience of Industrial Manufacturers through Implementing Natural Gas-Fired Distributed Energy Resource Systems with Demand Response

The use of relatively small-scale distributed electric power generation sources is one of the key focus areas in the development of global industry and regional power generation. By integrating distributed generation sources into their on-site energy infrastructure, industrial consumers gain new characteristics and possibilities as entities of the power system that do not only consume power, but in fact can flexibly generate and deliver electricity to local and even centralized grids. This type of entity is called a distributed energy resource system with demand response (Russian: ‘active energy complex’). The purpose of this study is to lay the methodological foundation for the use of distributed energy resource systems with demand response in industrial sites under existing gas and power market conditions and for ensuring the synchronization of parameters that is necessary for managing complex energy consumption. This article provides an empirical study of the principles of the natural gas pricing under the demand volatility of regional markets and the Russian Mercantile Exchange. The article outlines the key drivers, as identified by the authors, that impact gas consumption by a distributed energy resource system, including demand characteristics, limitations and capacity of the gas network and the mode of gas consumption by an industrial enterprise and its generator. Accounting for all of these factors is essential for effective management and proper operational adjustment of a distributed energy resource system with demand response. The result of the study is a proprietary model and a tool for the management of distributed energy resource systems in integration with the gas demand management, which analyze the internal and external parameters of the industrial entity’s operations and its distributed energy resource system, as well as factors existing in the integrated distributed energy system where the consumer is able to buy natural gas in various market segments. The proprietary tool of distributed energy resource system management is based on the centralized control system, which combines performance analytics, operational scheduling of production and the distributed energy resource system, price planning for the wholesale and retail power markets, regional gas markets and exchange, monitoring all elements of the system, and assessment of different active energy management scenarios under various external and internal conditions impacting production and energy demand. Our proprietary tool has been successfully tested in a typical industrial site and was reported to deliver a significant electricity and gas cost-saving effect, which amounted to an 18 percent reduction in the total energy costs of the company, or more than USD 2.6 million per year. The resulting saving effect can recoup the costs of investing in a distributed energy resource system, including construction and installation of the local grid and automation infrastructure, and can be obtained in any country of the world.

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. The methodology developed can be used to extend the analysis to other locations.

Wavelet-based estimation method for online condition monitoring of dc-link capacitors of distributed energy resources

This paper proposes a novel capacitor condition monitoring for dc-link of power converters employed in distributed energy resources systems. It follows the active methodology, in which an intermittent noncharacteristic signal is injected into the dc-link to estimate the equivalent series resistance (ESR) and capacitance (C) of dc-link capacitors. A real-time stationary discrete wavelet packet transform (RT-SDWPT) performs the capacitor parameter estimations. In this scheme, an interharmonic is used as a noncharacteristic signal to prevent the influence of the system’s inherent harmonic components, mitigating estimation errors. Moreover, the interharmonic frequency is chosen in the region influenced by the ESR and C parameters to ensure capacitor degradation condition. Besides, to mitigate quality issues, the interharmonic’s amplitude, duration, and the time interval between two signal injections follow the recommendations defined by standards. Furthermore, a parameter deviation detection scheme is employed to adaptively adjust the time interval between two estimations, improving failure detection. Experimental results obtained from a microgrid laboratory setup demonstrate the effectiveness and feasibility of the proposed method.

Control Design and Management of a Distributed Energy Resources System

Energy generation, distribution, and transmission are crucial to the development and advancement of humans and their environment. Therefore, the need for a sustainable environment is essential. This study focuses on designing, building, testing, and commissioning an intelligent grid solar-powered distributed energy resource system to serve as an alternative to powering loads with conventional energy sources, creating a pollution-free and self-dependent system that can be built to the capacity of the required load. The solar panels, voltage regulator, microprocessor, solar

A modelling approach to the management of distributed energy resources system

A distributed energy resource (DER) system contributes to an improved operation of an electrical power system for better economy and technical efficiency. In several applications, renewable energy sources are becoming more acceptable for powering nodes. Solar energy is an essential energy source, particularly for outdoor wireless sensor systems. This is due to the regularity and dependability of solar energy systems. In recent times, Photovoltaic cells (PV) are considered expensive alternatives to typical demand-limited lithium batteries, to provide a limitless energy source. This study has modelled and simulated a DER-enabled power distribution network with the use of Simulink in MATLAB and Simscape Electrical for switching operations. The switching operation selected a distributed-based approach, as influenced by the factors of availability and efficiency in enhancing the steady and uninterrupted supply of electric power to the load. The simulated results were achieved by subjecting the island and main utility grids to disturbances at specified time intervals in seconds (10, 35 seconds) and an additional 300 kW load was added to the variable load at the specified time intervals in seconds (40, 20 seconds, etc. respectively). The results and interaction between the island and utility grids, which yielded frequency disturbance, distributed resources, and the microgrid responses to the changes made, were analyzed and discussed. The study has provided a modelled solution for a reliable DER system to provide an almost uninterrupted power supply to the load.

Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm

Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms.

Developing an Optimal Framework for PMU Placement Based on Active Distribution System State Estimation Considering Cost-Worth Analysis

Due to low levels of observability and automation in active distribution networks (ADNs), the deployment of accurate measurement devices would be inevitable to increase the network observability. This work develops an optimal framework for phasor measurement unit (PMU) placement considering the accuracy of the distribution system state estimation (DSSE) process. In this regard, first, considering the significance of active power in supplying network loads, an active power sensitivity analysis is conducted in which the accuracy of active power injection at each bus is multiplied by its value of lost load. In this way, the accuracy of active power estimation could be transformed into a monetary value. Then, based on the determined sensitivity criterion, the optimal placement of PMUs has been performed with the aim of appropriate accuracy for the DSSE. On the other hand, the accuracy of the results obtained in the state estimation procedure can affect the estimation of line-loadings and lead to load shedding due to the low accuracy of estimated line-loadings. It is noteworthy that due to the high integration of distributed energy resources in distribution systems, ADNs would be prone to congestion issues. Therefore, in the next stage, this perspective is also used for determining the optimal number and location of PMUs in ADNs to improve their observability based on the operational conditions of the network. Finally, the developed algorithm is applied on the 77-bus-UK-test distribution network to investigate its effectiveness in improving the DSSE accuracy and mitigating interrupted loads. The numerical results indicate that implementing the proposed framework not only increases the DSSE accuracy but also decreases the cost of compensating the accuracy of active power by 7% compared to the typical network without PMUs. Further, the results show that the proposed model significantly mitigates the total curtailed loads due to the low accuracy of estimated line-loadings.

A steady-state optimal coordination strategy for DERs systems with guaranteed probabilistic performance

We consider the problem of coordinating multiple Distributed Energy Resources (DERs) so as to supply energy to the grid while minimizing its variability around a reference profile that must also be optimized. We focus on the case when each DER is equipped with solar panels and a battery storage device, and jointly design the disturbance compensation strategies for charging and discharging the batteries on a one-day time horizon. To this purpose, we linearly parameterize the strategies and search for a solution minimizing the fluctuations of the energy exchange with the grid in steady-state, with a bound on their extent that holds in probability given the stochastic nature of the solar energy. Interestingly, the probability measure of the resulting chance-constrained optimization problem depends on the parameters of the disturbance compensation strategies, which makes the application of the scenario approach not standard. The proposed scenario-based solution is feasible for the original steady-state chance-constrained optimization problem and proves effective in numerical simulations.

Efficient Methodology for Detection and Classification of Short-Circuit Faults in Distribution Systems with Distributed Generation

Fault detection and classification are crucial procedures for electric power distribution systems because they can minimize the occurrence of faults. The methods for fault detection and classification have become more problematic because of the significant expansion of distributed energy resources in distribution systems and the change in their currents due to the action of short-circuiting. In this context, to fill this gap, this study presents a robust methodology for short-circuit fault detection and classification with the insertion of distributed generation units. The proposal methodology progresses in two stages: in the former stage, the detection is based on the continuous analysis of three-phase currents, whose characteristics are extracted through maximal overlap discrete wavelet transform. In the latter stage, the classification is based on three fuzzy inference systems to identify the phases with disturbance. The short-circuit type is identified by counting the shorted phases. The algorithm for short-circuit fault detection and classification is developed in MATLAB programming environment. The methodology is implemented in a modified IEEE 34-bus test system and modeled in ATPDraw with three scenarios with and without distributed generation units and considering the following parameters: fault type (single-phase, two-phase, and three-phase), angle of incidence, fault resistance (high impedance fault and low impedance fault), fault location bus, and distributed generation units (synchronous generators and photovoltaic panels). The accuracy is greater than 94.9% for the detection and classification of short-circuit faults for more than 20,000 simulated cases.

A Comprehensive Tool for Scenario Generation of Solar Irradiance Profiles

Despite their positive effects on the decarbonization of energy systems, renewable energy sources can dramatically influence the short-term scheduling of distributed energy resources (DER) in smart grids due to their intermittent and non-programmable nature. Renewables’ uncertainties need to be properly considered in order to avoid DER operation strategies that may deviate from the optimal ones. This paper presents a comprehensive tool for the scenario generation of solar irradiance profiles by using historical data for a specific location. The tool is particularly useful for creating scenarios in the context of the stochastic operation optimization of DER systems. Making use of the Roulette Wheel mechanism for generating an initial set of scenarios, the tool applies a reduction process based on the Fast-Forward method, which allows the preservation of the most representative ones while reducing the computational efforts in the next potential stochastic optimization phase. From the application of the proposed tool to a numerical case study, it emerged that plausible scenarios are generated for solar irradiance profiles to be used as input for DER stochastic optimization purposes. Moreover, the high flexibility of the proposed tool allows the estimation of the behavior of the stochastic operation optimization of DER in the presence of more fluctuating but plausible solar irradiance patterns. A sensitivity analysis has also been carried out to evaluate the impact of key parameters, such as the number of regions, a metric, and a specific parameter used for the outlier removal process on the generated solar irradiance profiles, by showing their influence on their smoothness and variability. The results of this analysis are found to be particularly suitable to guide users in the definition of scenarios with specific characteristics.

Fundamental Studies of Smart Distributed Energy Resources along with Energy Blockchain

This article studies the broad methodology and major application of smart distributed energy resources (DER) in terms of energy generation, consumption, transaction, and power scheduling. This article simplifies a general DER system into a generic type of integrated DER model. This model is used to investigate a smart DER system that transforms three input parameters, (3I parameters) into three critical output functions(3O functions); hence, the model is also called the 3I3O model. The power at a common connection joint can be enabled by a computer that makes computerized decisions to utilize smart DER. Therefore, the computer algorithm collects various data fed into a computer for deep learning and artificial intelligence (AI) decision making. The authors demonstrate important results and the best solutions to meet power demand, offer an economic advantage and have a low carbon footprint for consumers. Moreover, several network blockchain options are discussed. EBC and DER represent an ideal combination with advantages in managing exergy through so-called intelligent power technology. This technology is discussed in detail and includes special hardware, software, and a broad set of computerized intelligence. Finally, the exergy that can possibly be achieved for smart DER systems is discussed.