Distributed Power Generation Research Articles

Stackelberg-Game-Based Demand Response for Voltage Regulation in Distribution Network with High Penetration of Electric Vehicles

With the development of the economy, electricity demand continues to increase, and the time for electricity consumption is concentrated, which leads to increasing pressure on the voltage regulation of the distribution network. For example, a large number of electric vehicles charging during a low-price period may cause the problem of under-voltage of the distribution network. On the other hand, the penetration of distributed power generation of renewable energy may cause over-voltage problems in the distribution network. This study proposes a Stackelberg game model between the distribution system operator and the load aggregator. In the Stackelberg game model, the distribution system operator affects the users’ electricity consumption time by issuing subsidies to decrease the frequency of voltage violations. As the representative of users, the load aggregator helps the users schedule the demand during the subsidized period to maximize profits. Case studies are carried out on the IEEE 33-bus power distribution system. The results show that the time of the subsidy can be optimized based on the Stackelberg game model. Both the distribution system operator and the load aggregator can obtain the optimal economic profits and then comprehensively improve the operating reliability and economy of the power distribution system.

An Advanced Boundary Protection Control for the Smart Water Network Using Semisupervised and Deep Learning Approaches

Critical infrastructures across many industries, such as smart water treatment and distribution networks (SWTDNs) and power generation and public transport networks, depend on the supervisory control and data acquisition (SCADA) system. However, being the core component of the critical infrastructures, it has made the SCADA-based SWTDN system an attractive target for cyberattacks. A successful attack on the SCADA will have a devastating impact on an SWTDN in terms of proper operations; therefore, safeguarding the SCADA from cyberattacks is of paramount. With the increasing cyberattacks on SWTDN, both in number and sophistication, the need to detect these attacks early has become a subject of great interest among practitioners and researchers. To this end, we propose a novel strategy, based on a semisupervised approach. Two semisupervised approaches, including unsupervised learning and deep learning-based approaches, have been proposed. The proposed approaches can involve learning dynamic cyberattack patterns from unlabeled data in an SWTDN. We validate the proposed semisupervised approach experimentally using an operational water treatment plant testbed. The proposed approach achieved almost 100% accuracy and substantially outperforms the existing baseline approaches used in this article. The outcome of the experiment is encouraging and demonstrates the potential use of the semisupervised approach for security control in smart water distribution.

Eco-feasibility study of a distributed power generation system driven by renewable green energy sources

ABSTRACT This paper improves a previously optimization approach to accomplish an enhanced total cost of electricity (TCE). Based on the integration of many energy deposits for supporting the primary Renewable Green Energy Source (RGES), the whole system is modeled with improved manner, which contributes to well achieve a more comprehensive write-up of the studied formulation problem. To decrease the TCE of the system containing a photovoltaic/wind turbine with battery storage system, the so-called virus colony search (VCS) algorithm is developed. Hence, the association of a lead-acid battery devoted to absorption of the high fluctuations is essential, which can contribute to the operational safety of the system. Thus, techno-economic analysis and cost-effectiveness evaluation are investigated. By depicting TCE as a key factor in this study and compared with other conventional algorithm, a reliability analysis is elaborated in accordance with the lowest cost of electricity. The obtained results prove a high level of economic feasibility in agreement with some evaluation criteria by achieving the lowest TCE. The benefit of the optimization based on VCS algorithm is successfully demonstrated in accordance with highest reliability by a significant saved cost. The results of the optimization display that savings in TCE is 14,792 $ as compared to the calculation process without using VCS algorithm.

Cascade utilization of organic Rankine cycle and absorption chiller assisted phosphoric acid fuel cell waste heat for dynamic building demands

The interest in fuel cells is rapidly increasing owing to the development of distributed power generation systems, and various attempts have been made to recover waste heat from fuel cells. This has led to the emergence of cascade heat utilization systems that integrate thermally driven equipment and fuel cells. However, the performance of these hybrid systems has been evaluated under steady-state conditions without considering energy demands, limiting the prediction of their effectiveness and feasibility in practical applications. To address this, a cascade system utilizing fuel cell waste heat is developed to investigate system performance and viability when applied to building energy demands under dynamic conditions. Annual profiles of energy sources and demands are collected to configure a holistic energy system and perform transient analysis. Numerical models of various components are developed and experimentally validated to reflect the actual performance. The cascade system is constructed by integrating the components based on their operating temperature and purpose. A novel dual cascading strategy is adopted using tap water as the heat sink medium to recover the low-temperature waste heat dissipated from the bottoming cycles. In addition, the overall equipment effectiveness of the main components is evaluated to verify accurate determination of operation time and capacity. The proposed system reduces the primary energy consumption and carbon dioxide emissions by 15.8% and 15.4%, respectively, compared to the conventional system. The best-case scenario results in an internal rate of return and payback period of 21.74% and 4.77 years, respectively, indicating the economic feasibility of the proposed system.

Energy Management Strategy of a Reconfigurable Grid-Tied Hybrid AC/DC Microgrid for Commercial Building Applications

This paper proposes an energy management strategy (EMS) of a reconfigurable grid-tied hybrid ac/dc microgrid (HMG) architecture for commercial building (CB) applications. This HMG architecture consists of a multi-mode configuration (MMC) with renewable-based distributed generators (DGs), energy storages (ESs), and genset. The main advantage of this architecture is its capability to reconfigure its structure based on the predicted building load power (BLP) and renewable-based DGs power. However, minimizing the building electricity cost (BEC) and maximizing the reliability index (RI) of a reconfigurable grid-tied HMG architecture is a challenging task due to the stochastic behaviors of BLP and renewable-based DGs power. In this context, the BLP and renewable-based DGs behaviors are modeled using an artificial neural network approach to predict future time slot values. Then, system level models are developed for HMG energy sources and grid-tied converters/switches. Furthermore, BEC and RI models are developed based on the dynamic pricing of grid/HMG electricity cost and supplied energy. Then, an EMS is proposed for the developed reconfigurable grid-tied HMG architecture, which consists of a two-stage control strategy, i.e., stage I and stage II. Stage I control strategy minimizes BEC and maximizes RI using multi-objective particle swarm optimization (MOPSO) and MMC. Stage II control strategy generates control signals for HMG energy sources, converters, and grid-tied converters/switches based on stage I reference signals. Historical data is used to demonstrate the effectiveness of the proposed EMS for a reconfigurable grid-tied HMG architecture. Through numerical simulation studies, it is shown that the proposed EMS is capable of reducing BEC and increasing RI by concurrently enabling MMC of a reconfigurable grid-tied HMG architecture.

Vibration damping of a vertical axis wind turbine in operating conditions

Distributed power generation technologies have been, over the years, gaining more and more attention from the industry as well as from the academia, due to the global interest in the exploitation of renewable energy sources even in urban areas. From this perspective, small size wind turbines, often with vertical axis layout and a nominal power between 1-3 kW, are being installed in urban areas on rooftops of residential, commercial, industrial buildings and even on metallic carpentry towers. As wind turbines tend to produce noise and vibrations, especially in presence of vortexes, wakes and unsteadiness, efficient devices for mitigating the vibrations transmitted to the supporting structure have to be added in order to limit the generation of stresses. Actually, the social acceptance of the installation of small wind turbines in built environment is tightly connected to the acoustic comfort for the inhabitants. The present study has been developed thanks to a joint collaboration between the Department of Engineering of the University of Perugia (Italy) and FH Technikum Wien (Austria) within the participation to the IEA Wind-Task 41: “Distributed Wind”. The work aims at mechanically characterizing the vibration damping provided by a mechanical device installed on the top of the turbine tower support. The decoupler, specifically designed for this purpose, has been tested in different conditions (in field and laboratory) and with different approaches, in order to have an overall evaluation of its performance. At first, vibrations are measured in open field in a real test case scenario with two installation arrangements: on the rooftop of a small building and on a tubular tower. Subsequently, the decoupler has been removed from its original location and tested in laboratory with external excitation from shaker.

Co-optimizing transmission and active distribution grids to assess demand-side flexibilities of a carbon-neutral German energy system

In modern power system planning and operation, the relevance of distributed power generation units and demand-side flexibility options grows. As a consequence, smart planning and operation routines become necessary also in the distribution grid. We therefore develop a co-optimization framework to consider transmission and distribution system constraints and their interactions together. This enables bidirectional flows between both systems, supporting a consistent and cost-efficient overall energy system. The key feature of this paper is an automated coupling of two independently and modularly defined systems. It allows a bottom-up modelling approach of energy demands, conversion and storage technologies from both system levels. However, this approach increases the model size significantly. Thus, timeseries aggregation methods are applied to reduce the computational complexity. The results for the optimal planning of the coupled German energy system show that the electrification of heat and mobility sectors in the distribution grid is not only beneficial to achieve carbon neutrality in 2050, but also to particularly make use of additional flexibility potentials. Our results underline a significant positive correlation between a smart operation of heat pumps and charging stations with the maximum integrable capacities of low-cost rooftop photovoltaics in the distribution system.

Microbial Fuel Cell for Wastewater Treatment as Power Plant in Smart Grids: Utopia or Reality?

Microbial fuel cells (MFCs) have undergone great technological development in the last 20 years, but very little has been done to commercialize them. The simultaneous power production and wastewater treatment are features those greatly increase the interest in the use of MFCs. This kind of distributed power generation is renewable and friendly and can be easily integrated into a smart grid. However, there are some key issues with their commercialization: high construction costs, difficulty in developing high power structures, MFC lifespan, and maintaining a high level of efficiency. The objective of this article is to explore the possibilities of using MFCs in urban wastewater not only regarding the technical criteria of their application, but also mainly from an economic point of view, to determine the conditions through which the viability of the investment is ensured and the possibilities of their integration in a smart grid are identified. Initially, this article explores the implementation/configuration of a power plant with MFCs within an urban wastewater treatment plant on a theoretical basis. In addition, based on the corresponding physical quantities for urban wastewater treatment, the construction and operational costs are determined and the viability of the investment is examined based on classic economic criteria such as net present value, benefit–cost ratio, internal rate of return, and discounted payback period. Furthermore, sensitivity analysis is carried out, concerning both technical parameters, such as the percentage of organic matter removal, power density, sewage residence time, MFC efficiency, etc., and economical parameters, such as the reduction of construction costs due to change of materials, change of interest rate, and lifetime. The advantages and disadvantages of their use in smart grids is also analyzed. The results show that the use of MFCs for power generation cannot be utopian as long as they are integrated into the structure of a central wastewater treatment plant on the condition that the scale-up technical issues of MFCs are successfully addressed.

Methods to Improve Dynamic System Response of Power Compensators Using Supercapacitors in Low-Voltage Ride-Through (LVRT) Conditions

In this paper, a power compensator using supercapacitors in parallel to protect grid-connected devices connected to the distributed power supply in the case of a low-voltage ride-through (LVRT) situation in designed, and a grid-connected device control method with improved responsiveness is proposed. In the LVRT situation, the distributed generation power may boost the DC_link voltage, increasing the risk of destroying grid-connected devices. To prevent this, the power compensator designed in this study absorbs active power in a fault situation and stores it in the supercapacitor to suppress the DC_link voltage rise and efficiently use the power. In addition, we propose methods to improve the response of the grid reactive power through the reactive power compensation of the power compensator in LVRT situation. To this end, the power angle (θPW) was extracted through the formula, and the reactive power command, to be compensated by the power compensator, and the reactive power command, compensated by the grid-connected devices, were calculated according to the active power value. In this way, the grid power controlled by the power compensation device and the grid-connected devices was controlled by the active/reactive power of the same power angle and analyzed mathematically. Active power control and static grid support were performed in the normal state where the reduction rate of the normal value of the grid voltage was around 10%. However, when the grid voltage dropped by 10% to 100%, the reactive power control was appropriately performed with dynamic grid support by increasing the voltage from 10% to 20% or more. We conducted a simulation of the new and renewable energy grid-connected devices using the OPAL-RT-based Hardware-in-the Loop Simulation (HILS) system to control the proposed active/reactive power.

Research on the Mechanism of Aggregate and Distributed Generation Participating in the Power Market

In recent years, distributed power generation has made great progress, but it is still restricted by factors such as low marketlization, lagging public services, and incomplete management systems. This paper studies the trading mechanism of distributed power participation in the market. First, it studies the participation of aggregated distributed power generation resources in the power market; then based on the model of distributed power generation resources that participating in the market through aggregated agents based on this article, the market mechanism is designed.Finally, a calculation example is adopted and the proposed method is verified.

Research on the influence of distributed generation and its grid connection on power system

Abstract China’s per capita resources are scarce and consumed very quickly. New energy power generation has the characteristics of green, environmental protection and renewable, and it is the main development direction of the current and future power industry. With the continuous expansion of new energy power generation and grid-connected scale, various adverse effects brought to the power grid in the process of grid-connected are gradually emerging and becoming more and more serious.This paper briefly introduces the distributed power generation, and then studies and analyzes various problems brought by the grid connection of new energy to the power system from the four aspects of grid voltage, grid harmonics, grid frequency, and grid protection, and gives some solutions. For example, if the power generation equipment meets the grid-connection standard, a real-time monitoring device for power quality and a dynamic reactive power compensation device can be installed; for harmonic pollution problems, multi-pulse converters and power filter devices can be used; for power quality problems in the distribution network, the structure of the power grid can be optimized., Reasonable selection of the impedance ratio of the circuit, etc.

Multi-object optimal configuration of energy storage-photovoltaic capacity in AC/DC active distribution network

Abstract The AC/DC active distribution network is considered as an efficient way to achieve intelligent use of electricity. However, the economical configuration of distributed generation is critical for system economic operation. In the power distribution network, the economic operation mode of the photovoltaic power generation, storage battery and load are established firstly. Considering the cost of equipment installation, replacement, operation and maintenance, power purchase cost, and power sales profit, the use life of battery and security constraint, a multi-object economics evaluation function is then established. By optimizing the install capacity of distributed power generation, the operating economy of the distribution network is significantly improved. Finally, using the operating data of the partner-type intelligent power generation system in Lianyungang, the total cost of the operating state is calculated to determine the optimal capacity allocation scheme of the system, and the effectiveness of the proposed capacity allocation method is verified.

Experimental verification of STATCOM based on quasi impedance source inverter for power quality enhancement in the hybrid distributed generation system

PurposeThis paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.Design/methodology/approachThe WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.FindingsThe coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.Originality/valueTo improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

Deep Reinforcement Learning-Based Adaptive Voltage Control of Active Distribution Networks with Multi-terminal Soft Open Point

The integration of highly penetrated distributed generators (DGs) aggravates the rise of voltage violations in distribution networks. Connected by multi-terminal soft open points (M−SOPs), distribution networks gradually evolve into an interconnected flexible architecture with high controllability. Distribution networks with M−SOPs can exchange active power flexibly, and M−SOPs can provide local reactive power support to alleviate voltage violations. However, conventional model-based M−SOP optimization methods cannot regulate voltage profiles adaptively owing to the rapid fluctuations of DGs. In this paper, a data-driven voltage control method is proposed for M−SOPs using a deep deterministic policy gradient network (DDPG). First, the data-driven voltage control framework is proposed for M−SOPs based on DDPG. The M−SOP−based voltage control problem is reformatted as a Markov decision process (MDP) to construct the DDPG agent. Based on real-time measurement, the DDPG agent can adaptively regulate the M−SOP operation to address the frequent DG fluctuations. Then, a multi-dimensional and dynamic boundary action masking approach is proposed to address the complex coupling in the action space of M−SOPs. Finally, the effectiveness of the proposed method was verified using the IEEE 33-node system. The results show that the proposed method can adaptively alleviate the voltage fluctuations caused by rapid DG power variations.

A switched quasi Z-source three-port (SqZSTP) DC-DC converter for a photovoltaic power generation system

In this paper, a modified wide-input switched quasi Z-source three-port (SqZSTP) DC-DC converter is proposed to interface a photovoltaic inverter with a distributed power generation system. The proposed SqZSTP DC-DC converter constructed with a quasi Z-source impedance network and a three-winding high-frequency transformer offers high voltage gain over a wide input voltage range. In the proposed topology, the input port is divided into two ports, to reduce the power rating and voltage stress across each component. The design and operating principles of the SqZSTP DC-DC converter are presented. The steady state and dynamic performance of the proposed SqZSTP DC-DC converter are compared to other converters that have an impedance network in front. The fuzzy logic controller used in the voltage loop avoids variation in the output voltage when a wide variation in the input voltage happens. In order to test the proposed topology, a scaled-down model with a voltage and power rating of 400 V/1400 W was developed. AT conversion efficiency of 94.5% is achieved.

Research on multi-objective operation optimization of multi energy integrated service stations based on autonomous collaborative control

Multi energy integrated service stations have strong comprehensive energy and coupling properties, covering functional units such as substation, multi type energy conversion station, data center, distributed power generation, charging and replacement power station, wireless base station and so on. However, with the continuous improvement of the physical complexity of power grid information, there are still great theoretical and practical difficulties on how to build the operation optimization architecture of energy integrated service station and realize the organic integration of energy flow, data flow and business flow. The typical model forms of various equilibrium equality constraints and inequality constraints between stations and stations are established, and the multi-objective operation optimization model is established and solved. The results show that it improves the level of multi energy conversion, multi energy complementarity, comprehensive energy utilization efficiency, realizes the purpose of collaborative control optimization of multiple energy integrated service stations, and effectively promotes the maximum local consumption of renewable energy.

Fault Location Analysis in Active Distribution Network Based on Multi-population Genetic Algorithm

Because the fault location of active distribution network is a complex optimization model, the traditional genetic algorithm has the problems of premature and slow convergence when solving complex optimization problems. The switch function that can adapt to the switching of multiple distributed power sources in real time is proposed. Here, we proposed a novel method to locate the fault of distributed power distribution network based on a multi-group genetic algorithm. When locating the fault zone, The algorithm stipulates that the direction of the generator flowing to the electrical equipment is the forward direction of the transmission line. In this paper, multiple populations are used to search the solution range at the same time to ensure that the final solution is the global optimal solution, and the optimal individual retention algebra is used as the convergence condition to fully improve the solution speed, which is suitable for complex distribution networks with distributed power generation. The fault location model proposed in this paper is simulated by a numerical example, and the results show that the model can accurately find the fault point, and has validity and accuracy.

Synchronous Generator Imitation Control and Dynamic Power Sharing for Distributed Power Generation Systems

In this paper, a control method called synchronous generator imitation control (SGIC) as well as a dynamic power sharing for distributed power generation systems (DPGSs) are presented. In order to imitate the behavior of a synchronous generator (SG), the SGIC method for the voltage source converter (VSC) station is proposed. The SGIC includes three loops, namely active power and frequency loop (Pf loop), reactive power and voltage loop (QU loop) as well as inner current loop. The Pf loop is used to emulate the swing equation of the SG. The exciter of the SG is mimicked by the QU loop. The inner current loop is developed for fast current and voltage regulations as well as current limiting. The system stability performances are analyzed through small-signal model, and the effectiveness of the proposed control is validated by PSCAD/EMTDC simulations. The results show that the Pf loop of the VSC emulates the motion equation of the SG rotor very well, which makes the VSC station to have inertia just as a SG; the VSC station can maintain a stable output voltage and regulate the reactive power at the same time; through the dynamic power sharing, precise power control, frequency offset elimination and system stability improvement are achieved; the system has the merits of fault ride-through capability as well as good dynamic performance.

Model Predictive Control for Three-Phase Three-Level NPC Inverter Based APF Interfacing Single Stage Photovoltaic System to the Grid

A finite control set model predictive control (FCS-MPC) based controller has a fast dynamic response and robustness. furthermore, the presence of a cost function gives designers a degree of freedom to include system control targets, constraints and system non-linearities. On the other hand, Multilevel inverter (MI) topologies are becoming a strong alternative in distributed power generation system (DPGS), among these topologies is the three-phase three-level NPC (TTLNPC) inverter. Generally, to properly operate this topology, the applied current control ensures the achievement of two main objectives. First, the output current must be controlled to track its reference. Second, the two dc-link capacitor voltages have to be equal and balanced. In this paper, FCS-MPC is proposed to control the TTLNPC inverter based parallel active power filter (APF) adopted to connect a photovoltaic system (PVS) to the grid and perform a harmonic mitigation. The proposed FCS-MPC exploit the model of the system to predict the future values of the inverter currents by selecting the best voltage vector that aims to minimize a predefined cost function. Instead of using the popular redundant vectors algorithms to balance the two-split dc-link capacitor voltages, another term will be added to the expression of the cost function to achieve this goal. The PV panel is coupled directly to the inverter without DC/DC converter, the P&O MPPT algorithm is responsible to generate the capacitor reference voltage whatever the climatic conditions are. Simulations using Matlab/Simulink were performed to prove the efficiency of the proposed technique to mitigate the grid current harmonics, and to ensure a continuous power injection and perform a load power sharing.

Energy Management in the Microgrid and Its Optimal Planning for Supplying Wireless Charging Electric Vehicle

The ongoing research work on electric vehicles (EVs) as well as the growing concern around the world to ensure a pollution-free environment is sure to lead to a significant increase in the number of EVs in the near future. The electrification of automobiles is an inevitable trend of future development. However, the growth of EVs relies on several elements: autonomy, the charging practice and infrastructure, the price, and the high amount of energy needed for supplying EV. This tendency impacts several points in transportation such as the road infrastructure and electrical power network. The aim of this article is the integration of new energy power sources as a part of the microgrid (MG) to supply EV with dynamic wireless charging. The main goal is to establish an energy management strategy reducing the running cost. The purpose is suggested for two kinds of operation mode: relying only on the MG (island mode) or relying on the MG and the large grid (grid-connected). The optimization problem is solved on the basis of the particle swarm optimization (PSO) algorithm. We could note that the stability of the microgrid in the off-grid mode is better, when the load is close to the output power of the distributed power supply. Through the coordination and cooperation of the battery output and the other two distributed power generation units, the microgrid can achieve its autonomy and maximize the economy of the system operation. Thanks to our methodology, a better revenue and an enhanced flexible dispatching of the system were met in the grid-connected mode as well.