Distributed Power Resources Research Articles

Information control model of distributed energy resources

Currently, there is a constant growth of distributed energy resources, it became necessary to integrate them into the power grid. However, the integration process must consider not only the control parameters of the distributed energy resource but also the parallel operation of several such resources, the parameters of the power system as a whole. At the highest level of control, it is also necessary to consider the economic indicators formed by the energy market. Special devices – controlled inverters – can be effectively used for integration. The most difficult task is choosing a control system for controlled inverters. There are many different control systems such as Proportional-Integral, Deadbeat controllers, etc. The purpose of this paper is to build an information model for controlling distributed power resources. The current control method was used to control active and reactive power. The advantage of current control is resistance to variations in the parameters of the inverter and the external grid, excellent dynamic performance, and higher control accuracy. The proposed approach for building an automatic control system using the Internal model control strategy and taking into account restrictions on the control variable. The advantages of a system with an Internal model control controller compared to a conventional Proportional-Integral controller are the use of a powerful control method based on the object model, the ability to influence the roughness of the system with a separate setting parameter, increased speed with almost complete absence of over-regulation, simplified setup procedure. Such a system is proposed for use in facilities with strict requirements to minimize over-regulation and the speed of working out disturbances and tasks. The PSCAD software app was used to model the work results.

Multi-source data driven harmonic spectrum estimation of substation feeder current

With the proliferation of non-linear loads and distributed power resources that connect through power electronic equipment, decentralized harmonic pollution in three-phase symmetric power system becomes increasingly serious. Despite this, monitoring the current harmonic of all substation feeders regardless of cost is unrealistic. To this end, a multi-source data driven method is proposed in this paper, utilizing data from the power quality monitoring system, dispatching system, and market business system, to estimate the harmonic spectrum of substation feeder currents and estimate the harmonic current components of each feeder with monitoring data of bus voltage harmonics and line harmonic currents. The objective function of the harmonic spectrum estimation model is constructed based on the analysis of current harmonic phasor and power relationship on the feeders. An improved particle swarm optimization (PSO) algorithm is proposed to solve the proposed estimation model thereby obtaining the current harmonic content of each feeder and the phase angle difference between the current harmonics of the feeders. The performance of the proposed model and algorithm is validated by numerical simulation with a test system and an actual system.

Impact of Transportation Electrification on the Electricity Grid—A Review

Transportation electrification is a pivotal factor in accelerating the transition to sustainable energy. Electric vehicles (EVs) can operate either as loads or distributed power resources in vehicle-to-grid (V2G) or vehicle-to-vehicle (V2V) linkage. This paper reviews the status quo and the implications of transportation electrification in regard to environmental benefits, consumer side impacts, battery technologies, sustainability of batteries, technology trends, utility side impacts, self-driving technologies, and socio-economic benefits. These are crucial subject matters that have not received appropriate research focus in the relevant literature and this review paper aims to explore them. Our findings suggest that transitioning toward cleaner sources of electricity generation should be considered along with transportation electrification. In addition, the lower cost of EV ownership is correlated with higher EV adoption and increased social justice. It is also found that EVs suffer from a higher mile-per-hour charging rate than conventional vehicles, which is an open technological challenge. Literature indicates that electric vehicle penetration will not affect the power grid in short term but charging management is required for higher vehicle penetration in the long-term scenario. The bi-directional power flow in a V2G linkage enhances the efficiency, security, reliability, scalability, and sustainability of the electricity grid. Vehicle-to-Vehicle (V2V) charging/discharging has also been found to be effective to offload the distribution system in presence of high EV loads.

Peak-valley tariffs and solar prosumers: Why renewable energy policies should target local electricity markets

There is a growing recognition that local electricity markets (LEMs) for distributed power resources are technically and economically feasible. However, the conditions under which these markets can create value for prosumers and consumers (P&C) and ensure overall welfare for society are insufficiently understood. To help address this literature gap, this paper takes China as a case to study a local electricity market that is driven by peer-to-peer trading. The results show that peak-valley tariffs increase cost-savings for P&C at the expense of grid revenue and the larger the peak-valley spread, the greater the benefits to P&C and, hence, losses to the grid. In addition, the study finds that the value of solar PV declines when deployment of solar technology increases linearly with storage installation in the market. Because the declining value of variable renewable energy may be especially problematic in wholesale electricity markets (WEMs), this study argues that as long as storage installation increases at a faster rate than variable renewable energy deployment, LEMs that operate independent of the central grid can potentially offer a more cost-effective option for large-scale renewable energy utilization. These results underscore the importance of government policies that seek to promote the development of LEMs.

Machine Learning Assisted Energy Optimization in Smart Grid for Smart City Applications

Peer-to-peer electricity transaction is predicted to play a substantial role in research into future power infrastructures as energy consumption in intelligent microgrids increases. However, the on-demand usage of Energy is a major issue for families to obtain the best cost. This article provides a machine learning predictive power trading framework for supporting distributed power resources in real-time, day-to-day monitoring, and generating schedules. Furthermore, the energy optimization algorithm used in machine learning (EOA-ML) is proposed in this article. The machine learning-based platform suggested two modules: fuel trading and intelligent contracts based on machine learning implemented predictive analytical components. The Blockchain module enables peers to track energy use in real-time, manage electricity trading, model rewards, and irreversible transaction records of electricity trading. A predictive analysis component based on previous power usage data is designed to anticipate short-term energy usage in the Intelligent Contracts. This study utilizes data from the provincial Jeju, Korea’s electricity department on true energy utilization. This study seeks to establish optimal electricity flow and crowdsourced, promoting electricity between consumers and prosumers. Power trading relies on day-to-day, practical environmental control and the planning of decentralized power capitals to satisfy the demands of smart grids. Furthermore, it employs data mining technologies to obtain and study time-series research from the past electricity utilization data. Thus, the time series analytics promotes power controllingto better future efficient planning and managingelectricity supplies. It utilized numerous statistical methods to assess the effectiveness of the suggested prediction model, mean square error in different models of machine learning, recurring neural networks. The efficacy of the proposed system regarding the delay, throughput, and resource using hyperleader caliper is shown. Finally, the suggested approach is successfully applied for power crowdsourcing between prosumer and customer to reach service reliability based on trial findings. The actual and predicted cost analysis has been increased (95%). It minimizes the delay rate to (40.3%) by improving the efficiency rate.

Evaluation model of key driving factors for different types of demand side distributed power resources to participate in market transactions

Customer side distributed power resources are of great significance for low-cost guarantee of supply and demand balance and system peak shaving, and participation in market transactions is conducive to reducing project operation costs. Connotation and types of customer side comprehensive resources are analyzed, constructing the driving factor index system for customer side resources to participate in market transactions, including three indicators: internal rate of return of project investment, cost performance of participating in transactions and meeting their own electricity demand, and the perfection of supporting policies for participating in transactions, and evaluating the key driving factors for current relatively mature gas-fired CCHP, distributed photovoltaic power generation, electrochemical energy storage and demand side response resources to participate in market trading, putting forward the implementation path suggestions, promoting the large-scale and normalized trading of qualified customer side resources.

Transient Stability of Voltage-Source Converters With Grid-Forming Control: A Design-Oriented Study

Driven by the large-scale integration of distributed power resources, grid-connected voltage-source converters (VSCs) are increasingly required to operate as grid-forming units to regulate the system voltage/frequency and emulate the inertia. While various grid-forming control schemes have been reported, their transient behaviors under large-signal disturbances are still not fully explored. This article addresses this issue by presenting a design-oriented transient stability analysis of the grid-forming VSCs. First, four typical grid-forming control schemes, namely, the power-synchronization control (PSC), the basic droop control, the droop control with low-pass filters (LPFs), and the virtual synchronous generator (VSG) control, are systematically reviewed, whose dynamics are characterized by a general large-signal model. Based on this model, a comparative analysis on the transient stabilities of different control schemes is then carried out. It reveals that the PSC and the basic droop control can retain a stable operation as long as there are equilibrium points, due to their noninertial transient responses, while the droop control with LPFs and the VSG control can be destabilized even if the equilibrium points exist, due to the lack of damping on their inertial transient responses. With the phase portrait, the underlying stability mechanism is explicitly elaborated, and the quantitative impacts of the controller gains and the virtual inertia are clearly identified. Subsequently, controller design guidelines are proposed to enhance the system damping as well as the transient stability. Finally, experimental results are provided to verify the theoretical analysis.

An energy sharing scheme based on distributed average value estimations for islanded AC microgrids

Autonomous, self-governing micro energy networks are a smart energy solution that satisfy the energy needs of isolated communities. Such smart micro networks usually comprise of several distributed semi-controllable power resources, storages and loads. Usually, the power generation sources draw their energy from renewable energy resources. Power electronics converters suitably condition the power to be transmitted and utilized. A sensory, control and communication layer ensures the integration of several network components to achieve stable network operation. Distributed power-sharing methods function at local processing and decision-making nodes across the energy network. The complete control scheme is a hierarchical structure divided into four control levels. Faults and latencies experienced at the communication network layer adversely affect the performance of the control scheme. This paper proposes a new and improved hierarchical, multi-agents-based control strategy for efficient power-sharing, voltage and frequency regulation between nodes during communication link latencies. A novel distributed averaging estimator is proposed to estimate power injected in the system at various nodes and thereby mitigate the effect of relayed information delays. The effectiveness of the proposed strategy is established comprehensively through mathematical modeling, analytical proofs, discrete-time small signal stability analysis, and MATLAB case study simulations.

Decision-making Model of Virtual Power Plant for Participating in Spot Market Transaction Based on Hybrid Stochastic and Robust Approach

China is vigorously promoting the reform of the electricity spot market after the notice on the development of pilot projects for the spot electricity market was issued in 2017. At the same time, china is upgrading and renovating its energy structure, in the context of structural reform on the energy supply side, the decentralized form of clean energy utilization will develop rapidly. With the continuous improvement of the trading mechanism in spot market, it has become an inevitable trend that many distributed power resources will be involved in electricity market to participate in market transaction. Therefore, in order to promote distributed energy to participate in spot market, virtual power plant technique is paid increasing attentions. Combining the current hot issue, this paper constructs a decision-making model of virtual power plant for participating in spot market transaction based on hybrid stochastic and robust method, which can provide a quantitative decision analysis tool for virtual power plant operators to participate in spot market transactions. The main contribution of this paper are as follows:1) we proposed a transaction decision model that based on hybrid stochastic optimization and robust optimization methods and example simulation was given to illustrate the effectiveness of the model; 2) this paper focused on the electricity market in china.

A Study on Seismic Resilience Evaluation Method of Electrical Distribution Network with Distributed Power Resources

A Study on Seismic Resilience Evaluation Method of Electrical Distribution Network with Distributed Power Resources

Research on Distributed Power Capacity and Site Optimization Planning of AC/DC Hybrid Micrograms Considering Line Factors

With the rapid development of AC/DC hybrid microgrids and the widespread use of distributed power resources, planning strategies for microgrids with high-density distributed power generation have become an urgent problem. Because current research on microgrid planning has not considered line factors, this paper analyses the planning of an AC/DC hybrid microgrid based on an AC microgrid. The capacity and siting of the distributed power resources are optimized, taking into account the influence of the line investment cost and the interactive power upper limit on the planning results. In the proposed model, the objective is aimed at minimizing the sum of investment cost, load-loss economic cost, and system losses, taking into consideration power balance constraints and feeder number constraints. The commercial solver CPLEX is applied to attain the optimal distributed power capacity and site. The theoretical results are verified by an actual system.

System design to reduce disaster risks by installing distributed power resources

Subsidy and social systems should be designed to effectively promote, for example, the introduction of a mechanical system. For an effective subsidy distribution, developing evidence-based decision-making methodologies is essential. We developed a tool that minimizes an objective function includes economic costs, environmental cost, and disaster risk to determine the amount of energy distributed by the equipment when installing in hospitals against disasters. Open data available on the Internet are used as simulation values herein. This simulation model optimizes six design values using a genetic algorithm based on the values (business site area, demand for heat and electricity, and maximum allowable loss) input by customers for their construction and visualizes the total cost. The tool allows to quantitatively assess the changes in the initial and running costs owing to equipment installation and the avoidable losses related to $$\hbox {CO}_{2}$$ emission reductions and disaster risks. In addition, the net present value (NPV) can be calculated using the obtained values for initial and running costs, thereby allowing to clearly estimate the return on investments after equipment installation. The opportunity profit can be calculated based on the difference between the NPV after 15 years assuming no risk and with disaster risks. A method to set this opportunity profit as a calculated subsidy amount is proposed herein. Decision support can be provided via these simulations to the customers and government subsidy system design engineers.

A new design of dual mode Type-II fuzzy logic load frequency controller for interconnected power systems with parallel AC–DC tie-lines and capacitor energy storage unit

A new design of dual mode Type-II fuzzy logic load frequency controller (DMT-IIFLC) for interconnected power systems with parallel AC–DC tie-lines and capacitor energy storage unit (CES) is proposed in this paper. Any optimum controller selected for load frequency control of interconnected power systems should not only stabilize the power system, but also reduce the system frequency and tie-line power oscillations and settling time of the output responses. In general proportional plus integral controllers are used for loadfrequency control but it does not eliminate the conflict between the static and dynamic accuracy. This dispute may be broken up by using the principle of T-IIFLC to utilize expert knowledge and being adaptive in nature. The dual-mode concept is incorporated in the proposed controller to improve the system performance. A DC link is connected in parallel with AC tie-line to stabilize the frequency of oscillations. In summation, the CES unit is found to be advantageous for secondary control in the power system and keeps the power quality with the distributed power resources. The CES, which are not aged to the frequent charging and discharging, has been a quick response and outstanding function during overload conditions. The system performance of the proposed controller have improved significantly when compared with PI and T-IFLC. It is also found to be less sensitive to the changes in the system parameters and also robust under different operating modes of the system.

Design and Simulation for Microgrid System Based on Homer Software

Aiming at some microgrid system in Shanghai, economic simulations and analyses are done. A microgrid including solar, wind power, microturbines, diesel engine, energy storage and other distributed power resources is constructed based on homer software and simulation parameters are set to make an optimum proposal. Further studies such as running on the grid, changing the cost of distributed energy and operating in the PV / wind power plant mode are discussed.

Study on Load Frequency Control Using Redox Flow Batteries

Rechargeable batteries such as redox flow, which are not aged by frequent charging and discharging, have a quick response equivalent to SMES and outstanding function during overload. The battery efficiency increases when the cycle period of charging/discharging becomes shorter. In addition to leveling load, the battery is advantageous for secondary control in the power system and maintenance of power quality of distributed power resources. In this paper, we study the control performance of RF battery systems in its application to LFC. Using dynamic simulation, we show that the LFC capacity of RF battery systems is ten times that of fossil power systems due to quick response characteristics.

State of the Arts of Friends on 2003

FRIENDS(Flexible, Reliable and Intelligent Energy Delivery System)is a new power delivery concept which enablesto connect distributed power resources to power delivery system and to realize customized power quality servicesby controlling them. This paper introduces following 4 items of recent technological developments in FRIENDS: (1) an optimal network configuration method of FRIENDS in urban area from a viewpoints of supply reliability, (2) a fault state autonomous restoration method of FRIENDS through multi-agent system, (3) DC loop type QCC(Quality Control Center) to realize the customized power quality services for the area where DC power supply is dominating, (4) economical aspect of the customized power quality services.