Distributed Generation Sources Research Articles

A Novel Reclosing Scheme for Mitigation of Distributed Generation Effects on Overcurrent Protection

This paper proposes a novel scheme to mitigate distributed generation (DG) effects on existing fuse-recloser protection infrastructure in radial distribution networks. The proposed scheme employs a control unit, variable load bank, and dedicated recloser at the point of common coupling (PCC). It detects the increase in the DG terminal current producing a tipping signal when it exceeds a preset value. The proposed scheme also receives a fault detection signal from the head-end recloser via a fast communication channel. Upon verifying both signals, the scheme disconnects the DG unit from the system. Simultaneously, it connects a transfer impedance at the PCC to operate the DG unit at its prefault load-sharing condition. This allows the DG unit to continue supply to the transfer impedance at the prefault load-sharing condition, that is, maintain operation at the prefault level with no need for immediate shut down. Furthermore, it also allows the DG to maintain its speed and frequency at the prefault levels which, in turn, allows faster reconnection of the DG unit to the system after successful reclosing. For the case of unsuccessful reclosing or the case where the fault is not cleared within the set utility time set frame, the proposed scheme shuts the DG source down. The transfer impedance is selected from a variable load bank and is a function of the prefault load-sharing condition; therefore, a sensitivity survey was performed during the investigations of this paper to cover all possible system operating conditions and its corresponding transfer impedances. In the context of this paper, multiple in-depth time-domain simulations are conducted to ascertain the efficiency of the proposed scheme in mitigating the impact of DG sources on existing overcurrent protection infrastructure. Time-domain simulations have been conducted using a typical distribution network in the EMTP-RV software environment for validation purposes.

Optimal Integration of Multi Distributed Generation Sources in Radial Distribution Networks Using a Hybrid Algorithm

Distributed generation (DG) can be integrated into any radial distribution network (RDN) to meet the increasing demand for electric power. Instead of integrating a single large size DG, two or more than two small DGs (multi DGs) are usually placed. These DGs must be placed in appropriate buses/nodes with suitable size to ensure better performance of the system. The purpose of this paper is to implement an established hybrid optimization algorithm to place multi DGs with suitable size at each site. The proposed hybrid ABC-CS optimization algorithm combines the behaviour of the artificial bee colony (ABC) and cuckoo search (CS) algorithms. The multi DGs are optimally placed by considering objectives like power loss, penalty function (PE) and voltage profile (VP). The outcomes of two different types of radial distribution networks obtained by the suggested method for placement of multi DGs have been correlated to that obtained by using genetic algorithm (GA), particle swarm optimization (PSO) and GA-PSO. The proposed method has also been correlated with the other published methods to indicate its strength.

A Framework to Split the Benefits of DR Between Wind Integration and Network Management

In power systems today, considerable developments are being made in the energy transition from centralized fossil fuels to renewable distributed generation (DG) sources. However, this ongoing progress has presented several challenges to the operation and planning of distribution systems due to the variability of intermittent renewable generation. Demand response (DR) is widely regarded as a feasible tool to provide a seamless transition by altering the load profiles according to the intermittent generation profile. However, the resultant volatile power flows can be taxing for network capacity. This paper offers a framework from the distribution system operator's perspective for the optimal utilization of DR between DG curtailment mitigation and network management. The application of the developed framework to a generic Finnish distribution system demonstrates that the benefits of DR should be envisioned for network management as long as the wind curtailment rate is below a certain level. This means that, beyond the threshold energy curtailment rate, the distribution system operator would be more economically efficient by making network reinforcements.

Coordinated Volt-Var Control: Online Voltage-Profile Estimation in Smart Distribution Networks

The increasing penetration of intermitt ent and stochastic distributed generation (DG) sources in the existing power grid can lead to voltage rise problems. Meanwhile, the rapid development of smart grid technologies calls for effective solutions to realize the real-time measurements and coordinated volt-var control to improve the overall systems voltage profile (VP). This article presents online VP estimation and coordinated volt-var control in a smart distribution network with multiple DG systems.

Multi-Agent Decision Support Tool to Enable Interoperability among Heterogeneous Energy Systems

Worldwide electricity markets are undergoing a major restructuring process. One of the main reasons for the ongoing changes is to enable the adaptation of current market models to the new paradigm that arises from the large-scale integration of distributed generation sources. In order to deal with the unpredictability caused by the intermittent nature of the distributed generation and the large number of variables that contribute to the energy sector balance, it is extremely important to use simulation systems that are capable of dealing with the required complexity. This paper presents the Tools Control Center (TOOCC), a framework that allows the interoperability between heterogeneous energy and power simulation systems through the use of ontologies, allowing the simulation of scenarios with a high degree of complexity, through the cooperation of the individual capacities of each system. A case study based on real data is presented in order to demonstrate the interoperability capabilities of TOOCC. The simulation considers the energy management of a microgrid of a real university campus, from the perspective of the network manager and also of its consumers/producers, in a projection for a typical day of the winter of 2050.

Optimal Sizing for Grid-Tied Microgrids With Consideration of Joint Optimization of Planning and Operation

This paper presents a multiobjective optimization method to jointly optimize the planning and operation of a grid-tied microgrid (MG) with various distributed generation sources such as wind turbine and photovoltaic arrays with the assistance of demand side management. In order to explore the economy and demand variety, the problem is formulated as a double-objective optimization to minimize the total annual cost and to maximize the customer satisfaction. To solve the multiobjective optimization problem, a fuzzy satisfaction-maximizing method is adopted to convert the original problem into a single objective optimization problem and a mixed integer linear programming algorithm is then used to solve the problem. To verify the proposed solution, various case studies have been carried out and compared. The results show that the proposed method is effective in minimizing the cost of an MG without sacrificing the satisfaction of customers.

Comparison of the reactive control strategies in low voltage network with photovoltaic generation and storage

The aim of this study is to analyze the different decentralized voltage control strategies, based on the reactive power control of photovoltaic inverters. The study focuses on evaluating their impact in terms of reactive power demanded from the grid, due to the regulation, and active losses in the network and in the photovoltaic inverters. In a second step, the presence of battery energy storage systems in the network is considered and further analysis are performed, in order to take into account the overvoltage mitigation by peak shaving of the photovolta-ic generation. All the simulations are performed in MATLAB/SIMULINK, where the model of a single-phase low-voltage distribution network with distributed generation sources is implemented.

Placement of measurements for electrical distribution network state estimation

The paper is concerned with the problem of placement of the minimum number of smart meters to ensure either the observability of all state variables in distribution network or the observability of voltage magnitudes. Voltage control is important in the distribution network with distributed generation sources which adoption can lead to unpredictable overvoltage exceeding admissible values. The algorithm for smart meters including measurements of voltage magnitudes and active and reactive current injections is similar to the algorithm of choosing the minimum number of phasor measurement units to ensure topological observability. Optimal control of the active distribution network operation requires monitoring to be based on a classical linear state estimation procedure. The results of the research demonstrate the effectiveness of the proposed approaches and are illustrated by example of a test distribution network.

Feasibility Study and Analysis of a Micro-Grid Scheme for Federal University of Technology, Owerri, Imo State, Nigeria

The need for reliable, robust, clean and secure electrical energy has led to developments in distributed off-grid solutions. This work considers various distributed generation sources such as; hydro, solar and wind, within the specified environment. Its aim is to ascertain the most feasible micro-grid solution for the specified campus environment. The work evaluates various micro-grid models to ascertain the most suitable model for the campus environment. HOMER micro-grid optimization software was used to aid the analysis. The micro hydropower plant at Otamiri River was found to be a good source with the power output of 586kW, and cost of energy per kWh of $0.284. Consequently, the model of the micro-grid was further analyzed in MATLAB/Simulink to determine the behavior of the system. The effect of load variation and short circuit fault was observed, and it shows the performance of the system to be stable.

Optimal Placement and Sizing of Distributed Generation in an Unbalance Distribution System using Gray Wolf Optimization Method

The distributed generation sources (DGs) are becoming increasingly attractive due to introduction of small scale renewable energy sources. They can be integrated in to low voltage distribution networks, to reduce the burden on transmission and sub transmission network. However, the number of DGs, their placement, and sizing can influence the advantages from the distribution network operation point of view. Also, most of the time the planning is done considering the peak load demand only. However, the losses obtained at peak load, may not give the realistic picture. This paper demonstrates the application of a grey wolf optimisation method for obtaining the optimal size and location of DGs (solar photovoltaic-based) in an unbalanced distribution network. The method proposed in this paper provides a set of solutions from the point of view of voltage stability enhancement and loss minimisation. The utility can prioritise either voltage stability enhancement or loss minimisation or both to choose the best compromised solution. Moreover, the losses are calculated by considering the seasonal load and PV generation patterns during the year to simulate the real picture of distribution system. Results on 33 bus balanced and 25 bus unbalanced distribution system are taken to demonstrate the potential of the proposed algorithm.

Reactive Power Control of DGs for Distribution Network Voltage Regulation Using Multi-Agent System

Nowadays, with increase the installation of distributed generation (DG) sources in the distribution networks (DNs), the traditional voltage regulation devices with their conventional control abilities face several difficulties to solve the voltage regulation problems. The DG sources that have reactive power capability can greatly help to reduce the stress on the voltage regulation devices in DNs. This paper proposes an effective control strategy for voltage regulation in DNs with high DG penetration based on a multi-agent system (MAS). The proposed strategy is a simple and efficient method for managing the reactive power capability of various types of DG in DNs. The proposed control strategy utilizes voltage/reactive power sensitivity analysis to reduce the overall system voltage deviation. Comprehensive case studies on IEEE 33 test feeders are carried out to demonstrate the effectiveness of the control strategy. The numerical results show that the proposed strategy can significantly mitigate the voltage violation problems in a simple manner.

Promoting behind-the-meter battery storage: options for more effective government support and regulation

We examine the use of subsidies to promote behind-the-meter battery installation, the limitations and perverse outcomes created by these subsidies, particularly as a result of suboptimal spatial concentration. We suggest the use of consumer subsidies to promote behind-the-meter batteries is unlikely to lead to optimal outcomes in aiding the integration of distributed generation sources (solar PV). It is also possible batteries could reduce the reliability of the grid. The problems identified relate to the undirected installations of batteries within the grid due to the reliance on consumers to take part in a subsidy scheme. Recommendations for policy makers and regulators are to encourage optimal installations through directing subsidies, and in lieu of that, to orchestrate and/or coordinate individual installed battery capacity.

The Effects of Distributed Generation Sources within Commercial Retail Reticulation Networks

Distributed Generation (DG) systems are becoming more common with increasing electricity prices and growing awareness of sustainable energy generation sources. Reticulation networks are typically planned, designed and operated to be purely passive networks that deliver electricity to consumers in a unidirectional manner (from source to load). The integration of DG into reticulation networks can alter conventional power flow within the network, as well as load parameters. The effects of DG on load and network parameters is investigated in this paper through the use of a developed hypothetical commercial reticulation network and load demand profiles. The introduction of a DG source at low levels of penetration was found to not significantly alter load parameters, although effects are noticeable. The largest variation in load parameters can be observed at high levels of DG penetration. Since load parameters (such as coincident demand) play an important role in the design of reticulation networks, the results obtained from this study indicate that current design procedures and standards for reticulation networks must be scrutinized when high levels of DG penetration are introduced.

Energy management systems for hybrid distributed generation sources in grid connected and stand-alone micro-grids

This paper proposes energy management systems for micro-grids. In recent years, the use of renewable energy sources in micro-grids has become an effective means of power decentralization especially in remote areas where the extension of the main power grid is an impediment. But a mixture of renewable energy sources and conventional generation poses serious challenges in the operation and control of micro-grids as a result of the uncertainty associated with renewable sources. Therefore, excellent energy management with regards to the power production, control, reliability, and consumption is needed in the power system. The main objective of the energy management system is to minimize the system cost as well as meeting the demand. In order to take into account the uncertainties of distributed generators (DGs) and load consumption, demand response participation and load shedding is taken into account. Two different types of algorithms are used to solve the smart energy management system of the micro-grid. To minimize system costs, which includes unit commitment and demand response, a genetic algorithm is used. To further balance the supply and demand during extreme cases, load shedding is employed through the use of the artificial neural network. The simulation results displayed corroborate the merit of the proposed method.

OPTIMAL DG PLACEMENT IN A RADIAL DISTRIBUTION NETWORK FOR RELIABILITY IMPROVEMENT

This paper presents an efficient Grey Wolf Optimization technique to improve the reliability of distribution systems. Various reliability objectives such as energy not supplied, System Average interruption Frequency Index and System Average Interruption Duration Index are solved using the Grey Wolf Optimization method for optimal placement of distributed generators in radial feeders for reliability enhancement. Distributed generation sources are becoming more prominent in distribution systems due to the incremental demands for electrical energy and sometimes provide the lowest cost solution to handling low-voltage or overload problems. Siting and sizing of Distributed generation sources have profoundly impacted on the system losses in a distribution network. Assessment of customer power supply reliability is an important part of distribution system operation and planning. Distribution system reliability assessment is able to predict the interruption profile of a distribution system based on system topology and component reliability data. Distributed generation is being adopted in distribution networks with one of the objectives being enhancement of system reliability. Grey Wolf Optimization technique is proposed to obtain the optimal location DG to improve the reliability. The effectiveness of the proposed objective functions has been investigated on standard test distribution systems (69 bus radial distribution systems).

Behaviour analysis of an operational planning tool facing activation probabilities, for near optimal operation of smart grids

The dispatch down of renewable generation and the combination of user controllable devices and network operation of grid components are flexibilities which are available in the distribution networks. Despite their added value for the system, their optimal control might bring more uncertainty in the operation of the network. The authors evaluate the behaviour performance of an operational planning tool that coordinates the flexibility activation planning, by introducing an activation probability for every flexibilities. An IEEE distribution network with distributed generation sources was used as base scenario for evaluation. A correlation between the probability of activation for load and generation flexibilities and the global result provided by the operation planning tool was observed. With the results gathered, the uncertainty's impact was analysed and some applications of the methods for futures works are proposed.

Constraint models of voltage fluctuation limit on OLTC/SVR caused by DG power fluctuation and generator disconnection to assess their impacts on DG penetration limit

With the rapid growth of distributed generation (DG) in distribution systems, DG penetration limit is becoming a more emergent issue. The short-term voltage fluctuation resulting from the DG power fluctuation of intermittent DG sources, e.g. photovoltaic (PV) and wind power, could trigger excessive actions of a transformer with on-load tap changer (OLTC) or a feeder step-voltage regulator (SVR). In addition, DG tripping from feeder will cause sudden large voltage step change. These facts limit the maximum allowable penetration of DG in distribution networks. This study proposes the constraint models of voltage fluctuation limit on OLTC/SVR resulting from DG power fluctuation and generator disconnection to assess their impacts on the DG penetration limit. A simple optimal power flow methodology is built according to the practical criteria and applied to the practical feeder systems, to demonstrate the huge advantages of the proposed constraint models in the assessment of DG penetration limit, which also validates that both factors have significant impacts on DG hosting capacity.

Challenges, advances and future directions in protection of hybrid AC/DC microgrids

Hybrid microgrids which consist of AC and DC subgrids interconnected by power electronic interfaces have attracted much attention in recent years. They not only can integrate the main benefits of both AC and DC configurations, but also can reduce the number of converters in connection of distributed generation sources, energy storage systems and loads to AC or DC buses. In this study, the structure of hybrid microgrids is discussed, and then a broad overview of the available protection devices and approaches for AC and DC subgrids is presented. After description, analysis and classification of the existing schemes, some research directions including communication infrastructures, combined control and protection schemes, and promising devices for the realisation of future hybrid AC/DC microgrids are pointed out.

Adaptive critics based cooperative control scheme for islanded Microgrids

This paper introduces novel cooperative control scheme based on adaptive critics for islanded Microgrids in the presence of disturbances. The interactions between the distributed generation sources are governed by a communication graph. Synchronization ideas are used to couple the dynamics of the distributed generation sources. A utility function is selected to reflect the objectives of the optimization problem. An online adaptive learning technique based on particle filtering is developed to estimate the dynamics of the distributed generation sources. Once the separation principle is held, the control input of every generation source and the estimator can be designed independently. The online adaptive learning technique uses incomplete knowledge about the dynamics of the distributed generation sources. Means of adaptive critics are used to implement the solution in real-time.

An optimization procedure for Microgrid day-ahead operation in the presence of CHP facilities

Microgrids are more and more called to satisfy, through the management of distributed generation sources and the electricity network, the demand for energy by local users. The simultaneous production of electrical and thermal energy by means of Combined Heat and Power (CHP) systems represents one of the features of a Microgrid and can contribute to improve system reliability, efficiency and economic performance. In this paper, an optimization procedure for day-ahead scheduling of a CHP-based Microgrid is developed, aiming to minimize operation and emission costs of Microgrid components in the presence of electric and thermal loads and renewable forecasts. To this purpose, four different operating strategies for CHP are accounted in Microgrid framework. The proposed methodology is based on a non-linear optimization technique and it is applied to the determination of day ahead operation program, with 15-minutes time step, for realistic model of an experimental Microgrid.