Performance Optimisation of Standalone and Grid Connected Microgrid Clusters

Remote areas usually supplied by isolated electricity systems known as microgrids which can operate in standalone and grid-connected mode. This research focus on reliable operation of microgrids with minimal fuel consumption and maximal renewables penetration, ensuring least voltage and frequency deviations. These problems can be solved by an optimisation-based technique. The objective function is formulated and solved with a Genetic Algorithm approach and performance of the proposal is evaluated by exhaustive numerical analyses in Matlab

Market model for clustered microgrids optimisation including distribution network operations

This paper proposes a market model for the purpose of optimisation of clustered but sparse microgrids (MGs). The MGs are connected with the market by distribution networks for the sake of energy balance and to overcome emergency situations. The developed market structure enables the integration of virtual power plants (VPPs) in energy requirement of MGs. The MGs, internal service providers (ISPs), VPPs and distribution network operator (DNO) are present as distinct entities with individual objective of minimum operational cost. Each MG is assumed to be present with a commitment to service its own loads prior to export. Thus an optimisation problem is formulated with the core objective of minimum cost of operation, reduced network loss and least DNO charges. The formulated problem is solved by using heuristic optimization technique of Genetic Algorithm. Case studies are carried out on a distribution system with multiple MGs, ISP and VPPs which illustrates the effectiveness of the proposed market optimisation strategy. The key objective of the proposed market model is to coordinate the operation of MGs with the requirements of the market with the help of the DNO, without decreasing the economic efficiency for the MGs nor the distribution network. © The Institution of Engineering and Technology 2019

Multi-level supervisory emergency control for operation of remote area microgrid clusters

Remote and regional areas are usually supplied by isolated and self-sufficient electricity systems, which are called as microgrids (MGs). To reduce the overall cost of electricity production, MGs rely on non-dispatchable renewable sources. Emergencies such as overloading or excessive generation by renewable sources can result in a substantial voltage or frequency deviation in MGs. This paper presents a supervisory controller for such emergencies. The key idea is to remedy the emergencies by optimal internal or external support. A multi-level controller with soft, intermedial and hard actions is proposed. The soft actions include the adjustment of the droop parameters of the sources and the controlling of the charge/discharge of energy storages. The intermedial action is exchanging power with neighboring MGs, which is highly probable in large remote areas. As the last remedying resort, curtailing loads or renewable sources are assumed as hard actions. The proposed controller employs an optimization technique consisting of certain objectives such as reducing power loss in the tie-lines amongst MGs and the dependency of an MG to other MGs, as well as enhancing the contribution of renewable sources in electricity generation. Minimization of the fuel consumption and emissions of conventional generators, along with frequency and voltage deviation, is the other desired objectives. The performance of the proposal is evaluated by several numerical analyses in MATLAB (R)

Power transaction management amongst coupled microgrids in remote areas

© 2017 IEEE. Large remote areas normally have isolated and self-sufficient electricity supply systems, often referred to as microgrids. These systems also rely on a mix of dispatchable and non-dispatcha- ble distributed energy resources to reduce the overall cost of electricity production. Emergencies such as shortfalls, overloading, and faults can cause problems in the operation of these remote area microgrids. This paper presents a power transaction management scheme amongst a few such microgrids when they are coupled provisionally during emergencies. By definition, power transaction is an instance of buying and selling of electricity amongst problem and healthy microgrids. The developed technique aims to define the suitable power generation from all dispatchable sources and regulate the power transaction amongst the coupled microgrids. To this end, an optimization problem is formulated that aims to define the above parameters while minimizing the costs and technical impacts. A mixed- integer linear programming technique is used to solve the formulated problem. The performance of the proposed management strategy is evaluated by numerical analysis in MATLAB

Impact of scaled fitness functions on a floating-point genetic algorithm to optimise the operation of standalone microgrids

Standalone hybrid remote area power systems, also known as microgrids (MGs), can provide reasonably priced electricity in geographically isolated and the edge of grid locations for their operators. To achieve the reliable operation of MGs, whilst consuming minimal fossil fuels and maximising the penetration of renewables, the voltage and frequency should be maintained within acceptable limits. This can be accomplished by solving an optimisation problem. Floating-point genetic algorithm (FP-GA) is a heuristic technique that has a proven track record of effectively identifying the optimal solutions. However, in addition to needing appropriate operators, the solver needs a fitness function to yield the most optimal control variables. In this study, a suitable fitness function is formulated, by including the operational, interruption and technical costs, which are then solved with an FP-GA, with different combinations of operators. The developed fitness function and the considered operators are tested for the non-linear optimisation problem of a 38-bus MG. Detailed discussions are provided on the impact, which different operators have upon the outcomes of the fitness function

Transient Stability Improvement of Large-Scale Photovoltaic Grid Using a Flywheel as a Synchronous Machine

The global climate protection policy aimed at achieving a zero greenhouse gas emissions target has led to the fast incorporation of large-scale photovoltaics into the power network. The conventional AC grid was not modeled to be incorporated with large-scale non-synchronous inverter-based energy resources (IBR). Incorporating inertia-free IBR into the grid leads to technical issues such as the degradation of system strength and inertia, therefore affecting the safety and reliability of the electrical power system. This research introduced a new solution to incorporate a flywheel in the rotor of a synchronous machine to improve the dynamic inertia control during a system disruption and to maintain the constancy of the system. The objective of this work is to enhance large-scale photovoltaic systems in such a way that they can avoid failures during a fault. A model of transient constancy with two synchronous generators and a LSPV is established in PowerWorld modeling software. A line-to-ground and three-phase fault are simulated in a system with up to 50% IBR penetration. The outcomes showed that the power network was able to ride through faults (RTFs) and that the stability of frequency and voltage are enhanced because of a flywheel that improved grid inertia and strength

Upgradation of Metering Infrastructure of Low Voltage Distributed Network in Nottingham Road, Kwa-Zulu Natal, South Africa

The management of electricity distribution faces numerous challenges, including energy losses arising from technical and non-technical issues such as electricity theft. Energy losses due to theft have a significant global impact, including in South Africa (SA). SA rural areas are suffering from poor voltage, and technical and non-technical losses due to old power system systems. Hence, this research project is a proposal for the upgradation of an old and technically weak network of Nottingham Road, Kwa-Zulu Natal in South Africa. To reduce non-technical losses, this research examines the influence and potential solutions of using smart meters. The paper focuses on modeling real low voltage (LV) distribution systems and the energy meters that measure various parameters of the smart meters. This research also examines the effect of illegal links on the network. However, implementing the smart metering technology for lesser power consumers in developing countries such as South Africa can be challenging because of the greater initial costs. Therefore, this paper investigates the possibility of various technology choices and their return on investment in both urban and rural regions

Integration of EVs through RES with Controlled Interfacing

Electric cars have a lot of promise in future energy markets as a manageable load. A popular vehicle-to-grid control interface, which enables the aggregation of the charging mechanism for energy management in the distribution grid, is one of the most significant road blocks to realize this opportunity. Understanding the ecology of electric transportation and integrating it in local communities to alleviate the energy shortage at peak hours is very complicated. In this research paper, recent standardization initiatives aimed at overcoming obstacles such as the integration of electric cars into smart grids are discussed. A charge control scheme focused on vehicle-to-grid connectivity is implemented. It is observed that the rise of environmentally sustainable energy sources, such as photovoltaic (PV) and wind energy, is straining the power network and their infrequent power generation is causing problems in power system operation, regulation and planning. The introduction of electric vehicles (EVs) into the electricity grid has been proposed to overcome grid load variations. Finally, the article discusses the incorporation of renewable energy sources and latest potential solutions involving electric vehicles

Power quality improvement of a distribution system integrating a large scale solar farm using hybrid modular multilevel converter with ZSV control

Photovoltaic system is a major source of power generation. Its production is affected by the varying shading conditions that occur due to changing weather and other environmental factors. The modular multilevel converter (MMLC) is a promising selection to achieve high power. However, to achieve more levels of voltages the conventional MMLC requires more cells which eventually increases the complexity and losses. In this paper, the hybrid MMLC is proposed which have fewer IGBT switches for the same number of output level which eventually decreases the losses and improves the voltage output. The production of power is enhanced due to the series and parallel connection of half and full bridge cells in the converter configuration. The power quality issues such as voltage, current, and power are also satisfactorily handled by the converter without using any active or passive filters. However, due to the variation of input irradiation and temperature the output parameters such as Voltage, current and power show disturbance. Mitigation of these unbalances for a grid connected converter is important to stabilize the control and the quality of power injected into the grid. Therefore, zero sequence control (ZSC) is proposed for producing the balanced power during unstable input parameters. For ensuring the balanced power among the phases of the Converter to be fed to the grid zero sequence voltage (ZSV) is injected in each phase of the converter output validating the power balancing among the phases fed to the low voltage grid. Simulation results are presented to assess the output parameters before and after the injection of ZSV in the low voltage (LV) grid connected Hybrid MMLC of a large scale PV system and demonstrate the improved performance. This investigation is verified by simulation results with PSCAD software