Farhad Shahnia

An autonomous microgrid (MG) may observe overloading and renewable-based excessive generation. Such issues can lead to unacceptable deviation in the MG's voltage or frequency. These problems can be eased by load-shedding or renewable curtailment. On the other hand, forming provisional neighboring MG clusters and facilitating power exchange among them can also improve the situation more economically and effectively. The power exchange link between the MGs can be in the various forms such as a three-phase ac, a single-phase ac or a dc link. This approach requires power electronics-based converters to interlink the three-phase ac microgrid with the power exchange link and control the power-sharing amongst them. This paper has studied such structures and has proposed a decentralized approach to control the converters of the neighboring MGs to enable power-sharing amongst them. The performance of the proposed control mechanisms is evaluated through simulation studies in PSIM ® .

Dear Authors, Invited Guests, and Delegates As the General Chair and Technical Committee Chair of the 2020 International Conference on Smart Grids and Energy Systems (SGES 2020), it gives us immense pleasure to welcome over 200 guests and delegates from Universities, Research Organizations, Industry, Government, and NGOs from over 30 countries around the world to the Conference. Also, a very warm welcome to the beautiful and sunny Perth in a virtual way. COVID-19 changed many of our current practices in 2020 including face-to-face conferences but we are thankful to all conference authors and delegates who supported our idea of arranging this conference on-line.

The ever-declining price of the photovoltaic (PV) modules and governmental supports have contributed to the continued increase of PV system installations and integration into the power systems. There is a growing need to upgrade and stabilize the power system with massive PV integration to address the corresponding technical challenges. At the same time, revising international standards and national grid code requirements to enable a more diverse and robust power system infrastructure is a must. Given this background, this paper presents a comparison of several current grid codes for integrating PV systems and explores future grid code amendments for maintaining power system secure operation.

With the development of technology and ever-increasing integration of renewable energy power generation, the growing problem of the uncertainty of power outputs from renewable energy sources (RESs) has further promoted the progress of the demand-side response (DR) technology. The large industrial customers have high power consumption and high degree of automation, bringing in a higher DR potential. This paper presents a DR strategy for large industrial customers considering the uncertainty in the power outputs from RESs. First, the DR model of large industrial customers has been established considering their characteristics. Then, to deal with the uncertainty of the RES outputs, the methods of scenario sampling and reduction are formed, through which the typical and representative scenarios of RES outputs will be obtained. Next, based on the day-ahead prediction of the power outputs from RESs and real-time electricity price, a day-ahead DR strategy has been established for such customers with an objective of minimizing the overall daily electricity cost. Finally, taking an industrial park with distributed wind power and photovoltaic units as a sample example, the feasibility and effectiveness of the proposed method are demonstrated. In addition, the impacts of different types of loads are evaluated on the DR potentials of customers.

For the life-cycle cost management of a power grid project, the maintenance is not only expensive, but also has many impacting factors. Therefore, studying the cost of maintenance stage is important to improve the cost management of power grid enterprises. Based on the life-cycle cost management, this paper analyzes the content and cost composition of various maintenance tasks of power grid engineering. Finally, through the introduction of single factor sensitivity analysis method, combined with specific examples, this paper analyzes in detail the impacts of various kinds of power grid maintenance tasks in life-cycle maintenance.

To evaluate the investment effectiveness of and provide decision-making support for a production and technical transformation project (PTTP) in a power system, the concept and methodology of perfect technical transformation (PTT) are presented in this work. The well-established analytic hierarchy process (AHP) is employed to disassemble the evaluation objectives of a PTTP while the weights and scores of indicators at each level can be determined. Then, the comprehensive evaluation result of a PTTP can be obtained by weighted calculation. A perfection percentage index is defined to judge the satisfaction degree of an implemented PTTP. Next, a deviation identification and improvement method is used to accurately locate the poorly implemented parts of the PTTP, and optimize the technical scheme of the PTTP. Finally, an actual PTTP is employed to demonstrate the presented PTT based approach for investment effectiveness evaluation of a PTTP.

It is essential to eliminate the uncertainties in the variability of the output power of the solar photovoltaics (PV) as much as possible to improve the penetration level of such systems in microgrids. Hence, employing PV forecasting tools can be very helpful in this aspect. This paper has used a battery energy storage system and short-term PV forecasting together to assess the potential of fuel-saving in diesel generator-PV-battery hybrid microgrids. An innovative framework has been proposed to address the problems of forecast error for short-time horizon, realizing the persistence of the forecast's performance variation for various sky and cloud conditions throughout the year. This approach helps to build a confidence level for utilizing the PV forecast method as short as 1-min ahead. The studies have shown that PV forecasting mechanism yields in promising results when innovative strategies comprising of the post-processing of forecast data is effectively utilized.

Load-shedding and curtailment of renewable sources are common mechanism to prevent temporary overloading and over-generation in autonomous microgrids (MGs). However, these problems can be addressed by interconnecting the neighbouring MGs to share power among them. In such a scheme, the interconnected MGs, termed as coupled microgrid (CMG), are controlled to supply their local loads, as well as the loads in the neighboring MGs through an interconnecting three-phase ac link with back-to-back power electronics-based converter. This paper has proposed a suitable control mechanism to realize power sharing amongst the MGs within a CMG, when operating in different conditions. The efficacy of the proposed power sharing and control mechanisms are validated through simulation studies using PSIM ® .

This paper is built on practical power quality measurements of several relatively large rooftop photovoltaic systems (PVs) across the state of Western Australia. The considered PVs are three-phase 30 - 200 kWp systems, installed on the roof of industrial and commercial customers. This study has aimed to provide a statistical analysis of some of these power quality parameters, highlighting the impact of switching on the PV systems. Also, the study reports the percentage of the sites in which the desired limits set by the local utility have not been met in the case of these parameters.

Large remote areas may consist of multiple microgrids (MG), each owned and operated by a different owner (operator) in standalone mode. However, they can be coupled provisionally to support each other during overloading or excessive generation by renewables. This paper proposes a technique to maintain the voltage and frequency (VF) of each MG within the desired range in such situations. To this end, a multilevel optimization approach is utilized that determines the most suitable actions to recover the troubled MG. At first, the proposed technique utilizes the local resources of an MG, such as adjusting the generation levels of the dispatchable sources, charging or discharging of existing battery energy storages, and determining the best configuration for the microgrid's network. It then proceeds to determine the required support from neighboring healthy MGs if the local supports are not adequate. In that case, the proposed technique optimally selects the MGs (and level of support) to be coupled to support the troubled MG(s). In this regard, it considers the trading cost, reliability, emission and VF of the prospective coupled MG's network while forming an MG cluster. The performance of the developed technique is evaluated through numerical analyses in MATLAB.