Guest editorial: Multi-energy microgrid: Modelling, operation, planning, and energy trading

A multi-energy microgrid (MMG) aims to integrate multiple energy carriers in the form of electricity, heating, and cooling, as well as gas in a microgrid architecture. To achieve higher energy generation and utilisation efficiency, MMGs can be implemented in distribution networks, smart buildings, smart homes, smart factories, and mobile microgrids such as ship power systems. In these systems, multiple energies can be simultaneously generated, transmitted, stored, and consumed through the seamless coordination of heterogeneous generation units, energy storage systems, and flexible loads. The key research challenges for MMG include accurate modelling of the multi-energy carrier units considering their diverse characteristics, optimally sizing and deploying the units in the MMG, flexibly dispatching and controlling them for MMG operation, and guiding effective trading on the generation and demand sides. This special issue has received wide attention from the research community, and five papers have been finally accepted which cover the topics of planning, operation, control, as well as the power quality and reliability of the MMG. A brief introduction of these five papers is given below.

In ‘Holistic Data-Driven Method for Optimal Sizing and Operation of an Urban Islanded Microgrid’, Feng and Tseng. presented a holistic data-driven method for the optimal sizing and operation of a building-level islanded microgrid with renewable energy resources in an urban setting. First, various meters were integrated on an energy-monitoring platform where field data were collected. A randomised learning-based forecasting model was designed for supply/demand prediction in a microgrid. Based on the forecasting results, data-driven uncertainty modelling was used to characterise the uncertainties associated with renewable energy supplies and demands. An optimal sizing approach was then proposed to determine the optimal sizes for energy storage systems and distributed generators with the overall aim of minimising the investment and maintenance costs. Based on the optimal sizing and uncertainty scenarios, a two-stage coordinated energy management method was proposed to minimise the operating cost under uncertainties.

In ‘Capacity Configuration Optimisation of Standalone Multi-energy Hub Considering Electricity, Heat and Hydrogen Uncertainty’, Liu et al. proposed a novel multi-objective capacity configuration model for standalone multi-energy hub considering electricity, heat and hydrogen energy uncertainty. First, a standalone multi-energy hub model with electricity, heat, and hydrogen energy was established. It considered photovoltaic generators, wind generation, combined heat and power units, power to gas, gas boiler, and hydrogen storage tank to meet electrical, thermal, and hydrogen energy demands. Meanwhile, to solve the influence of uncertainties on hub capacity configuration, typical source-load scenarios were established considering the uncertainty of wind speed, solar radiation, and energy demands. On this basis, the objective functions and constraints of the capacity configuration model are presented. An improved hybrid multi-objective particle swarm optimisation algorithm and fuzzy membership function were used to solve the model.

In ‘Control and Implementation of Multifunctional Microgrid with Seamless Synchronisation Capability’, Yadav et al. studied a microgrid with a solar photovoltaic (SPV) array, wind generator, battery energy storage (BES), and a bidirectional DC–DC converter with seamless transition capability from on-grid mode (OGM) to off-grid mode (FGM) and grid reconnected mode. This microgrid, based on renewable sources, increases the authenticity and sustainability of the supply and can feed the load in OGM and FGM, as well as during mode shifting. The undetermined disturbances and unpredictability of the microgrid in the OGM are managed by a sixth-order complex filter (6thOCF)-based control. With this control, the load current quadrature fundamental component (LCFC-Q) is obtained without a DC offset, even during voltage imbalances.

In ‘Power Quality Investigation of CHB Nine-Level Converter Based Large-Scale Solar PV System with Different Modulation Schemes’, Kulkarni et al. studied multilevel converters (MLCs) for solar photovoltaic (SPV) application. This study utilises different modulation techniques, such as phase-shifted (PS) multicarrier pulse-width modulation (PWM), selected harmonic elimination (SHE), and nearest level modulation (NLM) for switching of cascaded H-bridge (CHB) converter-based large-scale SPV systems. The investigation on the improvement of power quality is presented with a suitable fast Fourier transform (FFT) analysis and comparative graphs. The presented control and modulation enhance the power quality of the output current being fed to the grid in the dynamic solar profile. Moreover, the low switching frequency employed in this photovoltaic converter at a high power rating increases the system efficiency. Graphical illustrations of losses with fundamental and PWM switching were analysed for the MW-rated system.

In ‘Reliability Assessment of Island Multi-energy Microgrids’, Greenwood et al. studied the reliability problem of the island MMG because electricity and gas networks exhibit very different dynamic behaviours in response to a fault or failure, and gas networks have built-in energy storages that can continue providing a reliable supply if gas inputs to the system are compromised. This paper presents a novel reliability assessment method applied to MMGs, which combines an incidence matrix analysis that identifies the connectivity between source and load points with a sequential Monte Carlo simulation and generation adequacy evaluation. A case study was conducted using an electricity-gas microgrid. The electricity network is a multi-sourced grid, whereas the gas network is supplied by a biogas plant. The linepack (gas stored along the pipelines) was modelled to account for the slower gas dynamics. The proposed method was evaluated using a real-world electricity distribution network in Austria. The results indicate the reliability benefits of forming an MMG.