• Energy Research

The cascaded H-bridge structure has raised more and more attention in the field of photovoltaic (PV) power generation. This paper presents an improved ω-ϕ droop control method for the islanded cascaded photovoltaic-energy storage (PVES) system. The PV units mainly focus on outputting active power with unity power factor characteristic while the ES unit is responsible for the total output voltage regulation, frequency restoration, and power fluctuation suppression. With the proposed method, the string voltage can be regulated by the ES unit. Further, both the frequency synchronization with no steady state error and the cooperation between ES and PVs are realized automatically with only ES control requires PCC information. Therefore, the communication dependence is reduced which improves the system reliability. In addition, stability analysis and simulation results are provided to verify the effectiveness of the proposed controller.

Rural electrification, diesel generator replacement, and resilient electrification systems against natural disasters are among the main targets for Perusahaan Listrik Negara (PLN) in Indonesia to achieve a universally accessible, resilient, and environment-friendly electricity supply. Microgrids, therefore, become a popular and available way to achieve the aforementioned targets due to their flexibility and resiliency. This paper aims to provide a resilience-oriented planning strategy for community microgrids in Lombok Island, Indonesia. A mixed-integer linear program, implemented in the distributed energy resources customer adoption model (DER-CAM), is presented in this paper to find the optimal technology portfolio, placement, capacity, and optimal dispatch in a community microgrid. The multinode model is adopted for the planning, and hence, power flow constraints, N-1 contingency, and technology constraints are considered. The results show that the placement of photovoltaic (PV) arrays, battery energy storage systems (BESSs), and diesel generators (DGs) as backup sources in multi-node community microgrids lead to multiple benefits, including 100% rural electrification, over 25% cost savings, as well as over 22%, in particular CO2 emission reduction in multinode community microgrids.

In a 100% clean energy town, to meet the energy balance and reduce the impact of power fluctuations on the main grid, in this paper, a hierarchical optimal energy management strategy (EMS) for a hybrid energy storage system (HESS) is proposed. The EMS consists of three layers. To meet the requirement of 100% clean energy, in the upper layer, a HESS economic operation model based on the mixed integer non-linear programming (MINLP) is presented. Then, considering the uncertainty of renewable energy and load, a power prediction model is presented in the middle layer. In addition, to reduce the power disturbance on the main grid caused by the stochastic power, a stochastic model predictive control (SMPC) strategy is implemented to optimize the power allocation of a HESS. In the lower layer, to reduce the power fluctuations of the lithium-ion battery (LiB) when mitigating minute-scale power fluctuations, a HESS optimal power allocation strategy based on Pontryagin's minimum principle (PMP) is proposed. In every control period, each layer is optimized based on the results of the previous layer. Finally, a simulation study is provided to validate the effectiveness of the proposed EMS. The results show that the proposed strategy has good performance in typical scenarios.

The environmental concerns and reduction in fossil fuels have become a major concern due to which a large number of electric and hybrid vehicles are being built to minimize the contribution of greenhouse gas emissions from the transportation sector and to increase the efficiency of the overall vehicles. Electric vehicles (EVs) play an important role in today’s development of smarter cities and hence, there is a rapid growth of EVs all around the globe. Although they are found to be environmentally friendly and energy-efficient in comparison with internal combustion engine vehicles but lack of availability of a large number of charging stations at present time limits the use of EVs in the wider perspective. The broader use of EVs would require a huge amount of power from the existing power grids that may hit the prevailing distribution system. Further, charging such EVs equipped with huge battery packs, high power charging stations are essential to charge them at a speed comparable to the conventional oil/gas refueling system. The EVs considered in this study restricts to electric ships and electric cars being two major contributors towards greenhouse gas emissions. In order to address the aforementioned concerns, this study, therefore, presents state-of-the-art based on conventional and current technologies relating to EVs and their charging infrastructure. Further, possible configurations based on the integration of renewable energy sources and stationary energy storage systems are presented to aid the existing power grids. Lastly, challenges along with possible solutions and the future perspective are part of this study.

The application of hydrogen (H2) energy in Microgrids (MGs) is suppressed by the limited energy conversion efficiency between H2 and electricity, even though the energy density of H2 outperforms the electricity storage. This paper proposed a multi-objective energy management system (EMS) to economically operate a hybrid H2-electricity system under the flexible electricity market, considering the energy loss in not only power-to-gas (P2G) and gas-to-power (G2P) conversion but also the energy consumption of H2 pressurization. Particle swarm optimization (PSO) is deployed to perform a day-ahead schedule for the electricity storage system and H2 storage system separately. The global optimal operation is achieved by the proposed method to allocate renewable energy and shift the cheap electricity. The performance of the proposed EMS is verified through numerical experiments based on real-world data. The influence of prediction methods on the proposed MOEMS is further tested and analyzed to improve the reproducibility of the approach. The results indicate that the proposed MOEMS could effectively schedule the operation of the hybrid storage system.

Island nations frequently experience energy poverty, particularly the lower-income ones, especially Indonesia. Approximately 65-75% of families in the Pacific Island nations lack access to electricity from the national grid, and most produce electricity from fossil fuels like diesel generators. The price of imported fossil fuel varies with the international market, and the price of electricity produced from imported fuel is very high. It is anticipated that this problem will be mitigated by practical and affordable microgrid (MG) solutions, which are developing quickly in the field of renewable energy resources (RES). This study explores, develops, and assesses viable microgrid solutions for isolated islands, using Indonesia as an example. In this paper, we discuss and assess six possible microgrid options explored, and the two that are determined to be the most practical, affordable, and environmentally friendly for distant island microgrids by using Homer Pro Software. The first system is photovoltaic cells (PV), a battery energy storage system (BESS), and a diesel generator (DG), and the second is photovoltaic cells and a battery energy storage system.

The fluctuated power output of renewable energy sources brings new challenges to frequency control, especially for islanded microgrids with small spinning reserves. However, energy storage systems and widespread flexible loads can be employed to the frequency regulation thanks to their flexibility of power outputs. This paper investigates the frequency regulation problem for islanded microgrids with distributed heterogeneous energy storage systems (HESS) composed of battery energy storage systems (BESS) and building thermal energy storage systems (BTESS). A distributed event-triggered balanced power sharing strategy considering denial of service (DoS) attacks is designed for frequency regulation by allocating HESS power according to BESS state of charge (SoC), BTESS state of temperature (SoT) and their capacities. The range of control parameters for a stable controller are all provided by Lyapunov analysis. Moreover, the frequency feedback control gain for HESS is derived by using linear quadratic regulator. Simulation results show that the proposed frequency regulation strategy can guarantee the recovery of microgrids frequency and the proportional sharing of HESS power. Besides, SoC and SoT balancing with fewer communications are achieved, even with considering various parameters of HESS, such as capacity, efficiency and with communication link failures as well as DoS attacks.

This paper presents a novel hierarchical Internet of Things (IoT)-based scheme for Microgrid-Enabled Intelligent Buildings to achieve energy digitalization and automation with a renewable energy self-consumption strategy. Firstly, a hierarchical structure of Microgrid-Enabled Intelligent Buildings is designed to establish a two-dimensional fusion layered architecture for the microgrid to interact with the composite loads of buildings. The building blocks and functions of each layer are defined specifically. Secondly, to achieve transparent information fusion and interactive cooperation between the supply-side and demand-side, a state transition mechanism driven by a combination of time and events is proposed to activate the real-time and mutual response of generation and loads dynamically. Thirdly, based on the above hierarchical fusion structure and data-driven state transition mechanism, a power balance control algorithm driven by a self-consumption strategy is further proposed to achieve the autonomous balance of supply and demand. Finally, the IoT Microgrid Laboratory at Aalborg University is introduced to show how to implement this novel hierarchical IoT-based scheme in a Microgrid-Enabled Intelligent Building, and the power consensus control method based on the state transition mechanism is verified to achieve a renewable energy self-consumption strategy.