Hirohisa Aki

Solar photovoltaic generation and energy storage are being used to power rural places. However, remote users are burdened by private energy storage devices. Remoteness limits the economic viability of cooperative energy storage. Our work proposes a shared energy storage model considering battery degradation. To test the model, we compared Individual, Neighbor, and Communal scenarios. The system was built as a mixed integer linear programming model to investigate optimal operating methods. Compared to the other situations, the Neighbor scenario saves operational expenses by 4.97%. Finally, the self-consumption rate shows optimal penetration of renewable energy parameters.

The development of renewable energy systems and battery electric vehicles (BEVs) is essential for achieving carbon neutrality. However, the large-scale introduction of photovoltaics (PV), whose generation fluctuates, necessitates high grid flexibility. BEVs can provide flexibility by controlling the charge/discharge of batteries. This study focuses on the provision of grid flexibility by public fast-chargers. The aim of the study is to develop an optimal charging model, which considers user convenience, and estimate the provided grid flexibility by BEV fast-charging. The addition of an economic incentive to the charging rates encourages users to change their charging behavior. The charging model optimizes the charging period and amount of charge based on the charging rates. User convenience factors, such as the charging frequency and user psychology on charging, are considered. Simulations are performed using road traffic data, and the provided grid flexibility is evaluated. Three cases with different incentive rates and five groups with different user psychologies toward charging are examined. The simulation results indicate that BEV fast-charging can be used to provide grid flexibility. The fast-charging demand during the evenings and nights on weekdays, when electricity shortage is a concern, can be shifted to daytime on weekends when there is surplus electricity due to PV overgeneration.

The intermittency of renewable energy sources makes the use of energy storage systems (ESSs) indispensable in modern power grids for supply-demand balancing and reliability enhancement. Besides pumped-storage hydroelectric power stations, energy storage deployment worldwide is still quite low. However, the status quo might rapidly change as the energy storage technologies are growing and facilitating market regulations are being ratified. Battery energy storage systems (BESSs), Li-ion batteries in particular, possess attractive properties and are taking over other types of storage technologies. Thus, in this article, we review and evaluate the current state of the art in managing grid-connected Li-ion BESSs and their participation in electricity markets. The review mainly includes battery modeling, the architecture of battery management systems (BMSs), the incorporation of BESSs for electricity market services, global utility-scale battery storage facilities, and challenges in implementing and managing grid-connected BESSs.

This paper develops a practical framework for multi-objective optimal planning of a grid-connected renewable-battery system considering a long-period operation. The capacities of wind turbine, solar PV, and battery storage are optimized by minimizing three objective functions: cost of electricity (COE), grid dependency (GD), and total curtailed energy (TCE). A new rule-based energy management is developed for long-period operation where: (a) capacity degradations of PV and battery are applied, (b) purchase and sell back electricity prices are updated for each year using interest and escalation rates, and (c) salvation value of the components is considered to achieve a realistic economic analysis of the planning problem. The developed multi-objective optimal planning model is examined using long-period (10 years) real data of wind speed, solar insolation, ambient temperature, and load consumption for a grid-connected household in Australia. It is found that a household with the minimum GD (0.008%) results in a COE of 116 /kWh with a TCE of 100 MWh in 10 years. The proposed optimal planning framework based on the long-period operation is compared with the short-period operation.

This paper develops practical resiliency-oriented optimal planning models for a grid-connected system with renewable resources and battery energy storage. A long-term (10-year) operation is conducted by incorporating grid outages, operating reserve, detailed models of electricity prices, and components capacity degradations and costs. The number of grid outages per year as well as the days, starting time and duration of the outages are adopted using probability distribution functions. Interest and escalation rates are updated in each year of operation to update the retail price, feed-in-tariff, and penalty rate of the electricity provider for the unsupplied power during grid outages. A novel operation strategy is developed for islanded and grid-connected modes of operation. The renewable-battery system is optimized for two cases: 1) a resilient system without load interruption, and 2) a resiliency-constrained system with partial load interruption. A case study in South Australia is conducted by incorporating the load profile of an educational campus and the actual weather data for a project lifetime of 10 years. The resiliency-oriented optimal planning model is compared to the same system optimized by short-term data. It is found that the resiliency-constrained system achieves lower cost, battery capacity, and dumped energy with limited unsupplied energy compared to the resilient system which has zero unsupplied energy. The proposed long-term resilient system is found to need 2.2 MWh battery capacity to efficiently supply 17.58 MWh electricity during the grid outages. The cost of electricity for the proposed resilient system is 23.77 /kWh.

Optimal planning of a remote area electricity supply (RAES) system is a vital challenge to achieve a reliable, clean, and cost-effective system. Various components like diesel generators, renewable energy sources, and energy storage systems are used for RAES systems. Due to the different characteristics and economic features of each component, optimal planning of RAES systems is a challengeable task. This paper presents an overview of the optimal planning procedure for RAES systems by considering the important components, parameters, methods, and data. A timely review on the state of the art is presented and the applied objective functions, design constraints, system components, and optimization algorithms are specified for the existing studies. The existing challenges for RAES systems’ planning are recognized and discussed. Recent trends and developments on the planning problem are explained in detail. Eventually, this review paper gives recommendations for future research to explore the optimal planning of components in RAES systems.