Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning

This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the availability of solar/wind/bioenergy resources. In order to overcome the effects of intermittency in renewable resources and low inertia, each microgrid is incorporated with DRS and VIS units for demand- and supply-side management, respectively. The proposed system is simulated in MATLAB considering real-time recorded solar/wind data with realistic loading for 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm is proposed by hybridizing quasi-opposition-based learning and chaotic linear search techniques into the selfish-herd optimization, for optimal regulation of voltage and frequency in microgrids. Then, the system responses are compared with 7 algorithms and 5 error functions to tune PID controllers’ gains, which confirmed the superiority of QCSHO over others. Then, the study proceeds to investigate the voltage, frequency, and tie-line power coordination in 5 extreme scenarios of source and load variations in the proposed system without retuning the controllers. Finally, the system responses are analyzed for 10 different possible allocation of VIS and DRS units in different microgrids to find the most suitable combinations, and the results are recorded.

MITIGATING CO EMISSIONS FROM THE POWER SECTOR: LEAST-COST ANALYSIS OF POLICY OPTIONS IN THAILAND

Traditionally, the method used in the electricity generation expansion planning has concentrated only on the supply-side options to identify the sequence of generation additions meet the forecasted demand at a minimum cost. Electricity generation expansion planning with both supply- and demand-side options, commonly known as integrated resource planning are also being used in some developed countries. With growing environmental concerns, especially the emission of air-pollutants from the power generation, demand-side management and clean and efficient generation technology options in the power sector development are getting increasing attention. In this paper, we compare the traditional planning approach with integrated resource planning. We also analyze the implications of CO2 reduction targets for the power sector development in the framework of supply side planning by including clean supply-side technologies as candidate plants. During the planning horizon, generation capacity of 365 MW and a cumulative electricity generation or 61,681 GWh would be avoided through the use of efficient demand-side technologies compared to the business-as-usual (BAU) case. When the clean supply-side options considered in the least-cost planning process, three units of 100-MW biomass-based plants are selected. The long run average cost of generation is found to increase by 0.32, 0.65 and 1.61% at the level of CO2 emission reduction target of 5, 10, and 20%, respectively.