Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review

Abstract

This review paper provides a critical interpretation and analysis of almost 150 dedicated optimization research papers in the field of droop-controlled islanded microgrids. The significance of optimal microgrid allocation and operation studies comes from their importance for further deployment of renewable energy, reliable and stable autonomous operation on a larger scale, and the electrification of rural and isolated communities. Additionally, a comprehensive overview of islanded microgrids in terms of structure, type, and hierarchical control strategy was presented. Furthermore, a larger emphasis was given to the main optimization problems faced by droop-controlled islanded microgrids such as allocation, scheduling and dispatch, reconfiguration, control, and energy management systems. The main outcome of this review in relation to optimization problem components is the classification of objective functions, constraints, and decision variables into 10, 9, and 6 distinctive categories, respectively, taking into consideration the multi-criteria decision problems as well as the optimization with uncertainty problems in the classification criterion. Additionally, the optimization techniques used were investigated and identified as classical and artificial intelligence algorithms with the latter gaining popularity in recent years. Lastly, some future trends for research were put forward and explained based on the critical analysis of the selected papers.

Dump Load Allocation in Islanded Microgrid with Robust Backward\Forward Sweep and MIDACO

“…Moreover, it is very difficult to calculate 𝜁𝜁 1 and 𝜁𝜁 2 analytically [17], while attempting trial of different values is unpractical since many optimization problems that rely on LF is il-conditioned and using static damping will ultimately lead to solution divergence. Due to their impeccable record of solving nonconvex and MINLP problems, metaheuristics have gained substantial interest and coverage in recent years [1]. Additionally, MIDACO is known for its high speed and precision when it comes to solving MINLP against other competitive swarm and evolutionary metaheuristics [4].…”

“…Stable and reliable microgrid (MG) operation is vital in facilitating distributed generation (DG) growth with increased reliance on renewable resources. Autonomous MG, often referred to as islanded MG (IMG), has become an area of interest [1]. Furthermore, due to its ease of implementation and reliability for IMG, droop control have gained considerable share of studies that focused on optimal operation of droop-controlled IMG (DCIMG) [1].…”

“…Autonomous MG, often referred to as islanded MG (IMG), has become an area of interest [1]. Furthermore, due to its ease of implementation and reliability for IMG, droop control have gained considerable share of studies that focused on optimal operation of droop-controlled IMG (DCIMG) [1]. Highly penetrated DCIMG has resulted in voltage and frequency (𝑉𝑉-𝑓𝑓) regulation issues, this was more evident during off-peak hours.…”

“…As in [4], stability improvement in highly penetrated MG was achieved by the optimal dump load (DL) allocation using combination of robust LF method called special BFS (SBFS) and the mixed-integer distributed ant colony optimization (MIDACO) algorithm. The use of stochastic optimization techniques to solve non-convex mixed-integer non-linear problems (MINLP) has gained significant interest in many years [1]. Ant colony optimization (ACO) is a wellestablished metaheuristic that is based on real ants foraging behaviour.…”

Adaptive frequency control in smart microgrid using controlled loads supported by real-time implementation

“…In this work, an islanded μ G that consists of 20MW (1pu) diesel generator, 17MW (0.85pu) load, 6 MW (0.3pu) PVs, 2.38MW (0.12pu) EVs and 1.62MW (0.08pu) HPs has been suggested [ 19 , 20 ]. The block diagram of LFC for the non-reheated turbine μ G without a controller is shown in Fig 1 .…”