Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage

Abstract

In association with the development of intermittent renewable energy generation (REG), dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day-ahead, optimal dispatch problem incorporating energy storage (ES) is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space-time domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO-TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO-TLBO method in solving the proposed dispatch problems.

A Competitive Swarm Optimizer‐Based Technoeconomic Optimization with Appliance Scheduling in Domestic PV‐Battery Hybrid Systems

“…(3) while G � 1 to Mg do (4) P(G + 1) � ∅; (5) while P(G) ≠ ∅ do (6) Generate two random indices r 1 and r 2 from np; (7) if…”

“…ere were an enormous number of studies on hybrid system optimization over the past twenty years. Advanced technologies have been applied to the economic power dispatch problem in hybrid energy systems [5][6][7]. Most of such studies focused on power ow control strategies where the demand side was rather considered constraints in the system.…”

A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch

“…e optimization of these two indicators is essentially contradictory. Economic and emission load dispatch (EED) is a multiobjective optimization problem that considers these two con icting indicators at the same time [2]. In addition, because the mathematical expressions of the two indexes are nonconvex and nonsmooth objective functions, it is di cult to solve the optimization problem.…”

“…In [10], an enhanced multiobjective bee colony optimization algorithm is proposed for solving short-term hydro-thermal-wind complementary scheduling considering the uncertainty of wind power. In [2], a dynamic economic emission dispatch (DEED) incorporating renewable energy and energy storage is formulated and an adaptive robust method is proposed to solve the problem.…”

Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection

“…In the evolutionary computation community, the studies of static multiobjective optimization problems (MOPs) have been widely conducted during the recent decades, and there are a number of effective and efficient evolutionary algorithms for tackling static MOPs. However, in some practical engineering applications, it is found that some optimization problems are very complicated and need to be solved in a dynamic or uncertain environment, as their objective functions may change with the environment, which often exist in planning and scheduling problems [1][2][3][4], parameter optimization [5,6], resource allocation [7,8], and control system [9][10][11]. is kind of MOPs is often called dynamic multiobjective optimization problems (DMOPs), which can be defined in different aspects according to the nature of dynamics [12][13][14].…”