Economic Dispatch Of Microgrid Research Articles

An Improved ABC Algorithm for Energy Management of Microgrid

Microgrids are an ideal way of electricity generation, distribution, and regulation for customers by means of distributed energy resources on the community level. However, due to the randomness of photovoltaic and wind power generation, it is a crucial and difficult problem to achieve optimal economic dispatch in microgrids. In this paper, we present an optimal economic dispatch solution for a microgrid by the improved artificial bee colony (ABC) optimization, with the aim of satisfying load and balance demand while minimizing the cost of power generation and gas emission. Firstly, we construct a mathematical model according to different characteristics of distributed generation units and loads, and improve the performance of global convergence for ABC in order to fit such model. Secondly, we explore how to solve the optimal economic dispatch problem by the improved ABC and give the essential steps. Thirdly, we carry out several simulations and the results illustrate the benefits and effectiveness of the proposed approach for optimal economic dispatch in microgrid.

Dynamic Economic Optimal Dispatch of Microgrid Based on Improved Differential Evolution Algorithm

Aiming at the static economical dispatch for microgrid ignoring the inherent link between the lack of each time interval, considering wind turbines, photovoltaic cells and sodium sulfur battery uncertainty factors on economic dispatch, taking the minimum micro power output and micro grid operation cost as objective function, the establishment of a micro grid dynamic economic dispatch model. Using VC + +, the dynamic economic dispatch program of microgrid is developed by using improved differential evolution algorithm. By changing the dynamic crossover factor, the convergence speed of the algorithm and the ability to avoid falling into local optimum are improved. According to the characteristics of microgrid example structure, the output principle and operation control strategy of microgrid are formulated according to the operation of microgrid isolated grid / grid connected operation. The results show that the economic dispatch of microgrid using dynamic optimization theory is more advantageous than static scheduling in cost saving, and it makes the charge and discharge of sodium sulfur battery more global and practical.

Research on Environmental/Economic Dispatch for Microgrid Incorporating Reserve Cost

Based on the minimum principle of reserve cost, operating cost and environmental cost, an environmental/economic dispatch model is constructed in this paper. The improved particle swarm optimization algorithm with time-varying acceleration coefficient is used to solving the model. Through the example simulation, the results show that the built model can make the optimization of the microgrid more reasonable. It can effectively reduce the reserve cost, the operating cost and the environmental cost. This is a good exploration of the environmental/ economic dispatch for microgrids.

Distributed Economic Dispatch in Microgrids Based on Cooperative Reinforcement Learning.

Microgrids incorporated with distributed generation (DG) units and energy storage (ES) devices are expected to play more and more important roles in the future power systems. Yet, achieving efficient distributed economic dispatch in microgrids is a challenging issue due to the randomness and nonlinear characteristics of DG units and loads. This paper proposes a cooperative reinforcement learning algorithm for distributed economic dispatch in microgrids. Utilizing the learning algorithm can avoid the difficulty of stochastic modeling and high computational complexity. In the cooperative reinforcement learning algorithm, the function approximation is leveraged to deal with the large and continuous state spaces. And a diffusion strategy is incorporated to coordinate the actions of DG units and ES devices. Based on the proposed algorithm, each node in microgrids only needs to communicate with its local neighbors, without relying on any centralized controllers. Algorithm convergence is analyzed, and simulations based on real-world meteorological and load data are conducted to validate the performance of the proposed algorithm.

A non-linear convex cost model for economic dispatch in microgrids

This paper proposes a convex non-linear cost saving model for optimal economic dispatch in a microgrid. The model incorporates energy storage degradation cost and intermittent renewable generation. Cell degradation cost being a non-linear model, its incorporation in an objective function alters the convexity of the optimization problem and stochastic algorithms are required for its solution. This paper builds on the scope for usage of macroscopically semi-empirical models for degradation cost in economic dispatch problems and proves that these cost models derived from the existing semi-empirical capacity fade equations for LiFePO4 cells are convex under some operating conditions. The proposed non-linear model was tested on two data sets of varying size which portray different trends of seasonality. The results show that the model reflects the trends of seasonality existing in the data sets and it minimizes the total fuel cost globally when compared to conventional systems of economic dispatch. The results thus indicate that the model achieves a more accurate estimate of fuel cost in the system and can be effectively utilized for cost analysis in power system applications.

Review on Multi-objective Joint Economic Dispatching of Microgrid in Power System

As the global energy crisis and environmental pollution problems are becoming more and more serious, the microgrid (MG), as an effective supplementary means of large power grid, has gradually become the focus of attention. With the gradual maturity of MG technology and deepen practice of engineering application, the economic dispatching of MG has become the key issue in the field of MGs. This paper analyzes the status quo of domestic and international researches on MG economic dispatch from multiple perspectives, such as dynamic and static economic dispatch, demand side response, energy management and multi-MGs joint dispatch. It points out that the economic dispatching of micro-grid still has some problems to be further studied. For instance, the imperfect of uncertainty researches on renewable energy (RE) and load demand (LD) and the immaturity of research on MG economic dispatch. Finally, a summary and prospect for economic dispatch research is concluded.

Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming

Energy Management System (EMS) applications of modern power networks like microgrids have to respond to a number of stringent challenges due to current energy revolution. Optimal resource dispatch tasks must be handled with specific regard to the addition of new resource types and the adoption of novel modeling considerations. In addition, due to the comprehensive changes concerning the multi cell grid structure, new policies should be fulfilled via microgrids’ EMS. At the same time achieving a variety of (conflicting) goals in different microgrids requires a universal and a multi criteria optimization tool. Few of recent works in this area have considered the different perspectives of network operation with high amount of constraints and decision criteria. In this paper two dispatch-optimizers for a centralized EMS (CEMS) as a universal tool are introduced. An improved real-coded genetic algorithm and an enhanced mixed integer linear programming (MILP) based method have been developed to schedule the unit commitment and economic dispatch of microgrid units. In the proposed methods, network restrictions like voltages and equipment loadings and unit constraints have been considered. The adopted genetic algorithm features a highly flexible set of sub-functions, intelligent convergence behavior, as well as diversified searching approaches and penalty methods for constraint violations. Moreover, a novel method has been introduced to deal with the limitations of the MILP algorithm for handling the non-linear network topology constraints. A new aging model of a Lithium-Ion battery based on an event-driven aging behavior has been introduced. Ultimately, the developed GA-based and MILP-based optimizers have been applied to a test microgrid model under different operation policies, and the functionality of each method has been evaluated and compared together.

Real-time microgrid economic dispatch based on model predictive control strategy

To deal with uncertainties of renewable energy, demand and price signals in real-time microgrid operation, this paper proposes a model predictive control strategy for microgrid economic dispatch, where hourly schedule is constantly optimized according to the current system state and latest forecast information. Moreover, implicit network topology of the microgrid and corresponding power flow constraints are considered, which leads to a mixed integer nonlinear optimal power flow problem. Given the non-convexity feature of the original problem, the technique of conic programming is applied to efficiently crack the nut. Simulation results from a reconstructed IEEE-33 bus system and comparisons with the routine day-ahead microgrid schedule sufficiently substantiate the effectiveness of the proposed MPC strategy and the conic programming method.

Economic dispatch for microgrids with constrained external power exchange

This paper examines microgrid unit dispatch, with hourly bounds on energy exchange with the macrogrid and minimum storage level constraints. These goals can be used to meet market constraints and to ensure there is sufficient energy reserved for future periods, respectively. In particular, economic model predictive control is used to minimize cost while ensuring these scheduling goals and other operational constraints are satisfied. Simulation of a dynamic microgrid system over a 24-hour period shows that the proposed dispatch strategy is able to effectively reject forecasting errors and meet the established energy exchange and storage level goals.

Improved Interval Optimization Method Based on Differential Evolution for Microgrid Economic Dispatch

This article proposes an improved interval optimization method based on differential evolution for dynamic economic dispatch of a microgrid. First, the dynamic economic dispatch model applied is a microgrid model considering various distributed generations, energy storage systems, the transaction between the microgrid and power grid, as well as multiple kinds of loads. Both economic and environmental costs are taken into account. Second, an improved interval optimization method based on differential evolution is proposed to solve this non-linear optimization model. The proposed method is improved in the aspects of the branch-and-bound strategy, acceleration tool, and interval estimation method. Finally, a practical dynamic economic dispatch case of a microgrid considering the valve-point effect is studied. A comparison among the proposed method, traditional interval method, differential evolution method, and interior point method is given to verify the efficiency and practicality of the improved interval optimization method.

Two-Layer Optimize Algorithm for Microgrid Economic Dispatch

To deal with the super short-time energy management of microgrid, a mixed-integer programming optimization algorithm combined with genetic algorithm is proposed. Firstly, this paper introduced the short-time economic dispatch mathematical model of microgrid. Secondly, a two-layer optimize algorithm is been developed. The lower layer takes no account of power flow constrains, convert the model into a mixed-integer programming problem through linearization techniques. The lower layer gets the generation schedule, and then passes the data to the upper layer. The upper layer takes the power flow constrains into account, optimize the unit output based on genetic algorithm. The simulation result shows that the proposed algorithm achieves a better complementary of the two kinds of optimization algorithm. At the same time, the optimization result also shows the effectiveness of the algorithm.

Research for PV Cell and Storage Battery of Dynamic Economic Dispatch in Micro-Grid

The method of day-ahead dynamic economic dispatch is applied to the micro-grid composed of photovoltaic (PV) generation system and batteries to make its operational cost minimized. The battery life was converted cost and added to the objective function. Micro-grid’s mathematical model of economic dispatch was set up. Mathematical model of economic dispatch was solved by using the method of real population genetic algorithm. The charge and discharge plan of battery in micro-grid and buying or selling electricity plan between micro-grid and State Grid was established at the same time. Taking real data of Shanghai Electric Group’s micro-grid for case study, the dynamic economic dispatch is compared with traditional dispatch strategy. The results verify the effectiveness of the dynamic economic.

Decentralized Economic Dispatch in Microgrids via Heterogeneous Wireless Networks

As essential building blocks of the future smart grid, microgrids can efficiently integrate various types of distributed generation (DG) units to supply the electric loads at the minimum cost based on the economic dispatch. In this paper, we introduce a decentralized economic dispatch approach such that the optimal decision on power generation is made by each DG unit locally without a central controller. The prerequisite power generation and load information for decision making is discovered by each DG unit via a multiagent coordination with guaranteed convergence. To avoid a slow convergence speed which potentially increases the generation cost because of the time-varying nature of DG output, we present a heterogeneous wireless network architecture for microgrids. Low-cost short-range wireless communication devices are used to establish an ad hoc network as a basic information exchange infrastructure, while auxiliary dual-mode devices with cellular communication capabilities are optionally activated to improve the convergence speed. Two multiagent coordination schemes are proposed for the single-stage and hierarchical operation modes, respectively. The optimal number of activated cellular communication devices is obtained based on the tradeoff between communication and generation costs. The performance of the proposed schemes is analyzed and evaluated based on real power generation and load data collected from the Waterloo Region in Canada. Numerical results indicate that our proposed schemes can better utilize the cellular communication links and achieve a desired tradeoff between the communication and generation costs as compared with the existing schemes.

Economic Dispatch of Microgrids

Economic Dispatch of Microgrids