Economic Power Dispatching from Distributed Generations: Review of Optimization Techniques

In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.

Wind farm active power dispatching algorithm based on Grey Incidence

This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching(WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of highspeed turbines is effectively reduced.

A pooled-neighbor swarm intelligence approach to optimal reactive power dispatch

This paper presents a pooled-neighbor swarm intelligence approach (PNSIA) to optimal reactive power dispatch and voltage control of power systems. The proposed approach uses more particles’ information to control the mutation operation. The proposed PNSIA algorithm is also extended to handle mixed variables, such as transformer taps and reactive power source in- stallation, using a simple scheme. PNSIA applied for optimal power system reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system in which the control of bus voltages, tap position of transformers and reactive power sources are involved to minimize the transmission loss of the power system. Simulation results showed that the proposed approach is superior to current methods for finding the optimal solution, in terms of both solution quality and algorithm robustness.

Evidence Mechanism of Power Dispatching Instruction Based on Blockchain

With the development and application of energy Internet technology,the collaborative interaction of“source network,load and storage”has becomethe development trend of power grid dispatching.The large-scale access of renewableenergy on the load side,the unified management of adjustable loads,and theparticipation of multiple parties in energy operations have put forward requirementsfor the safety,credibility,openness,and transparency of the load dispatchingenvironment.Under the environment of carbon emission reduction,the paperproposed an architecture of the scheduling data blockchain,based on the in-depthstudy of blockchain.Moreover,smart contracts are used to realize the applicationscenario of load dispatching instruction evidence on the blockchain.The contentand storage mode of scheduling instruction evidence on blockchain are studied.And different storage modes are adopted according to the actual needs.Andthe smart contract system realizes the evidence generation of power dispatchinginstruction.This is the basis for the normal circulation of power dispatchinginstruction evidence.The research significance of this paper is highlighted as follows.The data and information generated in the power dispatching process arestored as evidence.On the one hand,it can provide a basis for settlement betweenpower production and dispatching companies and power users.On the other hand,it can prepare for distributed transactions in the power grid under the environmentof carbon emission reduction.

Challenges and Improvements of Wind Power Dispatch in Northwest China

Besides common characteristics of wind power,there are some special characteristics in China power system,including large-scale,long distance transmission and lack of flexible regulating power sources.These special characteristics make power dispatch more challenging in China.Many studies have been carried out and some improvements are presented including wind power monitoring and control as well as evaluation of wind power integration capabilities.As a demonstration project,the technologies are integrated into the energy management system and are implemented in the Northwest China power system.They provide effective measures for wind power dispatch in the grid.

Large-Scale Distributed Photovoltaic Power Dispatching and Operation Management Review

Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper analyzes development status, technical requirement and dispatching and operation management situation of distributed PV in Germany and China. Then introduce the preparation of distributed PV dispatching and operation management criterion. Through summarizing the experiences and lessons of large-scale distributed PV development in Germany, it gives advice to the development of distributed PV dispatching and operation management in China.

Operation Indices for Smart Power Dispatch Center Design

With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.

Optimal reactive power dispatch of wind power plant cluster considering static voltage stability for low-carbon power system

The implementation of developing the wind power is an important way to achieve the low-carbon power system.However,the voltage stability issues caused by the random fluctuations of active power output and the irrational regulations of reactive power compensation equipment have become the prominent problems of the regions where large-scale wind power integrated.In view of these problems,this paper proposed an optimal reactive power dispatch(ORPD)strategy of wind power plants cluster(WPPC)considering static voltage stability for lowcarbon power system.The control model of the ORPD strategy was built according to the wind power prediction,the present operation information and the historical operation information.By utilizing the automatic voltage control capability of wind power plants and central substations,the ORPD strategy can achieve differentiated management between the discrete devices and the dynamic devices of the WPPC.Simulation results of an actual WPPC in North China show that the ORPD strategy can improve the voltage control performance of the pilot nodes and coordinate the operation between discrete devices and the dynamic devices,thus maintaining the static voltage stability as well.

Parallel Dispatch:A New Paradigm of Electrical Power System Dispatch

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs

Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based services.In recent years,researchers in the field of power systems have explored KGs to develop intelligent dispatching systems for increasingly large power grids.With multiple power grid dispatching knowledge graphs(PDKGs)constructed by different agencies,the knowledge fusion of different PDKGs is useful for providing more accurate decision supports.To achieve this,entity alignment that aims at connecting different KGs by identifying equivalent entities is a critical step.Existing entity alignment methods cannot integrate useful structural,attribute,and relational information while calculating entities’similarities and are prone to making many-to-one alignments,thus can hardly achieve the best performance.To address these issues,this paper proposes a collective entity alignment model that integrates three kinds of available information and makes collective counterpart assignments.This model proposes a novel knowledge graph attention network(KGAT)to learn the embeddings of entities and relations explicitly and calculates entities’similarities by adaptively incorporating the structural,attribute,and relational similarities.Then,we formulate the counterpart assignment task as an integer programming(IP)problem to obtain one-to-one alignments.We not only conduct experiments on a pair of PDKGs but also evaluate o ur model on three commonly used cross-lingual KGs.Experimental comparisons indicate that our model outperforms other methods and provides an effective tool for the knowledge fusion of PDKGs.

Distributionally Robust Optimal Reactive Power Dispatch with Wasserstein Distance in Active Distribution Network

The uncertainties from renewable energy sources(RESs)will not only introduce significant influences to active power dispatch,but also bring great challenges to the analysis of optimal reactive power dispatch(ORPD).To address the influence of high penetration of RES integrated into active distribution networks,a distributionally robust chance constraint(DRCC)-based ORPD model considering discrete reactive power compensators is proposed in this paper.The proposed ORPD model combines a second-order cone programming(SOCP)-based model at the nominal operation mode and a linear power flow(LPF)model to reflect the system response under certainties.Then,a distributionally robust optimization(WDRO)method with Wasserstein distance is utilized to solve the proposed DRCC-based ORPD model.The WDRO method is data-driven due to the reason that the ambiguity set is constructed by the available historical data without any assumption on the specific probability distribution of the uncertainties.And the more data is available,the smaller the ambiguity would be.Numerical results on IEEE 30-bus and 123-bus systems and comparisons with the other three-benchmark approaches demonstrate the accuracy and effectiveness of the proposed model and method.

Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and le´vy walk

This paper presents the mean–variance(MV)model to solve power system reactive power dispatch problems with wind power integrated.The MV model considers the profit and risk simultaneously under the uncertain wind power(speed)environment.To describe this uncertain environment,the Latin hypercube sampling with Cholesky decomposition simulation method is used to sample uncertain wind speeds.An improved optimization algorithm,group search optimizer with intraspecific competition and le´vy walk,is then used to optimize the MV model by introducing the risk tolerance parameter.The simulation is conducted based on the IEEE 30-bus power system,and the results demonstrate the effectiveness and validity of the proposed model and the optimization algorithm.

Multi-timescale Affinely Adjustable Robust Reactive Power Dispatch of Distribution Networks Integrated with High Penetration of PV

Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leading to unexpected power loss and voltage fluctuation.To address the uncertainties,this paper proposes a multi-timescale affinely adjustable robust reactive power dispatch(MTAAR-RPD)method to reduce the network power losses as well as alleviate voltage deviations and fluctuations.The MTAAR-RPD aims to coordinate on-load tap changers(OLTCs),capacitor banks(CBs),and PV inverters through a three-stage structure which covers multiple timescales of“hour-minute-second”.The first stage schedules CBs and OLTCs hourly while the second stage dispatches the base reactive power outputs of PV inverter every 15 min.The third stage affinely adjusts the inverter reactive power output based on an optimized Q-P droop controller in real time.The three stages are coordinately optimized by an affinely adjustable robust optimization method.A solution algorithm based on a cutting plane algorithm is developed to solve the optimization problem effectively.The proposed method is verified through theoretical analysis and numerical simulations.

Aggregated impact of allowance allocation and power dispatching on emission reduction

Climate change has become one of the most important issues for the sustainable development of social well-being.China has made great efforts in reducing CO2 emissions and promoting clean energy.Pilot Emission Trading Systems(ETSs)have been launched in two provinces and five cities in China,and a national level ETS will be implemented in the third quarter of 2017,with preparations for China’s national ETS now well under way.In the meantime,a new round of China’s electric power system reform has entered the implementation stage.Policy variables from both electricity and emission markets willimpose potential risks on the operation of generation companies(Gen Cos).Under this situation,by selecting key variables in each domain,this paper analyzes the combined effects of different allowance allocation methods and power dispatching models on power system emission.Key parameters are set based on a provincial power system in China,and the case studies are conducted based on dynamic simulation platform for macro-energy systems(DSMES)software developed by the authors.The selected power dispatching models include planned dispatch,energy saving power generation dispatch and economic dispatch.The selected initial allowance allocation methods in the emission market include the grandfathering method based on historical emissions and the benchmarking method based on actual output.Based on the simulation results and discussions,several policy implications are highlighted to help to design an effective emission market in China.

FUZZY SATISFYING INTERACTIVE MULTIOBJECTIVE THERMAL POWER DISPATCH： SWT APPROACH

In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution. In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz. cost, NOx emission, SOx emission and COx emission are minimized simultaneously. The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner. Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain. Exploiting fuzzy decision making theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off （SWT） functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker＇s preferences to non-inferior solutions through optimal weight patterns. The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses. Decoupled load flow analysis is performed to find the transmission losses. The validity of the proposed method is demonstrated on 11-bus, 17-lines IEEE system, comprising of three generators.

Hierarchical Cluster Coordination Control Strategy for Large-scale Wind Power Based on Model Predictive Control and Improved Multi-time-scale Active Power Dispatching

The grid-connection of large-scale and high-penetration wind power poses challenges to the friendly dispatching control of the power system.To coordinate the complicated optimal dispatching and rapid real-time control,this paper proposes a hierarchical cluster coordination control(HCCC)strategy based on model predictive control(MPC)technique.Considering the time-varying characteristics of wind power generation,the proposed HCCC strategy constructs an improved multitime-scale active power dispatching model,which consists of five parts:formulation of cluster dispatching plan,rolling modification of intra-cluster plan,optimization allocation of wind farm(WF),grouping coordinated control of wind turbine group(WTG),and real-time adjustment of single-machine power.The time resolutions are sequentially given as 1 hour,30 min,15 min,5 min,and 1 min.In addition,a combined predictive model based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),wavelet thresholding(WT),and least squares support vector machine(LSSVM)is established.The fast predictive feature of this model cooperates with the HCCC strategy that effectively improves the predictive control precision.Simulation results show that the proposed HCCC strategy enables rapid response to active power control(APC),and significantly improves dispatching control accuracy and wind power accommodation capabilities.