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.

Optimization dispatching strategy for an energy storage system considering its unused capacity sharing

In renewable energy systems,energy storage systems can reduce the power fluctuation of renewable energy sources and compensate for the prediction deviation.However,if the renewable energy prediction deviation is small,the energy storage system may work in an underutilized state.To efficiently utilize a renewable-energy-sided energy storage system(RES),this study proposed an optimization dispatching strategy for an energy storage system considering its unused capacity sharing.First,this study proposed an unused capacity-sharing strategy for the RES to fully utilize the storage’s unused capacity and elevate the storage’s service efficiency.Second,RES was divided into“deviation-compensating energy storage(DES)”and“sharing energy storage(SES)”to clarify the function of RES in the operation process.Third,this study established an optimized dispatching model to achieve the lowest system operating cost wherein the unused capacity-sharing strategy could be integrated.Finally,a case study was investigated,and the results indicated that the proposed model and algorithm effectively improved the utilization of renewable-energy-side energy storage systems,thereby reducing the total operation cost and pressure on peak shaving.

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.

Operating Analysis and Data Mining System for Power Grid Dispatching

The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.

Optimal Dispatch in Power Systems with Intermittent Power Sources

With the increasing integration of intermittent power sources (IPSs) into the power system, the uncertainty of IPSs requires solution and current dispatch system needs improvement. This paper aims to generate the optimal dispatch plan for day-ahead scheduling and real-time dispatch using the proposed model of characteristic optimal power flow (COPF). The integral time period represented by the median load point and the heavy and light load point with simplicity and accuracy. Simulation case studies on a 30-bus system are presented, which shows that COPF is an effective model to generate the optimal dispatch plan for power systems with high penetration of IPSs.

Synergetic Dispatch of Power System with Integration of Large-Scale Renewable Energy

This paper comes up with a concept of synergetic advanced dispatch in order to deal with the ever-increasing uncertainty in power grid: Decision is made with respecting to AGC units and active load on the basis of synergetic unit combination such that active load’s advantages in regulation speed is put to full use in achieving efficient cooperation with renewable energy power. Meanwhile, factoring in allowable frequency variation range during decision-making may help to reduce AGC units’ regulation load and improve power grid's capacity of accommodating renewable energy power. Calculation example analysis suggested that the model and technique presented in this paper is capable of efficient coordination between active loads and renewable energy power, delivering friendly transition with day-ahead dispatch and AVC control.

A Multi-Agent Particle Swarm Optimization for Power System Economic Load Dispatch

A new versatile optimization, the particle swarm optimization based on multi-agent system (MAPSO) is presented. The economic load dispatch (ELD) problem of power system can be solved by the algorithm. By competing and cooperating with the randomly selected neighbors, and adjusting its global searching ability and local exploring ability, this algorithm achieves the goal of high convergence precision and speed. To verify the effectiveness of the proposed algorithm, this algorithm is tested by three different ELD cases, including 3, 13 and 40 units IEEE cases, and the experiment results are compared with those tested by other intelligent algorithms in the same cases. The compared results show that feasible solutions can be reached effectively, local optima can be avoided and faster solution can be applied with the proposed algorithm, the algorithm for ELD problem is versatile and efficient.

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.

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.

A DISPATCHER TRAINING SIMULATOR SYSTEM INTEGRATED WITH THE EXIST SCADA/EMS

To utilize exist SCADA(Supervisory Control and Data Acqui si tion)/EMS (Energy Management System) fully and economize capital, Henan Electric Power Dispatching and Communication Center in China established a set of Henan Dispatcher Training Simulator (HNDTS) base on its exist SCADA/EMS. In order to i ntegrated with exist SCADA/EMS, the integration method and technique are propose d. Graph data integration discussed with emphasis. After integration implemented , HNDTS can share all data with SCADA/EMS and dispatchers can be trained in same environment as real work situation, in the same time it can avoid amout of work of maintenance engineers. Both advantages and disadvantages of integration are analyzed. In the end of paper, the requirement for future DTS is put forward bas e on the experience of author.

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.

Present State and Development Planning ofEast China Power System

This paper presents the existing state anddevelopment planning of East China PowerSystem, which refers to load, power source,power network, system protection, dispatchautomation and system communication.

Rolling Generation Dispatch Based on Ultra-short-term Wind Power Forecast

The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.

Revisit power system dispatch:Concepts,models,and solutions

Power system dispatch is a general concept with a wide range of applications.It is a special category of optimization problems that determine the operation pattern of the power system,resulting in a huge influence on the power system security,efficiency,and economics.In this paper,the power system dispatch problem is revisited from the basis.This paper provides a categorization of the dispatch problem,especially with an emphasis on industrial applications.Then,this paper presents a detailed review of the dispatch models.The common formulations of the dispatch problem are provided.Finally,this paper discusses the solutions of the dispatch problem and lists the major challenges.

Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.