Neural-Network-Based Terminal Sliding Mode Control for Frequency Stabilization of Renewable Power Systems

This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.

Stochastic processes in renewable power systems: From frequency domain to time domain

With the increasing penetration of renewable energy resources(RESs), the uncertainties of volatile renewable generations significantly affect the power system operation. Such uncertainties are usually modeled as stochastic variables obeying specific distributions by neglecting the temporal correlations. Conventional approaches to hedge the negative effects caused by such uncertainties are thus hard to pursue a trade-off between computation efficiency and optimality. As an alternative, the theory of stochastic process can naturally model temporal correlation in closed forms. Attracted by this feature, our research group has been conducting thorough researches in the past decade to introduce stochastic processes within renewable power systems. This paper summarizes our works from the perspective of both the frequency domain and the time domain, provides the tools for the analysis and control of power systems under a unified framework of stochastic processes, and discusses the underlying reasons that stochastic process-based approaches can perform better than conventional approaches on both computational efficiency and optimality. These work may shed a new light on the research of analysis, control and operation of renewable power systems.Finally, this paper outlooks the theoretic developments of stochastic processes in future’s renewable power systems.

A robust optimization model for demand response management with source-grid-load collaboration to consume wind-power

To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.

Communication Resources Allocation for Time Delay Reduction of Frequency Regulation Service in High Renewable Penetrated Power System

The high renewable penetrated power system has severe frequency regulation problems.Distributed resources can provide frequency regulation services but are limited by com-munication time delay.This paper proposes a communication resources allocation model to reduce communication time delay in frequency regulation service.Communication device resources and wireless spectrum resources are allocated to distributed resources when they participate in frequency regulation.We reveal impact of communication resources allocation on time delay reduction and frequency regulation performance.Besides,we study communication resources allocation solution in high renewable energy penetrated power systems.We provide a case study based on the HRP-38 system.Results show communication time delay decreases distributed resources'ability to provide frequency regulation service.On the other hand,allocating more communication resources to distributed resources'communica-tion services improves their frequency regulation performance.For power systems with renewable energy penetration above 70%,required communications resources are about five times as many as 30%renewable energy penetrated power systems to keep frequency performance the same.Index Terms-Communication resources allocation,commun-ication time delay,distributed resource,frequency regulation,high renewable energy penetrated power system.

Development Track of Renewable Power Technology in China

Introduction Within the context of deeper global energy shortage and increasingly more polluted environment,countries throughout the world have been actively developing renewable energy sources to replace the fossil fuel,

A Study on Renewable Power Pricing Mechanism and Price Incentive Policies in China

The basic framework of price policies for promoting renewable power de- velopment in China is introduced. The background, concept and implementation of price policies, focused on wind power, biomass power and solar power, are summarized in the article. The experiences and lessons of implementation of these price policies are analyzed. It is concluded that reasonable price policy is quite effective for promoting re- newable power development. According to the requirement of China's renewable power development, the suggestions for improving renewable power pricing mechanism and price incentive policies are proposed.

Renewable energy power generation projects started construction in Tibet

On March 19, the construction of a 10-MW photovoltaic power plant and a 1 000-kW new type geothermal power generation project were started by Guodian Longyuan Group in Yanbajing Town, Dangxiong County of Tibet.

An Assessment of Renewable Energy Options for Somalia Turkey Hospital

Somalia Mogadishu-Turkey Training and Research Hospital is only powered by diesel generator currently.In this paper,the energy demand of this hospital is supplied by determining the optimum hybrid power renewable generating system.Therefore,numerous hybrid renewable power generating systems including the components like diesel generator,wind turbine,photovoltaic(PV)and battery are considered in different configurations.Eventually,they are technically,environmentally and economically analyzed by using the well-known HOMER software.Furthermore,a sensitivity analysis is also performed considering variations in three important parameters,namely average wind speed,current diesel price and also solar radiation.According to the results,the optimal system is the standalone Wind/Diesel/Battery hybrid renewable energy system(HRES)with the configuration of 1,000 kW wind turbine,350 kW diesel generator,250 kW power converters and 750 batteries.Additionally,this system has the net present cost of$5,056,700 as well as the cost of energy as$0.191/kWh.Lastly,it is clearly occurred that the Wind/Diesel/Battery HRES is eco-friendlier than other HRESs.

Combined cold,heat and power(CCHP)systems and fuel cells for CCHP applications:a topological review

As the basis for the study,this manuscript was written at a time when the energy crisis is affecting most parts of the world and most es-pecially the prevailing and rampant electricity crisis in most developing countries.As a result,50 combined cooling,heating and power(CCHP)systems studies were reviewed,which included the internal combustion engine(ICE),Stirling engine,biomass,micro turbine,solar and biogas,photovoltaic(PV)and gas turbine,wind turbine,PV and micro-turbine,solid-oxide and phosphoric-acid fuel cells(FCs),ICE and thermoelectric generator,low-temperature(LT)polymer electrolyte membrane(PEM),inlet air throttling gas turbine,ground source heat pump(GSHP)micro gas turbine and PV,ICE and GSHP,ICE with dehumidification and refrigeration,5-kW PEM FC,thermoelectric cooler and LT-PEM FC,Stirling engine and molten carbonate FC,thermo-acoustic organic Rankine cycle,solar-thermal,geothermal,integrated energy systems,power-and heat-storage systems,energy-conversion systems,thermodynamic and thermo-economic optimization strategies,working fluids based on hydrogen,helium as well as ammonia,H_(2)O,CO_(2) etc.Of these reviewed CCHP systems,FC-based CCHP systems were of the greatest interest,particularly the PEM FC.Consequently,FCs were further investigated,whereby the seven popular types of FCs identified and classified were summarily compared with each other,from which the PEM FC was preferred due to its practical popularity.However,PEM FCs,like all FCs,are susceptible to the fuel-starvation phenomenon;therefore,six FC-assisted schemes were examined,from which the FC assisted with the supercapacitor and battery technique was the most widely applied.In sum,the significance of the study entails assorted CCHP systems,FCs,their highlights,their applications and their pros and cons in a single reference document that anyone can easily use to holistically understand the characteristics of the CCHP systems.The study concludes with our perspective,by which we formulate and propose an alternative innovative unique CCHP system model under research,which is based exclusively on green tech-nologies:FCs,lithium-ion battery,ultracapacitor,thermoelectricity and an energy-management system using MATLAB■.

Smart Python Agents for Microgrids

Microgrids are revolutionary power systems that interconnect a mix of renewable power generation, load, storage systems, and inverters in a small-scale grid network. Operating microgrids while maintaining a consistent grid voltage and frequency during the islanding and disruption of renewables has been a challenging research problem. In this paper, a preliminary microgrid agent implementation is presented using SPADE (Smart Python Agent Development Environment) as a powerful development framework that has been used extensively in many application domains. Agents autonomously managed and operated microgrid individual components. A multiagent microgrid system was modeled to seamlessly operate and optimize energy balance by coordinating the actions of agents. Agents were built to forecast energy demand and solar power and coordinate to balance generation with load while maintaining optimal power flow and adequate network voltage and frequency.

Regional power system transitions towards carbon neutrality:The case of North China

China has announced its goal of reaching carbon neutrality by 2060,which will have a profound impact on its energy and economic systems.During this process,the power sector will play a key role in helping the country on its road towards carbon neutrality.This study develops a multi-regional power dispatch and capacity expansion model to combine long-term capacity expansion with short-term power dispatch.The model is built to optimise the carbon-neutral transition pathway from the perspective of economics,focussing on power system stability and reliability under high penetrations of renewables.Using the case study of North China,the cost-effective methods for power system transitions under the targets of reaching peak emissions by 2030 and achieving carbon neutrality by 2060 are discussed under different scenarios.We find that the future power supply system will rely heavily on renewable energy which will account for more than 89%of power generation.Inner Mongolia will produce more than 84%of power in the North China region.The inter-regional power transmission capacity will be five times higher than its current level.Policy choices will lead to different transition pathways as the early-stage installation decisions will have a lock-in effect on the following carbon emission reduction strategies and determine the importance of technologies adopted in achieving carbon neutrality.Although the transition to a low-carbon economy will result in an increase in cost by 17–19%,it will bring huge climate benefits to the world.

Nanostructure in energy conversion

Nanostructured and nanosized materials are widely applied to tackle the pressing challenges associated with energy conversion. In this conceptual review, rather than highlighting separate examples, we aim to give a general overview about where and how nanostructure design can be beneficial in the three major research fields（photo）thermal chemical energy conversion, electrochemical energy conversion, and solar energy conversion. It will be shown that in many cases the design of catalytically active nanostructures is the main task and that especially for catalysts nanostructure and activity are inseparably linked to each other. Moreover, electrochemical and photochemical processes are complicated by the overlap of multiple processes that all need to be optimized, including in particular light absorption, charge migration,recombination and trapping events and surface processes. It will also be shown how the development of materials for new challenges can often be based on our knowledge on existing materials for related applications.

Physics Insight of the Inertia of Power Systems and Methods to Provide Inertial Response

The growth of renewable energy reduces the moment of inertia for the synchronous AC grid,so the authors put forward two basic questions:1)What is the physics insight that a synchronous AC grid needs for mechanical inertia?2)How to provide inertial response for the power grid dominated with renewable energy?Based on Einstein’s special relativity and the Lorentz transformation,these papers illustrates that the nature of the inertia of the AC grid comes from the relativity of the electromagnetic field and motion,and from the strong coupling between them.According to their nature,the inertial response of the synchronous generator is self-proven.By contrast,the converter for the grid-connection of renewable energies used various algorithms in order to provide virtual inertia.But because algorithms do not rebuild the coupling between electromagnetic fields and motion,it is doubtful whether they can provide inertia and inertial responses.Therefore,the authors propose that there is a need to build extra electromagnetic fields and motion coupling for grids with high penetration rates of renewable energy.Therefore,a new grid-connection technology via Motor-Generator Pair(MGP)is discussed.The electromagnetic-motion coupling of the MGP is analyzed,and the results of simulation and experimental studies are also reported.

Impact of the cold surge event in January 2021 on the power system of China

During 6-10 January 2021,a recorded strong cold surge took place in China,with over 800 observational stations reaching their historical extremes.Unlike previous studies that focused on the response of either the power load or generation separately,this study quantitatively revealed the impacts on the balance between the demand and supply sides of the grid.On the demand side,the sensitivity of power load was found to increase substantially higher in southern China(0.533 GW°C^(−1))than in the northern region(0.139 GW°C^(−1))due to the limited municipal heating system.On the supply side,the hourly wind power generation dropped from the highest of 110 GW on 6 January to the lowest of 54 GW on 9 January due to the reduction in wind speed.In addition,a reduction in solar power generation was observed during 8-10 January.Thus,the balance of the power system was influenced by this cold event.As an effective adaptation measure,results further showed that early warning by three weeks ahead can be obtained by an operational climate model.The sensitivity of China's power system to such cold surge events may increase remarkably due to the expected increase in the proportion of wind and solar power generation in future new-type power systems.Thus,close cooperation between climate scientists and power engineers is needed to build the resilience of the power system to the cold extremes.

A VAE-Bayesian deep learning scheme for solar power generation forecasting based on dimensionality reduction

The advancements in distributed generation(DG)technologies such as solar panels have led to a widespread integration of renewable power generation in modern power systems.However,the intermittent nature of renewable energy poses new challenges to the network operational planning with underlying uncertainties.This paper proposes a novel probabilistic scheme for renewable solar power generation forecasting by addressing data and model parameter uncertainties using Bayesian bidirectional long short-term memory(BiLSTM)neural networks,while handling the high dimensionality in weight parameters using variational auto-encoders(VAE).The forecasting performance of the proposed method is evaluated using various deterministic and probabilistic evaluation metrics such as root-mean square error(RMSE),Pinball loss,etc.Furthermore,reconstruction error and computational time are also monitored to evaluate the dimensionality reduction using the VAE component.When compared with benchmark methods,the proposed method leads to significant improvements in weight reduction,i.e.,from 76,4224 to 2,022 number of weight parameters,quantifying to 97.35%improvement in weight parameters reduction and 37.93%improvement in computational time for 6 months of solar power generation data.

Economic potentials of energy storage technologies in electricity markets with renewables

The increasing penetration of renewables in power systems urgently entails the utilization of energy storage technologies.As the development of energy storage technologies depends highly on the profitability in electricity markets,to evaluate the economic potentials for various types of energy storage technologies under the compre-hensive market environment is of great significance.To this end,this study aims at conducting a quantitative analysis on the economic potentials for typical energy storage technologies by establishing a joint clearing model for electric energy and ancillary service(AS)markets considering the operating features of energy storage systems(ESSs).Furthermore,a test system is adopted for numerical analysis that accurately represents for the real-world operation characteristics of power systems in China,with which the market prices,and operation schedules and profitability of ESSs are comparatively studied.The proposed methodology and results could provide benefi-cial references for the modifications on electricity markets and the development of ESSs towards the increasing penetration of renewables in power systems.

Control Strategy Optimization of Voltage Source Converter Connected to Various Types of AC Systems

Connecting the voltage source converters(VSCs) to various types of AC systems results in different operation characteristics and core problems associated with traditional control strategies. Therefore, it is necessary to optimize the control strategies of the VSCs according to the types of AC systems.For the VSCs connected to islanded renewable power plants, a voltage/frequency(V/f) droop control strategy is proposed to damp fluctuations of AC voltage and frequency in the island,which is vital for bipolar VSC control. In addition, a multibranch impedance equivalent method for renewable power plants is proposed, with which large-scale renewable power plants can be modeled accurately in the frequency domain to prevent wide-band oscillation. For the VSCs connected to strong AC systems, smart AC voltage and coordinated frequency transient control strategies are proposed, which can improve AC system transient stability. For the VSCs connected to weak AC systems, the relationship between the system stability and strength is analyzed, and then the control strategy of inner-loop control parameter optimization and outer-loop power limiting(if necessary) is proposed to improve the stability of the allied system. The proposed strategies are verified by both software simulation and field commissioning.

Analysis and control of wind-driven self-excited induction generators connected to the grid through power converters

The analysis of the wind-driven self-excited induction generators （SEIGs） connected to the grid through power converters has been developed in this paper. For this analysis, a method of representing the grid power as equivalent load resistance in the steady-state equivalent circuit of SEIG has been formulated. The technique of genetic algorithm （GA） has been adopted for making the analysis of the proposed system simple and straightfor- ward. The control of SEIG is attempted by connecting an uncontrolled diode bridge rectifier （DBR） and a line commutated inverter （LCI） between the generator term- inals and three-phase utility grid. A simple control technique for maximum power point tracking （MPPT） in wind energy conversion systems （WECS）, in which the firing angle of the LCI alone needs to be controlled by sensing the rotor speed of the generator has been proposed. The effectiveness of the proposed method of MPPT and method of analysis of this wind-driven SEIG-converter system connected to the grid through power converters has been demonstrated by experiments and simulation. These experimental and simulated results confirm the usefulness and successful working of the proposed system and its analysis.

Dispatchable Region for Active Distribution Networks Using Approximate Second-order Cone Relaxation

Uncertainty in distributed renewable generation threatens the security of power distribution systems.The concept of dispatchable region is developed to assess the ability of power systems to accommodate renewable generation at a given operating point.Although DC and linearized AC power flow equations are typically used to model dispatchable regions for transmission systems,these equations are rarely suitable for distribution networks.To achieve a suitable trade-off between accuracy and efficiency,this paper proposes a dispatchable region formulation for distribution networks using tight convex relaxation.Secondorder cone relaxation is adopted to reformulate AC power flow equations,which are then approximated by a polyhedron to improve tractability.Further,an efficient adaptive constraint generation algorithm is employed to construct the proposed dispatchable region.Case studies on distribution systems of various scales validate the computational efficiency and accuracy of the proposed method.