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.

Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

Aiming at the problems of large-scale wind and solar grid connection,how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations,a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed.Firstly,the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output,obtains the optimal output value under the economic conditions of each new energy station,and then obtains the maximum consumption space of the new energy station.Secondly,based on the optimization results of the first stage,the second stage dispatching model uses the dispatching method of fuzzy comprehensive ranking priority to prioritize the new energy stations,and then makes a fair allocation to the dispatching of the wind and solar stations.Finally,the analysis of a specific example shows that themodel can take into account the fairness of active power distribution of new energy stations on the basis of ensuring the economy of system operation,make full use of the consumption space,and realize the medium and long-term fairness distribution of dispatching plan.

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.

Method of Evaluating Social Benefit of Energy-Conservation Based Generation Dispatching in Guangdong Province

Energy-conservation based generation dispatching is the revolutionary change in operation mode which could reduce energy consumption and pollutant emissions, promote power industry restructuring, and achieve sustainable development. Social benefit evaluation of the energy-conservation based generation dispatching under the new situation and environment has come into being as an important theoretical issue. A new scenario analysis based social benefit evluating method, which is implemented by comparing the energy., consumption and pollutant emissions of different scenarios defined by the key indicators, i.e., load factor and coal consumption structure, is proposed in the paper. Then the composition of social benefit is analyzed from the point of the dispatching mode and the coal consumption structure. The method proposed is of clear physical meaning. It is not only practical, but also applicable for the implementation of energy-conservation based generation dispatching in diffferent phases and with different goals.

Short-term power generation scheduling rules for cascade hydropower stations based on hybrid algorithm

Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm （POA） in combination with the genetic algorithm （GA）. After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.

Simulation Analysis for Massive Deployment of Variable Renewables Employing an Optimal Power Generation Mix Model

This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of photovoltaic system and wind power generation in power system explicitly considering those short-term output variation. PV （photovoltaic） and wind output are estimated, employing meteorological database. Simulation results reveal that variable fluctuation derived from a high penetration level of those renewables is controlled by quick load following operation of natural gas combined cycle power plant, pumped-storage hydro power, stationary NAS （sodium and sulfur） battery and the output suppression control of PV and wind. It additionally turns out that the operational configuration of those technologies for the renewable variability differs significantly depending on those renewable output variations in each season and solving the seasonal electricity imbalance as well as the daily imbalance is important if variable renewables are massively deployed.

Grey Wolf Optimizer to Real Power Dispatch with Non-Linear Constraints

A new and efficient Grey Wolf Optimization(GWO)algorithm is implemented to solve real power economic dispatch(RPED)problems in this paper.The nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the constraints.Conventional methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible solutions.The behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting mechanism.The leadership hierarchy is simulated using four types of grey wolves.In addition,searching,encircling and attacking of prey are the social behaviors implemented in the hunting mechanism.The GWO algorithm has been applied to solve convex RPED problems considering the all possible constraints.The results obtained from GWO algorithm are compared with other state-ofthe-art algorithms available in the recent literatures.It is found that the GWO algorithm is able to provide better solution quality in terms of cost,convergence and robustness for the considered ELD problems.

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.

Influences of uncertainties to the generation feasible region for medium- and long-term electricity transaction

For the implementation of power market in China,medium-and Iong-term security checks are essential for bilateral transactions,of which the electricity quantity that constitutes the generation feasible region(GFR)is the target.However,uncertainties from load forecasting errors and transmission contingencies are threats to medium-and Iong-term electricity tradi ng in terms of their in flue nces on the GFR.In this paper,we prese nt a graphic distortio n pattern in a typical threegenerator system using the Monte Carlo method and projection theory based on security constrained economic dispatch.The underlying potential risk to GFR from uncertainties is clearly visualized,and their impact characteristics are discussed.A case study on detailed GFR distortion was included to dem on strate the effectiveness of this visualization model.The result implies that a small uncertainty could distort the GFR to a remarkable extent and that different line-contingency precipitates disparate the GFR distortion patterns,thereby eliciting great emphasis on load forecasting and line reliability in electricity transacti ons.

Multicriteria Methods for Distributed Generation Resources Optimization

The optimization process of embedded, or DG （distributed generation） is a very complex task, and it should be evaluated and compared by means of multi-criteria methods of analysis. The classical method for selection is usually based only on a single criterion analysis, and it is defined by thermal or economic aspects. The problem of optimal dispatch of DG is typical example of optimization, because it differs from the classical problem of generation dispatch in the power system, due to the specific criteria related to the DG interconnection. The most important goals are to maximize the renewable production and to minimize the total cost, while satisfying additional constraints related to the operation of a distribution network. As there are many DGs in a distribution network, it is very complicated to decide the optimal DG outputs to satisfy all the criteria and constraints imposed by the distribution network. Another problem is the lack of the dispatcher control over DGs, and very often, the only available action is to switch on or off the generator. Finally, network operator and DG owner perspective are often opposed regarding appropriate control action in the network. In this paper, a multicriteria decision support based on AHP （analytical hierarchical processes） method is proposed for the choice of the dispatching action. The method is illustrated on the choice of the DG to be switched off in the case or reverse power flow.

Study on a Comprehensive Energy-Saving Sail by CFD Method

A comprehensive energy-saving sail (CES) has been proposed in order to promote energy saving and emission reduction from shipping. Wind energy is harvested for propulsion and electrical generator at the same time by a unique structure of CES. A CFD (Computational Fluid Dynamics) code is verified by a case of arc wind sail, and it is used to simulate the pressure and velocity around the CES. The results show that the outlet velocity of air tunnel Vo and wind velocity Vi serve as an equation Vo ≈ 1.31Vi, which means the CES can effectively improve the conversion efficiency. In addition, it is found that Vo increases with the tunnel diameter to some extend over which it will keep almost constant.

Risk-averse Robust Interval Economic Dispatch for Power Systems with Large-scale Wind Power Integration

This paper presents a robust interval economic dispatch(RIED)model for power systems with large-scale wind power integration.Differing from existing interval optimization(IO)approaches that merely rely on the upper and lower boundaries of random variables,the distribution information retained in the historical data is introduced to the IO method in this paper.Based on the available probability distribution function(PDF),wind power curtailment and load shedding are quantified as the operational risk and incorporated into the decision-making process.In this model,we need not rely on the forecasted value of wind power,which is randomly fluctuating and quite unpredictable.Furthermore,when the PDFs of wind power are taken into account,the resulting dispatch solution makes a good tradeoff between the generation cost and the operational risk.Finally,the RIED model yields an optimal dispatch solution for thermal units and the allowable intervals of wind power for the wind farms,which efficiently mitigates the uncertainty in wind power generation and provides more practical suggestions for system operators.Simulation studies are conducted on a modified IEEE-118 bus system and the results verify the effectiveness of the proposed RIED model.

Real-time Dispatchable Region of Renewable Generation Constrained by Reactive Power and Voltage Profiles in AC Power Networks

A large amount of renewable energy generation(REG)has been integrated into power systems,challenging the operational security of power networks.In a real-time dispatch,system operators need to estimate the ability of the power network to accommodate REG with a limited reserve capacity.The real-time dispatchable region(RTDR)is defined as the largest range of a power injection that the power network can accommodate in a certain dispatch interval for a given dispatch base point.State-of-the-art research on the RTDR adopts a DC power flow model regardless of the voltage profiles and reactive power,which can overlook potentially insecure operational states of the system.To address this issue,this paper proposes an AC power flow based RTDR model simultaneously considering the reactive power and voltage profiles constraints.The nonlinear constraints in our model are approximated using a linear power flow model together with a polytope approximation technique for quadratic constraints.An adaptive constraint generation algorithm is used to calculate the RTDR.Simulation results using the IEEE 5-bus and 30-bus systems illustrate the advantages of the proposed model.

Research on Wind Farm Participation in Power Grid AGC Control

Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid planning and construction, and will make a heavy impact on the safe and reliable operation of power systems. To deal with the diff iculties of large scale wind power dispatch, this paper presents a new automatic generation control (AGC) scheme that involves the participation of wind farms. The scheme is based on ultra-short-term wind power forecast. The author establishes a generation output distribution optimization mode for the power system with wind farms and verif ies the feasibility of the scheme by an example.

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.

Tempospacial energy-saving effect-based diagnosis in large coal-fired power units:Energy-saving benchmark state

The energy-saving analytics of coal-fired power units in China is confronting new challenges especially with even more complicated system structure, higher working medium parameters, time-dependent varying operation conditions and boundaries such as load rate, coal quality, ambient temperature and humidity. Compared with the traditional optimization of specific operating parameters, the idea of the energy-consumption benchmark state was proposed. The equivalent specific fuel consumption(ESFC) analytics was introduced to determine the energy-consumption benchmark state, with the minimum ESFC under varying operation boundaries. Models for the energy-consumption benchmark state were established, and the endogenous additional specific consumption(ASFC) and exogenous ASFC were calculated. By comparing the benchmark state with the actual state, the energy-saving tempospacial effect can be quantified. As a case study, the energy consumption model of a 1000 MW ultra supercritical power unit was built. The results show that system energy consumption can be mainly reduced by improving the performance of turbine subsystem. This nearly doubles the resultant by improving the boiler system. The energy saving effect of each component increases with the decrease of load and has a greater influence under a lower load rate. The heat and mass transfer process takes priority in energy saving diagnosis of related components and processes. This makes great reference for the design and operation optimization of coal-fired power units.

Market-oriented Optimal Dispatching Strategy for a Wind Farm with a Multiple Stage Hybrid Energy Storage System

With the increased promotion of integrated energy power systems(IEPS),renewable energy and energy storage systems(ESS)play a more important role.However,the fluctuation and intermittent nature of wind not only results in substantial reliability and stability defects,but it also weakens the competitiveness of wind generation in the electric power market.Meanwhile,the way to further enhance the system reliability effectively improving market profits of wind farms is one of the most important aspects of Wind-ESS joint operational design.In this paper,a market-oriented optimized dispatching strategy for a wind farm with a multiple stage hybrid ESS is proposed.The first stage ESS is designed to improve the profits of wind generation through day-ahead market operations,the real-time marketbased second stage ESS is focused on day-ahead forecasting error elimination and wind power fluctuation smoothing,while the backup stage ESS is associated with them to provide the ancillary service.An interval forecasting method is adopted to help to ensure reliable forecast results of day-ahead wind power,electricity prices and loads.With this hybrid ESS design,supply reliability and market profits are simultaneously achieved for wind farms.

Integrated approach for optimal island partition and power dispatch

Operating in island mode when failure occurs in sure to maintain an uninterrupted power supply to significant loads. A two-stage approach that integrates optimal island partition and power dispatch is proposed in this paper, considering photovoltaics(PVs), batteries(BEs) and electric vehicles(EVs) as the power sources. In the first stage, energy indices are defined to describe the energy demand and the maximum energy that these distributed energy resources(DERs) can provide, and islands are partitioned based on an energy constraint. Considering the variability the loads and PVs, the energy constraint is a necessary but not sufficient condition for island operation,so in the second stage, a power dispatch model is proposed the active distribution network(ADN) is an effective mea-as a test for the island partition result. Sequential power flow is also simulated to guarantee a feasible and optimized island status. The situations when the tests are not passed are analyzed and classified, and corresponding modifications for the first stage model are provided. Multiple levels of constraints based on the energy index are established for the island partition model. The proposed approach has been validated through simulation using a modified IEEE 69-bus system which is divided into three districts with different load variability characteristics.

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.

Some Recommendations for Improving Renewable Energy Policies in China

Renewable energy is the one of the most promising solutions for environmental protection and energy deficiency. Since 2005, the Chinese government has put forward a number of measures in promoting renewable energy. This paper presents those renewable energy policies in China and illustrates their achievements and limits. Comparing the renewable energy policies in Europe and US, feed-in-tariffs and quotas are two main measures that are adopted by western countries. A detailed performance review of feed-in-tariffs and quotas is examined by using effectiveness and efficiency as criteria. The enlightenments to improve renewable policies in China include strengthening compliance with quotas, developing priority dispatch and technical standards for interconnection, putting forward a more advanced feed-in-tariff system, and ultimately guaranteeing the electricity consumer＇s right of choice.