Research on the Model of Long Term Generation Planning in Power Market Reform

With the deepening of China’s power market, bilateral transactions will continue to grow in large scale. The release of bilateral transactions locked more regulatory resources of the power grid, will directly affect the operation mode of the unit and the implementation of planned electricity. In the paper, considering the large-scale bilateral trade effect on the peak regulation of power grid, energy saving and emission reduction, power system security and other factors, and then putting forward the method of long term generation planning and annual planning model to adapt to the safe operation of power grid in China. In the model, the target is minimizing the monthly load rate deviation and the annual electric quantity deviation rate, the latter includes the capacity factor. In addition, the constraints include the monthly quantity of electricity, adjustable utilization rate deviation, load rate, reserve and key sections, etc. Through an example to verify the correctness of the model, the planning and power transaction results can satisfy the peak regulation of load, energy saving and emission reduction and safety operation of the power grid requirements.

Analysis of Nigerian Electricity Generation Multi Year Tariff Order Pricing Model

The Multi Year Tariff Order (MYTO) is the Nigerian Electricity Regulatory Commission (NERC) pricing framework for determining the Nigerian Electricity Supply Industry (NESI) pricing model. One of the objectives of the NERC’s MYTO pricing model is to ensure regulated electricity end user tariff without compromising return on investment. Achieving this objective is imperative to attract investors in the growing Nigerian electricity market. However, NESI has hitherto been faced with challenges ranging from its inability to provide sufficient power to its customers to not being viable enough to provide return on capital invested. In this paper, sensitivity analysis of power plant operation and performance parameters on the cost of electricity (CoE) generation using MYTO (power generation) pricing model were evaluated. Thermodynamic modeling and simulation of an open cycle gas turbine (OCGT) was carried out to augment scarce data on power plant performance and operation in Nigeria. Sensitivity analysis was carried out using probabilistic method based on Monte Carlo simulation (MCS) implemented in commercial software (@ Risk®). The result highlighted sensitivity of the model input parameters to cost of electricity generation based on technical and financial assumptions of MYTO model. Seven most influential parameters affecting generation cost were identified. These parameters and their correlation coefficients are given as: 1) foreign exchange rate, 0.76;2) cost of fuel, 0.51;3) thermal efficiency, -0.23;4) variable operation and maintenance cost, 0.22;5) fixed operating and maintenance cost, -0.03;6) capacity factor, -0.02;and 7) average capacity degradation, 0.01. Based on the gas turbine engine and input parameter distributions statistics for this study, the generation cost lies between 9.84 to 15.45 N/kWh and the probabilities of CoE within these values were established.

Management of Peak Loads in an Emerging Electricity Market

An electricity market is a trading platform provided by the actors in the electricity sector to sell and buy electricity while maintaining the stability of the transmission network and minimizing energy losses.The management of electrical energy for rational use consists of all the operations that the consumers can carry out in order to minimize their electricity bill,while the producers optimize their benefits and the transmission infrastructure.The reduction of active and reactive power consumption and the smoothing of daily and yearly load profiles are the main objectives in this work.Many developed countries already have properly functioning electricity markets,but developing countries are still in their infancy of deregulated electricity markets.The major tools used in smoothing the load profiles include decentralized generation,energy storage and demand response.A load power smoothing control strategy is proposed to smooth the load power fluctuations of the distribution network.The required power change is determined by evaluating the power fluctuation rate of the load,and then the required power change is allocated to some generators or to some stored reserves.Otherwise,the consumers are made to curtail their power consumption.The ideas proposed in this work provide important opportunities for energy policy makers and regulators.These ideas would only be feasible if there exists real-time communication among the actors in the electricity market.The results indicate that as much as 1100 Megawatt-hours of energy can be stored for smoothing the load profile,when applied to the Southern Interconnected Grid of the Cameroon power system;and that Time of Use(TOU)pricing could be used instead of rotating blackouts in case of energy shortage.

Hybrid Scenario Generation Method for Stochastic Virtual Bidding in Electricity Market

Stochastic optimization can be used to generate optimal bidding strategies for virtual bidders in which the uncertain electricity prices are represented by using scenarios.This paper proposes a hybrid scenario generation method for electricity price using a seasonal autoregressive integrated moving average(SARIMA)model and historical data.The electricity price spikes are first identified by using an outlier detection method.Then,the historical data are decomposed into base and spike components.Next,the base and spike component scenarios are generated by using the SARIMA-and historical data-based methods,respectively.Finally,the electricity price scenarios are obtained by combining the base and spike component scenarios.Case studies are carried out for a virtual bidder in the PJM electricity market to validate the proposed method.The optimal bidding strategies of the virtual bidder are generated by solving a stochastic optimization problem using the electricity price scenarios generated by the proposed method,the SARIMA method,and a historical data-based method,respectively.Case study results show that the proposed method is better than the SARIMA method in preserving statistical properties of the electricity price in the generated scenarios and is better than the historical data-based method in predicting the future trend of the electricity price and,therefore,can help the virtual bidder earn more profit in the electricity market.

Energy Storage Modeling of Inverter Air Conditioning for Output Optimizing of Wind Generation in the Electricity Market

In order to achieve the compatibility of the air conditioning(AC)loads with the current dispatch models,this pa-per utilizes demand response(DR)technology as energy storage resources to optimize the aggregator’s behaviors in the real-time market for less economic loss caused by the fluctuations of wind power.The inverter AC,as a typical demand response resource,is constructed as a power type battery model(PTBM)and a capacity type battery model(CTBM)according to the different control methods,which are expressed through a circuit model and mathematical model to describe the energy storage characteristics of ACs.Moreover,the comparisons between the PTBM and CTBM are given analytically by their response speed,power&energy capacity and the cost of control,which will be helpful to guide the associated operators to choose the appropriate models to take part in demand response.Considering that the wind generation fluctuates frequently and greatly,the PTBM is chosen to take part of the demand response for output optimizing of the wind generation.The simulation results demonstrate that PTBMs can work in the way of conventional batteries(CBs)to optimize wind generation in the real-time market.

Enabling Hybrid Projects through Appropriate Market Design

Large-scale hybrid power plants, composed of two or more generation sources and with the participation of energy storage systems, have driven important electricity Market Design regulation discussions worldwide. Regulatory framework ought to be adapted to support technical particularities of these new generation arranges. This paper presents an assessment of the main requirements to be met by Market Design to enable hybrid power plants by means of assertive market incentives. Assessing regulatory adjustments promoted in Australia, United States, India, China, and Brazil, emphasizing the latter one, the authors presents a case study by applying specific computational simulation and optimization model to a hybrid Hydro-Solar plant, that supports the findings for the necessary evolution needed in the national regulatory framework in order to enable hybrid projects. The evaluation of international experiences indicates that the insertion of hybrid projects is associated with the design of the market they belong to and demand regulatory adjustments so that their attributes can be properly valued for the benefit of all stakeholders, especially for the electricity consumer.

Profit-Based Optimal Operation of a Head-Dependent Hydroelectric Power Station in the Bilateral Market

Deregulation and liberalization of electric power industry, among other things, has created new requirements for the market participants. The power system engineer, operator, and, in general, the market participants are being faced with requirements for which they do not have adequate training and the proper software tools. In this framework, among others, a pure hydro-generation company has to operate its hydro units, throughout the operating day, trying to fulfill the market clearing schedule or a bilateral contract, and modify the program in the intra-day energy markets if necessary （or more suitable） as real-time operation is getting closer. In this scenario the objective is to maximize the hydroelectric power plant profit from selling energy in the spot market or by means of bilateral contracts. In this paper the optimal operation of a head-dependent hydroelectric power station in bilateral market-short-term hourly hydro resource scheduling for energy is obtained.

Robust coordination of interdependent electricity and natural gas systems in day-ahead scheduling for facilitating volatile renewable generations via power-to-gas technology

The increasing interdependency of electricity and natural gas systems promotes coordination of the two systems for ensuring operational security and economics.This paper proposes a robust day-ahead scheduling model for the optimal coordinated operation of integrated energy systems while considering key uncertainties of the power system and natural gas system operation cost. Energy hub,with collocated gas-fired units, power-to-gas(Pt G) facilities, and natural gas storages, is considered to store or convert one type of energy(i.e., electricity or natural gas)into the other form, which could analogously function as large-scale electrical energy storages. The column-andconstraint generation(C&CG) is adopted to solve the proposed integrated robust model, in which nonlinear natural gas network constraints are reformulated via a set of linear constraints. Numerical experiments signify the effectiveness of the proposed model for handling volatile electrical loads and renewable generations via the coordinated scheduling of electricity and natural gas systems.

合同交易量和竞价交易量在日计划中的经济分配

目前电网公司在进行现货交易时 ,一方面要依据各发电公司申报的上网电价 ,另一方面也要考虑与发电公司原有的购售电合同 ,因此如何在保证完成年购售电合同的前提下 ,在机组竞价上网电价一定的条件下 ,使总的购电费用最低 ?基于这个目的 ,文中建立了在交易日的 96个交易时段经济分配日合同交易量和竞价交易量的数学模型 ,并应用线性规划法对该模型进行求解 ;文中给出的协调上网机组在各交易时段的合同交易量和竞价交易量的具体办法 ,在一定程度上限制了机组利用其特性约束条件进行投机报价 ;根据机组合同交易量的完成情况 ,滚动修正其下一交易日的日合同交易量 ,并给出表征机组上网紧迫程度的指标。

电力市场环境下电网日发电计划的电量经济分配策略

电力市场环境下,电网公司在进行购电交易时,要考虑各发电公司申报的上网电价,同时还要兼顾与发电公司原有的购售电合约。因此,需要对预测发电量进行合约电量和竞价电量的经济分配,这样既可以使发电方得到保护,又可以使电网公司利益最大化,更有利于电力市场的稳定发展和电网安全运行。为此,该文建立了预测交易日的48个交易时段经济分配日合约交易量和竞价交易量的数学模型。同时,为使求解过程简单易行可靠,又给出恰当的简化模型,并用线性规划和逐步淘汰相结合的方法对该模型进行求解。基于Matlab6.1的仿真算例分析表明,文中所述的经济分配方法更为简单合理。

发电机组检修市场的初步设计

电力市场环境下调度部门如何在保证系统可靠性的同时保证调度的公平性,这是一个亟待解决的问题。设计了一种新的发电机组检修计划制定模型:首先由各发电公司根据机组的检修周期、运行情况、对未来电价水平的预测和调度部门公布的未来各时段的最大检修容量,在规定的时间内上报机组的检修起始时间、检修持续时间、检修容量和检修报价;然后调度部门根据各发电公司的报价,对能够满足系统可靠性要求的检修机组按照报价从高到低的顺序安排检修,并收取相应的费用,而其余检修机组则按照等备用原则进行安排;最后调度部门将所收取的费用按照类似并联电路电流分配原则返还给各发电公司,从而确保其非盈利性。文中所提出的模型,既充分体现了发电公司的检修自主权,又保证了系统的安全可靠和调度的公平性。

电力市场竞价交易计划模型初探

讨论了电力市场下的竞价交易与传统的发电计划的区别,探讨了影响竞价交易的电力市场运营因素,指出了不同竞价交易因素将会影响竞价交易计划模型。针对部分投标方式建立了竞价交易计划的具体模型。讨论了我国现阶段电力市场的运营规则,并选取了适合于我国的竞价交易计划模型。

电力市场中电力供应商竞标策略的选择

对于电力市场中一个独立的电力供应商而言 ,除了解决传统意义上的机组组合或水火电联合经济调度问题 ,更重要的是如何选择竞标策略以使利益最大化。文中提出利用序优化的方法解决日竞标电力市场中电力供应商的竞标策略选择问题。首先建立电力市场仿真模型并构造一个尽量小而好的竞标策略子集 S,并保证 S在概率意义上含有“足够好”的解 ,然后通过对 S中每一个元素的精确计算得到其中最好的竞标策略 ,并以此作为最终的竞标策略。基于一个拥有 1 0个火电机组的独立电力供应商和美国加州电力市场历史价格数据的仿真结果表明 。

火电机组年合同电量的编制与分解算法研究

在传统调度、完全市场、限量竞价三种模式下,提出了火电机组年合同电量的编制与分解算法。算法从兼顾电网调度公平性和经济性的角度出发,以发电-负荷平衡、最大/最小发电量、机组检修计划等条件为约束,对火电机组的年合同电量进行编制和分解。算法通过调整各种模式下交易电量的市场份额以适应市场交易机制的变化,并对不同机制下的年合同电量提出了相应不同的编制与分解算法,具有较强的适用性和适度的前瞻性。某地方电网算例验证了该算法的实用性和有效性。

基于SP/A决策思想的发电公司报价决策模型及求解方法

以安全、潜力和期望(security,potential and aspiration,SP/A)风险决策理论为基础,该文对发电公司面对风险决策时应该考虑的因素进行了分析和数学描述,其中在报价方案潜力性的分析上有效地结合了经济学中机会成本理论。在此基础上,考虑发电公司自身发电计划约束,建立起一种发电公司计及风险因素的竞价决策模型,并结合矩阵实数编码遗传算法(matrix real-coded genetic algorithm,MRCGA)对该模型的优化求解进行了探讨。该文所建的竞价决策模型既考虑了自身发电计划安排,又顾及了在面对风险发电公司竞价决策时应该考虑的一些因素,因此模型比较贴近于实际的发电竞价情况。通过算例的模拟分析表明,文中所提出的基于SP/A的发电公司竞价决策模型是合理的,其求解方法也是切实可行的。

不同允许报价段数对发电公司报价策略的影响

针对国内外实际运营的电力市场中普遍采用的分段报价规约研究了不同允许报价容量段数对发电公司构造最优报价策略的影响。在研究初期以作为价格接受者的发电公司为研究对象,首先采用概率方法模拟电力市场中的电价并在此基础上采用等概率法建立了模拟发电公司最优报价策略的多段报价模型;然后研究了发电公司风险偏好程度和市场信息不对称对其构造最优报价策略的影响。最后通过算例对所提出的模型和方法进行了说明。

市场环境下水电系统短期预发电计划问题研究

随着市场化的推进,水电不久将走向市场,传统上以发电量最大为准则的优化调度,已不适应新形势下的水电经济运行。文中探讨了市场环境下水电站(群)短期(日)优化调度的效益最大问题,建立了相应的数学模型,为水电公司在日前市场上科学地申报次日各时段容量提供了依据。并通过实例对比分析,验证了所给出的模型的合理性和有效性。

电力市场交易计划中的发电调度规约研究

在电力市场中,机组的出力计划需要根据有关交易计划和市场规则中的发电调度规约来制定。机组的发电调度规约主要包括机组开停机规约、发电公司(厂)内部各机组间合同电量的分配规约、边际机组间的出力分配规约、机组发电计划调整规约等。结合我国电力市场建设的实际,分别针对全电量竞价模式和部分电量竞价模式分析了竞价开机、合同开机2种机组开停机规约;为协调发、购电双方的利益要求,提出了根据竞价机组可用发电量的比例或竞价上网电量的比例等2种在发电公司(厂)内部分配各竞价机组合同电量的方法;为协调边际机组间的边际负荷分配问题,提出了比例分配法、依次分配法2种分配边际负荷的基本方法;根据机组发电计划的组成特点,提出并分析了日合同计划不可调、日合同计划可调2种机组发电计划调整规约。

考虑CCER机制的碳-电耦合市场水火电协同竞价模型

当前,全国统一电力市场体系和全国碳交易市场正在同步改革,发电企业面临着在电力市场和碳市场竞争的双重压力。如何适应新的市场环境,在碳-电耦合市场中统筹考虑市场细则及自身电源特征制定竞价计划,是当前发电企业亟须解决的实际问题。针对这一问题,提出了考虑国家核证自愿减排量(CCER)机制的碳-电耦合市场水火电协同竞价模型。该模型详细考虑了碳市场中的碳清缴、CCER抵消、违约惩罚等机制及电力市场特征,兼顾梯级水电站水力-电力的时空耦合联系及非凸非线性的发电运行特征,描述了水火电在耦合市场中的协同竞价要素。针对模型中的非凸及逻辑表达式,引入多种线性化方法将其转为混合整数二次规划问题予以求解。以中国澜沧江流域梯级水电站与火电厂为工程背景验证了模型的有效性,并分析了碳-电耦合市场机制的作用效果。

考虑网损和输电约束的发电竞价交易方法

采用非线性规划方法解决电力市场中机组多时段报价与发电计划问题。建立了考虑抽水蓄能电站的多时段发电计划模型 ,在排序的基础上考虑输电约束和网损对发电计划的影响 ,用非线性优化方法进行计算 ,得到满足报价和电网约束的最优发电计划。对一个 6节点母线系统进行了多时段发电交易计划分析 ,结果显示电网输电约束和传输损失对发电计划产生影响 。