Investment Model for Power Generation and Transmission Network Expansion in Turkey

Provision of adequate electricity is one of the major factors for industrial and commercial development. However, decisions on the expansion of electricity are bogged down by high investment requirements and nonsynchronized expansion between electricity generation and transmission systems. As a rule, the investment requirements for these types of projects are immediate but their benefits can be obtained only in the long-term basis albeit electricity planners base their decisions on immediate requirements of shorter terms. As investment funds are very hard to come by, the funds, if available, should be utilized to maximum by minimizing the investment through a synchronized expansion planning of both electricity generation and transmission systems. This paper attempts to address this opportunity. We have proposed here a mixed integer model to develop concurrent transmission and generation investments plans. The model selects new generation plants or generation capacity expansions for existing plants that are located on the interconnected network by considering explicitly congestion in the transmission network. Hence the model contributes to this area by filling in the gap between models for developing long-term power generation policies and power flow models focusing on transmission network expansion. The application of the model in Turkey’s electricity network highlights the country’s congested areas in the transmission network, which might lead to loss of load and inefficient generation capacity expansion if not tackled properly. The analysis shows that a cost efficient generation expansion is possible to realize in congested regions if proper transmission expansion decisions are made concurrently with generation expansion decisions.     

Estimation of a Sensitivity-Based Metric for Detecting Market Power

The abuse of market power is a potentially serious problem for market designers. Few indices, if any, exist to measure the potential for market power in real time. In this regard, Murillo-Sanchez et al. derived an expression for a dispatch-to-price sensitivity matrix, M. The expression requires information about network topology and parameters, as well as the rules used to operate the market. While computing the matrix is conceptually easy for those with all the market and system information, such as an independent system operator, the method is probably impractical for market participants due to the inaccessibility of much of the information. In this paper, a method for estimating the M matrix by using publically available data are suggested, indicating that any market participant who does the computation will know when conditions permit them to lower or raise prices through decreased/increased bids and/or offers.     

Optimal Retailer Load Estimates Using Stochastic Dynamic Programming

In this paper, we describe a stochastic dynamic programming methodology for determining optimal forward load estimates for electric power retailers to their suppliers. This work describes both a model as well as results based on real data for the Electric Reliability Council of Texas market and provides insights useful for planning purposes for electric power retailers in the face of uncertain market prices and end-user loads.     

Customer-Focused Assessment of Electric Power Microgrids

The cost-effectiveness of interconnected microgrid systems with combined heat and power is examined for 36 cases involving six microgrid applications in six different U.S. locations. In the baseline analysis, microgrids are found to be good investments in areas with relatively high “spark spreads” (electricity/natural gas price differentials). Customers with a higher value for electric reliability realize greater benefits. Results become more favorable over time if the rate of increase of electricity prices is at least 60% of the rate of increase of natural gas prices—a plausible scenario in states with substantial natural-gas fired capacity. Sensitivity analyses reveal that the choice of microgrid customer mix has a much greater impact on system economics than climate. Economies of scale are shown to be fairly modest for the systems considered here, but microgrids do show clear benefits over traditional single customer distributed generation. If performance goals of current U.S. Department of Energy research programs for IC engines and microturbines are met, rates of return for microgrid investments increase 10–20%.     

输配电价测算方法的研究

电力改革是电力行业发展的必然趋势,输配电价独立核算是电力、电价改革的核心。通过对输配电价的测算方法的深入分析．详细介绍了如何科学合理地对其按电压等级和不同用户进行分类定价。     

Intertemporal Planning of Transmission Expansions in Restructured Electricity Markets

In the new environmental era, electricity markets change rapidly, requiring dynamic strategic responses from market agents and regulators. In this paper, we study the intertemporal dimension of the network planner decision process. In particular, we formulate a dynamic model of transmission investments and use this model to compare the behavior of a network planner when considering and when ignoring the dynamic nature of transmission investments. This paper’s analysis focuses on the situation faced by some hubs with growing demand which meet their demand with power generated by distant sources subject to uncertainty. This is the case of a large city, which demand is satisfied by hydro or wind power supplied from sources located far away. For this kind of systems (typified as a simple two-node network that satisfies certain properties), we characterize the structure of a socially efficient transmission investment policy. It is shown that, in such a network, an optimal open-loop transmission investment policy has a multiperiod (s,S) structure. The results are illustrated with a numerical example.     

Impact of Market Uncertainty on Congestion Revenue Right Valuation

Congestion revenue rights (CRRs) are property rights that entitle and/or obligate their holders to receive specified (possibly negative) congestion revenues. They provide price certainty for transmission customers who need to purchase open access transmission service. Auctions and bilateral transactions allocate CRRs to market participants who value the transmission rights the most. If valued correctly, CRRs would yield market signals required in valuing congested transmission facilities and inducing capital investment in the transmission sector. Financial transmission rights (FTRs) and flowgate rights (FGRs) are two specific forms of CRRs. This paper presents a simulation based approach for valuing FTRs and FGRs. Using the proposed approach, we derive the probabilistic characteristics of FTR and FGR values under market uncertainties resulting from fluctuating system loads, varying fuel prices, and other system contingencies such as unplanned transmission circuit and generator outages. A theoretical framework consisting of a multilateral-transaction model, a nonconforming electric load model, and CRR valuation models under different market structures incorporating market aforementioned uncertainties is proposed. A Monte Carlo simulation procedure is employed to obtain the distributions of FTR and FGR values. Numerical implementation of the proposed approach is illustrated on a sample test system.     

Economic Transmission Planning Model Suitable for a Regulated Network Service Provider

Conventional transmission planning models are subject to constant debate in the context of competitive markets, due to the functional unbundling of transmission sector from generation and distribution sectors and due to the new environment regulations. A value-based transmission planning model is proposed, suitable for an unbundled transmission network service provider having no assets in the generation sector. The model minimizes the long-term transmission investment costs and the expected social costs incurred to its clients, energy producers, and consumers, in the power auctions due to transmission bottlenecks. The uncertainties involved when incorporating short-term market models into long-term planning models are modeled with probabilistic representations for the bid prices, the component availabilities, and the hourly load variations. These features make this model suitable in the new environment paradigm. Generalized Benders decomposition technique with nonsequential Monte Carlo technique is employed to solve the final stochastic mixed-integer optimization model. Case studies are given to illustrate the performance of this model by implementing it in the modified Garver’s six-bus test system and the IEEE 24-bus reliability test system for a single planning year.     

Optimal Expansion Planning for the Deployment of Wind Energy

With the growing concern regarding climate change, the integration of renewable electric technologies into the grid has taken on increased importance over the past decade. In particular, the integration of wind energy is increasing the attention paid to power transmission investment planning, generation adequacy, and secure system operation. This attention calls for the development of new tools that can simultaneously address the economics, transmission, ancillary services, and reserve requirements associated with wind energy. This paper proposes a method for choosing the optimal plan for expanding transmission and generation considering optimal power flow, discrete plant sizes, and the resource variability of wind energy. The method minimizes total cost, i.e., the sum of the construction cost and the operation cost, to fulfill expected load. Due to the nature of transmission expansion planning and the economies of scale associated with conventional power plants, finding the expansion plan is an integer programming problem solved by a branch and bound method. The proposed method is tested by applying it to a nine-bus system.     

动力节电新技术在铝电解企业中的运用

在铝电解工艺中,动力用电量一般不到总用电量的10%,所以往往得不到管理者的重视。近年来,随着工艺节电技术的不断完善和企业节电意识的不断提高,在抓好工艺节电之时,通过采用新型变压器、接触器、变频器等节电设备改造以节省企业电费支出、降低生产成本,提高市场竞争力。     

线性回归法在电力多边交易中的应用

通过利用线性回归法建立煤气量、蒸汽量和发电量关系的模型,精准测算包钢公司自发电量,为计算外购电量提供数据支撑,保障企业在内蒙古电力多边交易市场中最大限度享受政策优惠,降低公司用电成本。     

Analytical Approximation to the Probability Distribution of Electricity Marginal Production Costs

This paper proposes an analytical approximation to calculate the probability distribution of the marginal production cost of an electric power system. This information is expected to benefit both buyers and sellers of electricity in the upcoming deregulated environment. Since the exact computation of the probability distribution is prohibitive for large systems, we propose to use a combination of the Edgeworth expansion and the large deviation approximation. The results show that the Edgeworth expansion is accurate for computing probabilities at the center of the distribution and the large deviation approximation for computing tail probabilities. Monte Carlo simulation is used as a benchmark to verify and assess the performance of the approximation method in a large power system. In our stochastic model of the system marginal production cost, the load is represented by a normal distribution and the generating unit availability is characterized by its forced outage rate. It is found that the proposed approximation provides accurate estimates at a reasonable computational time.     

Optimal Self-Scheduling of a Tidal Power Plant

This paper considers the optimal operation of a tidal power producer. Different generating cycles for the tidal power plant are considered. The paper provides a tool for self-scheduling of the tidal power producer so that the maximum profit from selling energy in an electricity market is achieved, while meeting all technical operating constraints of the tidal power plants. The formulation provided is also valid in a centralized operation framework; the only change needed is to define a different cost-related objective function. The resulting optimization problem, which is mixed-integer and linear, is solved using commercially available software. Results from realistic simulations are reported and analyzed.     

Transmission Asset Investment in Electricity Markets

We construct a general analytic framework for the transmission network investment problem in the market environment and demonstrate its application to some test systems. We define a set of metrics to quantify the improvement attained in terms of welfare for all the participants and make use of them in the evaluation of the impacts of new transmission investments under competition. The proposed metrics are useful to the central entity responsible for transmission planning to provide meaningful measures of the effects of a modification in the grid over the planning horizon. The proposed framework is particularly useful to transmission network planners to support desired environmental targets. The analysis of the effects of new investments on the participants affected by the expansion includes the assessment of appropriate environmental attributes. The consistency of the measured values in terms of these metrics allows the comparison of disparate transmission investment projects and their effective prioritization. A key element of the framework is the deployment of an optimization scheme to maximize the social welfare with and without the transmission asset investments under various bidding behaviors of the market players and contracting conditions. We report the application of the proposed framework to investigate several transmission expansion scenarios on the IEEE 24-bus reliability test system network. The results on both pool-based markets and combined pool-bilateral contract markets provide a good illustration of the capability of the framework to effectively address realistic questions in transmission investment.     

基于5G网络的工控PLC通信实现方法

工控系统是工业生产的核心控制中枢,一般通过PLC对生产流程进行实时的监控。上位机服务器与PLC之间的通信一般基于工控协议,工控协议由各工控企业自行开发,兼容性差,封闭性强,其通信常常为自动化项目中的难点。5G通信技术作为新一代移动通信技术,具有高带宽、低时延、稳定性好等优秀特性,天然适用于具有极高通信要求的工业控制网。但是,5G网络通常由运营商建设,数据需经过运营商核心网进行交互,如何实现5G网络与工控PLC之间的互通就成为了难点问题。本文基于工控协议底层,通过MEC边缘计算及隧道技术,提出了一种5G网络下工控PLC通信的新思路。     

Distributed Generation with Heat Recovery and Storage

Electricity produced by distributed energy resources (DER) located close to end-use loads has the potential to meet consumer requirements more efficiently than the existing centralized grid. Installation of DER allows consumers to circumvent the costs associated with transmission congestion and other nonenergy costs of electricity delivery and potentially to take advantage of market opportunities to purchase energy when attractive. On-site, single-cycle thermal power generation is typically less efficient than central station generation, but by avoiding nonfuel costs of grid power and by utilizing combined heat and power applications, i.e., recovering heat from small-scale on-site thermal generation to displace fuel purchases, DER can become attractive to a strictly cost-minimizing consumer. In previous efforts, the decisions facing typical commercial consumers have been addressed using a mixed-integer linear program, the DER customer adoption model (DER-CAM). Given the site’s energy loads, utility tariff structure, and information (both technical and financial) on candidate DER technologies, DER-CAM minimizes the overall energy cost for a test year by selecting the units to install and determining their hourly operating schedules. In this paper, the capabilities of DER-CAM are enhanced by the inclusion of the option to store recovered low-grade heat. By being able to keep an inventory of heat for use in subsequent periods, sites are able to lower costs even further by reducing lucrative peak-shaving generation, while relying on storage to meet heat loads. This and other effects of storage are demonstrated by analysis of five typical commercial buildings in San Francisco, California, in the United States, and an estimate of the cost per unit capacity of heat storage is calculated.     

Integrating Large Wind Farms into Transmission Planning of Hydrothermal System

This paper is aimed at presenting a methodology leading to the incorporation of large wind farms to the transmission planning of hydrothermal systems. We resorted to a simulation program for an optimum operation of a generation-transmission system based on stochastic dual dynamic programming and incorporated the wind energy features as well as undertook the simulations. This work was applied to an existing hydrothermal system; chiefly for evaluating the wind farm impact in three specific areas: the network expansion, the energy cost, and the effect on the reservoir water level.     

电解铝企业对清理高耗能企业优惠电价问题的思考

清理优惠电价将拉开高能耗企业的成本差距,未来国家按照节能减排思路会促使资源价格调整,没有自备电厂和已批准的直购电政策的电解铝企业将受到较大冲击。     

Evaluation of Black-Start Schemes Employing Entropy Weight-Based Decision-Making Theory

Optimization of schemes for black-start is one of the most important factors determining the speed of power system restoration after either a global blackout or a local outage. In this paper a novel method employing the entropy weight-based decision-making theory is proposed for this application. By using the method for the decision making in black start, the subjective weights acquired from knowledge and experience of experts could be used in conjunction with the objective weights (entropy weighs) deduced from some closely related indices. Obviously, the developed method can greatly improve the performance in power system restoration by overcoming the shortcomings of conventional methods that only use either the subjective or the objective weights. Furthermore, the proposed method is applicable in power systems with different levels of black-start experience for assisting the optimal black-start decision making. It is shown that the proposed method is suitable for power systems with different levels of black-start experience.     

基于Stackelberg博弈的钢铁企业余热余压发电的上网电价策略

研究钢铁行业余热余压发电与传统火力发电组成的电力市场,分析钢铁企业余热余压发电上网电价策略。建立了有关钢铁企业、传统化石燃料发电企业和地方政府三方的斯坦克尔伯格博弈（Stackelberg）模型,比较余热余压发电技术上网电价的三种定价策略（固定价格、固定溢价和可变溢价）,并进行了数值模拟分析市场规模、余热余压发电成本系数和钢铁企业环境成本对最优规制价格、最优钢铁企业利润和最优社会总福利的影响。结果表明:三种定价策略下最优规制价格、最优钢铁企业利润和最优社会总福利差异非常大。不同偏好的政策制定者会从不同的风险性和补贴选择不同的定价策略。其中,风险性大和补贴高是最优规则价格中的可变溢价策略、最优钢铁企业利润中的固定溢价策略和最优社会总福利中的可变溢价策略;风险性低和补贴低是最优规则价格中的固定价格策略、最优钢铁企业利润中的固定价格策略和最优社会总福利中的固定溢价策略;其他情形的风险性和补贴位于这两种情况之间。