Mixed Integer Nonlinear Programming model for the optimal design of fired heaters

In this paper, a mathematical optimization model for the optimal design of industrial furnaces/fired heaters is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operational and geometric constraints is developed to get an efficient furnace design. Discrete decisions connected with the geometric design such as number of tubes in convection and radiation sections, number of shield tubes, number of passes and number of tubes per pass are modelled by using integer variables. Continuous variables are used for process conditions (temperatures, flow-rates, pressure, velocities, pressure drops among others).The mathematical model and the solution procedure are implemented in General Algebraic Modelling System (GAMS), Brooke [A. Brooke, D. Kendrick, A. Meeraus, A. A. GAMS – A User’s Guide (Release 2.25), The Scientific Press, San Francisco, CA, 1992]. Based on a typical furnace configuration, several applications are successfully solved by applying the proposed MINLP model. In this paper, three case studies with increasing complexity are presented. In the first case study, the accuracy of results from the proposed model is compared satisfactorily with literature. In the second case study, the MINLP model is applied to optimize the fire heater’s efficiency. Finally, the total annual cost of the fired heater is minimized in the Case Study III. Also, a sensitive analysis of the unitary cost of fuel and capital investment is investigated. The developed model is characterized by its robustness and flexibility.     

A bilevel model for electricity retailers' participation in a demand response market environment

Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility.     

A model of market power in electricity industries subject to peak load pricing

This paper studies the exercise of market power in price-regulated electricity industries under peak-load pricing and merit order dispatching, but where investment decisions are taken by independent generating companies. Within this context, we show that producers can exercise market power by under-investing in base-load capacity, compared to the welfare-maximizing configuration. We also show that when there is free entry with an exogenous fixed entry cost that is later sunk, more intense competition results in higher welfare but fewer firms.     

A model for hedging load and price risk in the Texas electricity market

Energy companies with commitments to meet customers' daily electricity demands face the problem of hedging load and price risk. We propose a joint model for load and price dynamics, which is motivated by the goal of facilitating optimal hedging decisions, while also intuitively capturing the key features of the electricity market. Driven by three stochastic factors including the load process, our power price model allows for the calculation of closed-form pricing formulas for forwards and some options, products often used for hedging purposes. Making use of these results, we illustrate in a simple example the hedging benefit of these instruments, while also evaluating the performance of the model when fitted to the Texas electricity market.     

基于混合整数线性规则及迭代建模的综合能源系统优化控制

综合能源网络基于多能源技术的灵活性,可以为地区及更上级的能源系统提供服务.由于非线性因素和建模的复杂性,其运行不确定性在优化控制建模时常常被忽略.为此,提出了一个包含多能源可控装置的综合能源网络优化控制框架.并将改进型混合整数线性规划(mixed integer linear programming,MILP)和非线性...     

Organising a joint green European electricity market: the model ElGreen

In this paper, the features and the most important results of the computer model ElGreen will be presented. With the help of the computer model it is possible to simulate various promotion strategies for different technologies in all EU countries. Policies that can be selected are the most important price driven strategies (feed-in tariffs, investment subsidies, tax incentives), capacity driven instruments (tradable green certificates, national or international wide trading system) and a voluntary green pricing system.The following recommendations are derived:

(i)Regardless of which strategy is chosen credible sources must guarantee that the promotional strategy will survive a specified planning horizon;

(ii)The differences between either national trading, international trading or feed-in tariffs are very small if the design of the promotional system is optimised;

(iii)When introducing a TGC system it is of paramount importance that no mix up between existing and new capacities takes place.

     

A critical survey of agent-based wholesale electricity market models

The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed.     

A dynamic network analysis of spot electricity prices in the Australian national electricity market

This study applies dynamic network analysis to the power sector, examining the relationship between regional spot electricity prices in the Australian National Electricity Market (NEM). In particular, we employ principal component analysis and generate Granger causality networks to examine the degree of interconnectedness of the NEM in a time-varying setting. We find that the derived measures of interdependence can be related to actual market events such as price spikes, unexpected high demand for electricity, sudden increases in price volatility, rebidding of dominant generators, the temporary or permanent outage of major power stations, and upgrades and limitations in transmission capacity. In the analysed network, we find that stronger dependence is exhibited by regional markets that are linked through interconnectors, while the direction of Granger causality can be related to interregional trade. We further examine the usefulness of the derived measures for forecasting distributional characteristics of spot prices such as the maximum price, volatility, price spreads, or upcoming periods of price spikes. Our results suggest that the derived network measures have predictive power, albeit limited, for the behaviour of spot electricity prices in the NEM.     

A game theoretic model of the Northwestern European electricity market—market power and the environment

This paper develops a static computational game theoretic model. Illustrative results for the liberalising European electricity market are given to demonstrate the type of economic and environmental results that can be generated with the model. The model is empirically calibrated to eight Northwestern European countries, namely Belgium, Denmark, Finland, France, Germany, The Netherlands, Norway, and Sweden. Different market structures are compared, depending on the ability of firms to exercise market power, ranging from perfect competition without market power to strategic competition where large firms exercise market power. In addition, a market power reduction policy is studied where the near-monopolies in France and Belgium are demerged into smaller firms. To analyse environmental impacts, a fixed greenhouse gas emission reduction target is introduced under different market structures. The results indicate that the effects of liberalisation depend on the resulting market structure, but that a reduction in market power of large producers may be beneficial for both the consumer (i.e. lower prices) and the environment (i.e. lower greenhouse gas permit price and lower acidifying and smog emissions).     

Mathematical modelling of electricity market with renewable energy sources

The paper addresses the electricity market with conventional energy sources on fossil fuel and non-conventional renewable energy sources (RESs) with stochastic operating conditions.A mathematical model of long-run (accounting for development of generation capacities) equilibrium in the market is constructed. The problem of determining optimal parameters providing the maximum social criterion of efficiency is also formulated.The calculations performed have shown that the adequate choice of price cap, environmental tax, subsidies to RESs and consumption tax make it possible to take into account external effects (environmental damage) and to create incentives for investors to construct conventional and renewable energy sources in an optimal (from the society view point) mix.     

Forecasting electricity spot market prices with a k-factor GIGARCH process

In this article, we investigate conditional mean and conditional variance forecasts using a dynamic model following a k-factor GIGARCH process. Particularly, we provide the analytical expression of the conditional variance of the prediction error. We apply this method to the German electricity price market for the period August 15, 2000–December 31, 2002 and we test spot prices forecasts until one-month ahead forecast. The forecasting performance of the model is compared with a SARIMA–GARCH benchmark model using the year 2003 as the out-of-sample. The proposed model outperforms clearly the benchmark model. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.     

新电改背景下广东省售电侧恶性价格竞争机理研究——基于Bertrand竞价模型

为理顺恶性价格竞争的形成机理,以广东省售电企业为研究对象,将售电企业分为有发电资产的第一类售电企业与无发电资产的第二类售电企业,通过建立Bertrand模型研究新电改背景下恶性价格竞争机理,并对售电企业进入或退出售电市场曲线进行了分析。结果表明:引入市场竞争后的售电侧有形成恶性价格竞争的可能性,相关部门应加以防范。     

A spot-forward model for electricity prices with regime shifts

We propose a novel regime-switching approach for electricity prices in which simulated and forecasted prices are consistent with currently observed forward prices. Additionally, the model is able to reproduce spikes and negative prices. We distinguish between a base regime as well as upper and lower spike regimes. We derive hourly price forward curves for EEX Phelix, and together with historical hourly spot prices, historical hourly price forward curves are the basis for model calibration. The model can be used for simulation and forecasting of electricity spot prices over short- and medium-term horizons. Tests imply that it shows a better performance than classical time series approaches.     

A CGE analysis for quantitative evaluation of electricity market changes

Risk and uncertainty entailed by electricity industry privatization impose a heavy burden on the political determination. In this sense, ex ante analyses are important in order to investigate the economic effects of privatization or liberalization in the electricity industry. For the purpose of fulfilling these quantitative analyses, a novel approach is developed, incorporating a top-down and bottom-up model that takes into account economic effects and technological constraints simultaneously. This study also examines various counterfactual scenarios after Korean electricity industry reform through the integrated framework. Simulation results imply that authorities should prepare an improved regulatory system and policy measures such as forward contracts for industry reform, in order to promote competition in the distribution sector as well as the generation sector.     

考虑可再生能源消纳与灵活性需求的电力市场优化决策研究

可再生能源配额制与电力市场改革同步推进,电力系统灵活性需求急剧增加.为促进可再生能源的消纳,提高电力系统的灵活性,本文提出了一种电力市场双层优化决策模型.先是考虑风光负荷之间的相关性,建立了灵活性需求的概率模型;进而建立多市场主体下考虑省间-省内可再生能源和常规能源交易的双层优化模型;最后利用KKT条件和拉格朗日对偶理...     

A model of substitution in a competitive market

A dynamic model of technological substitution is developed which is a generalization of the two-party substitution model of Fisher and Pry. Competition among an arbitrary number of technologies is modeled as a sequence of pair-wise interactions. The intent is to reproduce the findings of Marchetti, who has observed that a large variety of historical substitutions follow a logistic pattern.     

Successful renewable energy development in a competitive electricity market: A Texas case study

The development of renewable energy in markets with competition at wholesale and retail levels poses challenges not present in areas served by vertically-integrated utilities. The intermittent nature of some renewable energy resources impact reliability, operations, and market prices, in turn affecting all market participants. Meeting renewable energy goals may require coordination among many market players.     

Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market

An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration.     

The impact of climate change on the electricity market: A review

Climate change will impact electricity markets through both electricity demand and supply. This paper reviews the research on this topic. Whereas there is much that remains unknown or uncertain, research over the last few years has significantly advanced our knowledge. In general, higher temperatures are expected to raise electricity demand for cooling, decrease demand for heating, and to reduce electricity production from thermal power plants. The effect of climate change on the supply of electricity from non-thermal sources shows great geographical variability due to differences in expected changes to temperature and precipitation. Whereas the research frontier has advanced significantly in the last few years, there still remains a significant need for more research in order to better understand the effects of climate change on the electricity market. Four significant gaps in the current research are regional studies of demand side impacts for Africa, Asia, the Caribbean and Latin America, the effects of extreme weather events on electricity generation, transmission and demand, changes to the adoption rate of air conditioning, and finally, our understanding of the sensitivity of thermal power supply to changes in air and water temperatures.