Guest editorial

Citation

Henggeler Antunes, C. (2008), "Guest editorial", International Journal of Energy Sector Management, Vol. 2 No. 3. https://doi.org/10.1108/ijesm.2008.32802caa.002

Guest editorial

Article Type: Guest editorial From: International Journal of Energy Sector Management, Volume 2, Issue 3

The energy sector has been a fertile ground for the application of models and methods in the realm of Operational Research. Oil, coal and electricity industries have been using OR techniques since the 1950s to address a large range of problems of operational nature. In September 1957, an article in The Economist reported about the First International Conference on Operational Research (Oxford, UK) stating that OR helped how to manage optimally Britain’s power stations. Utilities, namely hydroelectric companies, have used OR techniques to determine how to efficiently generate power as well as how effectively trade it. In the oil industry, refinery operations management rely on OR techniques. With the deregulation of the energy industry and the end of the vertical integration in the electricity sector, the variety and complexity of the problems to be faced by several players raised enormously. In this context, concerns such as the need to guarantee a secure supply in an affordable way to consumers, and the environmental and sustainability challenges associated with the production and use patterns of different energy forms, are bound to create new opportunities for OR. Moreover, it must be noticed that the challenging diversity and complexity of the problems arising in the energy sector have fostered new methodological developments, which are incorporated into the OR tool bag and can be creatively applied in other fields.

In the energy sector, policy, planning and operational management decisions are at stake, involving distinct players such as utilities, regulatory bodies and governments, marketers and end-users. Problems range from the operational to the strategic decision levels, with different perspectives involved such as technical issues, financial goals, socio-economic objectives, environmental concerns, etc. This diversity of problems, players and objectives, has a consequence in the development of a vast set of approaches available to researchers and decision-makers to tackle them.

This special issue presents eight papers dealing with different and interesting management problems in the energy sector, from issues related to energy markets in a context of restructuring and deregulation to load forecast and unit commitment optimisation. Besides their methodological contributions these papers possess an applied, practical-oriented, problem-solving nature, which can be of help for researchers and decision-makers facing similar problems. We hope these papers reveal to the IJESM audience the importance and value-added of using OR models and methods to tackle in a creative and effective manner the challenging problems arising in the energy sector in order to support sound decision-making.

The energy industry has witnessed profound changes, namely related with the deregulation trends and environmental challenges. In a competitive setting, electricity generation markets offer new opportunities, also conveying new risks to the companies. The paper by Mosquera, Reneses and Sánchez-Úbeda addresses medium-term risks faced by electricity generation companies in competitive markets, by developing risk analysis models for supporting decision making processes taking into account the tradeoffs between profits and risk exposure. In this time frame, companies face market risks because they are exposed to the uncertainty of electricity prices due to the stochastic nature of some variables, such as demand, hydro conditions, CO₂ emission costs, fuel (coal and natural gas) prices. A market equilibrium model is used to assess the impact of the different risk factors, which are modelled by means of scenarios. Decision trees are used to analyze the outputs obtained with the different scenarios, such as electricity prices or companies’ profits.

The European Union is in the process of changing from several highly diverse domestic monopolistic electricity markets into a single liberalised market under two driving forces, liberalisation and integration. In general, interconnectivity remains low and pricing is complex and dependent on the regulatory framework, capacity and global energy prices. Empirical evidence shows a diversity of spot price behaviour patterns. The paper by Silva and Soares aims at determining to what extent the phenomena of reductions and convergence of prices brought by a liberalised electricity market are apparent in the data available. It uses some statistical tools to assess price convergence and to analyse the extent of market integration, focusing on the measurement of spot price levels in several neighbouring European locations, also to assess the relevance of their respective interconnecting and transmission constraints. The study indicates that, although day-head prices seem to be more convergent within each one of the European markets, they are still far behind the desired integration level.

In deregulated electricity markets the competition among traders is generally intense and very small profit margins are frequently experienced. At the same time, the opportunity arises for traders to exploit the increasing of their profit margins. Coslovich, Pesenti, Piccoli and Ukovich in their paper tackle the problem an electricity trader faces when trying to set and validate his sale prices. The solution approach consists in offering adequate incentives to the customers to encourage them shifting their consumptions to more favourable time periods by introducing adequate price changes. Load redistribution may produce significant savings by reducing the trades in the wholesale market, which is typically less profitable than bilateral contracts. The problem of determining the most judicious prices to offer gives way to a quadratic programming model. The case of an Italian trader is analysed showing that sale price changes may produce savings both for the trader and his customers who are willing and able to shift loads.

The paper by Biberacher considers as case study, a future symbiosis or competition between fusion power and renewable energy sources to meet energy demand, addressing the challenges of future energy systems. The author proposes a modelling environment that combines geographical information systems (GIS) and energy models, taking into account the effects and problems due to the spatial heterogeneity of renewable energy potentials. Geographical factors possess an outstanding importance on renewable energy use (for instance, due to differences in the availability of resources across the globe), and therefore the geographic dimension plays a key role in determining the optimal solution of the future energy system. The energy system model generator TIMES is linked to a GIS software to manage big spatial datasets for studying a future competition and/or coexistence between a high coverage of energy demands by renewable energy potentials and a possible market entrance of fusion power plants. The scenarios developed are devoted to outline the spatial sensitivity in a globally linked energy system.

The combined generation of useful power, heat, cooling, also in combination with the production of other products, is attracting a growing interest in the framework of maximizing overall energy efficiency. In general, district heating pipes allow to distribute hot water or steam, and facilities are chilled from remote cooling generation units through district cooling systems. In a distributed generation environment, heat and cooling can be produced at customer sites, being exploited locally or forwarded to other users. The paper by Chinese aims at highlighting issues arising in the design of district cooling systems combined with district heating (DHC) systems in a distributed generation context. A mixed integer programming model is developed for supporting the decision process in decentralized DHC systems design. Decision to be made involve where to locate conversion facilities, whether a building should act as a heating/cooling supplier/buyer, how to configure the network types, sizes and layout taking into account demand and supply profiles of all participants. The model is applied to two real case studies in Italy, unveiling interdependencies between energy units sizing and network layout definition to find cost-effective solutions.

As the electric power infrastructure incorporates increasingly sophisticated computing and communication technology, aimed at improving the reliability and efficiency of electric power grids, joint simulations of continuous power system models and discrete event models of communication, computation and control operations become essential for understanding the whole system behaviour. This is especially relevant in a context of restructuring and deregulation in the electric power industry that has changed power transmission patterns, and new market pressures are eliminating capacity margins in both transmission and generation. The paper by Nutaro et al. addresses a central concern in modelling and simulating large and complex electric grids and the information infrastructure that monitors and controls them. The authors propose a new approach based on discrete event system specification to the modelling and simulation of hybrid systems as an enabling technology for analysis of modern electric power grids, in the framework of a unified simulation scheme, exploiting the complex interactions between the electric power and digital communication systems. The approach is illustrated with a hybrid model of a smart grid system that aims to prevent under-frequency failures by using an automatic load control scheme.

In deregulated settings commercial transactions between distribution companies, producers, transmission and retail companies, take place on the networks with a reasonable independence of the technical issues of network management. This trend reinforces the need of reliable short-term forecast algorithms, on which load dispatch and network reconfiguration under quality of service constraints, for instance, rely. The paper by Santos, Martins and Pires develops an artificial neural network for next hour load forecast in medium voltage electricity distribution systems, for which the input vector is constructed and uses the strictly necessary instances of the load contiguous values. A concept of trend of consumption is also used, based on two homologous days in the two past adjacent weeks, which is aimed at reducing the use of the time contiguous information.

The economical operation of a power system involves balancing energy production and demand. The unit commitment problem refers to deciding the power units that are on, in each period of a given planning horizon, usually lasting from one day to one or two weeks. The economic dispatch problem involves computing the economical production level of each of those units. In practice, the economical production level of each unit is generally determined disregarding network constraints. This may present drawbacks if the units committed, although being able to fulfil the load requirements, are geographically located in such a way that network constraints prevent them from providing the network with the energy required. A consequence is that additional higher priced units must be committed, different from the computed using the unit commitment algorithm, leading to uneconomical results. The paper by Pereira, Viana, Lucus and Matos solve this problem by using an integrated approach combining the economic dispatch considering network constraints with a unit commitment procedure. For this purpose, a local search based meta-heuristic is used for computing solutions regarding the units committed. An economic dispatch algorithm then works on those good quality solutions considering the geographic location of generators and loads.

Carlos Henggeler Antunes, Álvaro GomesDepartment of Electrical Engineering and Computers, University of Coimbra, Coimbra, PortugalR&D Unit INESC Coimbra, Coimbra, Portugal