مدل های کسب و کار برای مولدهای پراکنده در یک محیط بازار آزاد
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7542||2007||11 صفحه PDF||سفارش دهید||6591 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Electric Power Systems Research, Volume 77, Issue 9, July 2007, Pages 1178–1188
The analysis of the potential of emerging innovative technologies calls for a systems-theoretic approach that takes into account technical as well as socio-economic factors. This paper reports the main findings of several business case studies of different future applications in various countries of distributed power generation technologies, all based on a common methodology for networked business modeling and analysis.
The successful introduction into society of innovative technologies generally depends on a wide variety of technological as well as socio-economic factors . Accordingly, there is a consensus now in many areas of complex systems engineering that requirements specification and analysis should take into account both technical and business requirements , ,  and . Emerging distributed power generation technologies, variously referred to as distributed generation (DG) or distributed energy resources (DER), are no exception to this rule. The analysis of their future potential calls for a systems-theoretical approach that involves analysis of their general technical characteristics , consideration of the broader strategic contexts and scenarios in which technologies will function  and , and of the business models  that are to make innovative technologies economically sustainable beyond their research and development stage. The contribution of this paper is to consider the economic side of the introduction of new DG technologies, by investigating business requirements and models for different forms and applications of DG. Like many industries, the power and utility sector is no longer characterized by a linear value chain —from generation, transmission, and distribution to the final customer. Instead, value chains are now becoming more complex value constellations in which enterprises are collaborating and competing in networks  and . In the power sector, this is caused by a combination of factors, including the steady progress of distributed generation technologies, the increasing penetration of advanced information and communication systems and technologies (that, like the Internet and Web, are usually also distributed and tend to lead to decentralization) to manage an increasingly complex grid, and on top of this the ongoing industry restructuring and market liberalization in many countries. As a result, DG technologies must be economically analyzed in terms of networked business models that are sustainable in a liberalized market environment. We have developed a systematic methodology for constructing and assessing such new networked business models , , ,  and , called BusMod, and applied this to a number of different case studies and scenarios where DG technologies may be successfully applied in the future. The present paper discusses the key findings of these studies, which cover the economic potential of DG for dynamic demand response at peak hours packaged as a new business service, the market feasibility of small-scale local producers of renewable power, the usage of DG in grid balancing services, and in the active management of distribution networks. In Sections 2, 2.1, 2.2, 2.3, 3, 3.1, 3.2, 3.3, 4, 4.1, 4.2, 4.3 and 5, we present the major, qualitative and quantitative, results from four different case studies on DG business models from, respectively, Spain, Norway, The Netherlands and the United Kingdom. In Section 6, we outline some of the methodological background of the employed BusMod methodology for networked business modeling and analysis. Section 7 summarizes the key socio-economic conclusions for DG and some suggestions for further research.
نتیجه گیری انگلیسی
This paper has systematically investigated different case studies for DG business models that are sustainable in a liberalized market environment. These studies focused on the situation of different countries and highlighted the potential of various novel business ideas. Key findings are: • In a competitive market, the electricity bill that a customer has to pay can be reduced significantly by shifting part of the demand to low price periods. Demand response services may reduce the electricity bill of a final customer with DG capacity by over 15%. • Under current market and regulatory conditions, a demand shifting service should not be independently positioned as a key income source; revenue derives from a well-designed bundle of services (cf. also ref. ). • The small-scale Local Producer business model for renewable DG is profitable for all actors involved—even when changes in the network tariffs occur. • Due to deregulation, massive reserve power generation capacity is decreasing in many countries. This creates new business opportunities for DG. • DG has a strong potential to play a role in future distributed grid balancing services, for instance via CHP employed in horticulture, and in active management of distribution networks. Our studies have revealed some economic factors that seem to be more generally valid across different case studies: 1. The business case for DG generally improves if local DG producers are able to sell and trade directly on a power exchange market. 2. An important and general finding is that regulatory policies directly impact the feasibility and attractiveness of DG business models. Whatever its specific nature, a stable regulatory framework must be in place: regulatory certainty increases market confidence in long-term commercial viability of new business models. These results indicate some interesting future research lines for studies in this domain: (1) the modeling of the design and interplay of regulatory frameworks with new business models for DG and other technologies and (2) the role of future retail and market aggregators for DG/DER, and their relation to emerging concepts such as virtual power plants.