Sustainability and reliability assessment of microgrids in a regional electricity market
Introduction
A MG (microgrid) is a localized grouping of electric and thermal loads, generation and storage that can operate in parallel with the grid or in island mode and can be supplied by renewable and/or fossil-fueled distributed generation. We quantify the sustainability and reliability of MGs in a regional power market in terms of multiple indices for the regional grid. The setting is the Northwestern European electricity market (Belgium, France, Germany and the Netherlands). This is a regional network whose national markets already influence each other strongly and have taken steps to integrate even further into a single market. Since 2006, for example, the Netherlands, France and Belgium have coupled their electricity exchanges through the TLC (Trilateral Market Coupling), ensuring the convergence of spot electricity prices in the three countries. In November 2010, the TLC was replaced by the CWE (Central Western European Market Coupling), which also includes Germany [1], [2].
Sustainable development is often defined as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [3]. Translating this definition into quantifiable criteria that can be used to compare alternative power systems has proven difficult. For this reason, several authors have adopted a multi-criteria (or multiple objective) approach. The function of multi-criteria analysis is to communicate tradeoffs among conflicting criteria and to help users quantify and apply value judgments in order to recommend a course of action [4]. In this manner, a range of dimensions of sustainability can be considered, while allowing stakeholder groups to have different priorities among the criteria. This method has been used, for example, to assess the tradeoffs in power system planning [5] and to evaluate the sustainability of power generation [6].
The main contribution of this paper is the quantification of the sustainability and reliability of alternative power generation paths in a regional system with a diverse set of metrics. We explicitly simulate the impacts of a generation investment decision on operations and investment elsewhere in the grid, as evaluation of the net sustainability impacts of a decision should consider how a given investment choice propagates through the system. Our approach does not rely on multi-objective optimization; it presents instead a multi-criteria assessment through the use of indicators, which are calculated based on the results of a single-objective optimization model and a reliability model.
Among the commonly used four dimensions to evaluate the sustainability of energy supply systems (social, economic, technical and environmental) [7], the analysis emphasizes the latter three. In terms of microgrid impact on social sustainability, several areas commonly cited as important are equity, community impacts, level of participation in decision making and health impacts. The first three depend on how a given microgrid is owned and managed. In general, it is plausible that the increased impact that members of the microgrid-served population could have on ownership and management decisions, relative to populations served by conventional utilities, would count as a positive impact on social sustainability. Additionally, shared community values may lead some stakeholders to value microgrids that use renewable energy more highly than either microgrids that do not or larger systems in which the community has little choice about the source of electricity [8]. Increased security of supply associated with microgrids may also offer social as well as economic benefits within and outside the community served by a microgrid. Finally, microgrid operation may create jobs that offer social sustainability gains for the local community.
On the other hand, microgrids may have negative effects on residents’ quality of life, if they increase the level of noise or have aesthetic impacts on the landscape [9]. Health impacts of a microgrid may also be negative, as microgrids are likely to have generation and thus pollution closer to the populations they serve than conventional distribution networks. How risks to life and health associated with local air pollution compare with the ones from a conventional utility source will be very population, site and technology specific.
While we can speculate on the likely direction of these impacts for the power system modeled in this paper, it is difficult to quantify them without reference to a specific location and population whose views and willingness to pay can be surveyed or estimated. The methodology used in our analysis aims at assessing the broader impacts of alternative power generation paths on a regional power system. For this reason, no direct quantification of social sustainability is offered in our study. However, to account indirectly for this dimension we perform a sensitivity analysis on the results in order to assess whether and how the introduction of a social sustainability index would alter our conclusions.
We consider six alternative scenarios for satisfying the electric power and thermal needs of a regional power market, and we characterize their sustainability and reliability using four sets of indicators. The scenarios are various combinations of microgrid implementation (with and without MGs), microgrid generating mix (fossil-fueled only, or fossil-fueled and renewable) and CO2 policies (with and without a price on CO2 emission allowances). The first set of indices is based on CO2 and conventional air pollutant emissions (NOx and SOx). The second one emphasizes economic sustainability in terms of total generation costs [10] and accounts for externalities of electricity generation. Externalities can be defined as “the costs and benefits which arise when the social or economic activities of one group of people have an impact on another, and when the first group fails to fully account for their impacts” [11]. In the 1990s the importance of environmental costs as an input to the planning and decision processes of electric power generation systems was recognized in several studies [12], [13]. The third set of indices is based on thermodynamic energy and exergy based efficiencies, while the fourth considers effects on bulk power system reliability.
Economic and environmental analyses of power systems including distributed generation are common (see, for example [14], [15]). Several studies assess the potential benefits of distributed generation [16], [17] and evaluate its impact on sustainable development [18]. Others focus directly on the economic and regulatory issues of MG implementation [19], on the implications of environmental regulation on MG adoption [20], and on the improvement in power reliability provided to different types of buildings by the installation of a MG [21]. In contrast, neither thermodynamic analyses considering the interaction of MGs with existing regional power systems nor the effect of MG deployment on system reliability have been previously published, to the best of our knowledge.
We include exergy because an analysis relying on first law efficiency alone does not consider to what degree the outputs of a power plant are useful. For example, electricity is more valuable than steam, one of the typical by-products of power production, because the latter is characterized on a per unit energy basis by a lower value of exergy than electricity. Therefore, not all outputs should be valued in the same way: outputs having a higher quality or exergy per unit energy (like electricity) should have a higher unit price than those having a lower quality or exergy per unit energy (like steam) because the former possess a greater ability to do work. In contrast, when the second law of thermodynamics is disregarded, the difference in quality of the various energy outputs is not considered and cannot be effectively compared for different energy conversion processes.
Thus, the use of exergy-based indicators can help decision makers to improve the effectiveness of energy resource use in a given system. Such indicators have been widely adopted in the sustainability literature. Yi et al. [22] use thermodynamic indices to assess the sustainability of industrial processes. Frangopoulos and Keramioti [23] evaluate the performance of different alternatives to meet the energy needs of an industrial unit, taking into account several aspects of sustainability. von Spakovsky and Frangopoulos [24], [25] use an environomic (thermodynamic, environmental and economic) objective for the analysis and optimization of a gas turbine cycle with cogeneration. Rosen [26] presents a thermodynamic comparison of a coal and a nuclear power plant on the basis of exergy and energy. Zvolinschi et al. [27] develop three exergy-based indices to assess the sustainability of power generation in Norway.
In addition to sustainability, it is important to incorporate a reliability analysis in the decision process because of the positive impact that microgrids may have on power system reliability, and thereby on promoting their deployment. Therefore, we add reliability to our suite of indices and quantify it using the annual LOLP (Loss of Load Probability) and ELOE (Expected Loss of Energy) [28], [29]. The reliability of a power system is the probability that the system is able to perform its intended function (generation meets load), under a contractual quality of service, for a specified period of time. Reliability is quantified here using the concept of “long-run average availability” of the bulk power system (supply-demand balance), without consideration of dynamic system response to disturbances, which instead is the concept of “security” [30].
We do not consider aspects of power quality that may also be controlled within MGs. It has been argued that microgrids have the potential to deliver different degrees of power quality tailored for different customers’ needs, as they may be employed to control power quality locally according to customers’ requirements. This may prove to be more beneficial than providing a uniform level of quality and service to all customers without differentiating among their needs [31], [32]. However, the way in which microgrids may affect power quality in a regional grid is still under study and there are no definitive results. For this reason, we do not include power quality considerations in our analysis, though we note they should be addressed in future research.
We also do not consider customer outages arising at the sub-transmission or distribution-level. However, it is worth noting that the majority of power interruptions experienced by customers in the countries we consider are not due to large events at the bulk level, but to more localized ones affecting the distribution system [33].
Section 2 describes our modeling approach, data and assumptions concerning alternative power systems (with and without MGs) and CO2 policies. Section 3 presents the six scenarios considered in our analysis to satisfy the electric power and thermal needs of the Northwestern European electricity market. Section 4 describes the indicators chosen in this paper to assess the sustainability and reliability of the network. Section 5 discusses the results of the analysis, while Section 6 concludes.
Section snippets
Methodology and data
Two different models are used to quantify our indices. A regional power market model based on linear optimization methods [10], [34] provides the information necessary for the economic, environmental and thermodynamic indices; the model is presented in Section 2.1. A local reliability model based on convolution methods [28], [29], described in Section 2.2, is used to obtain the reliability indices.
Description of the scenarios
We consider six alternative scenarios to satisfy the electric power and thermal needs of the Northwestern European electricity market. In every scenario we simulate six representative hours, one for each block defined in Section 2.1.2. Annual results are obtained by averaging the hourly results by the number of hours in each block. The scenarios can be described as follows.
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Scenario 1: no MG, no CO2 price. This scenario assumes that no MGs operate in the Northwestern European power market and
Indicators
We chose our indicators based on [23] to assess different aspects of economic, technical and environmental sustainability. We also include two indicators commonly used in the literature to measure power system adequacy [28]. The indicators are classified into four groups.
Results
The indicators are calculated based on the results of the optimization problem and the reliability valuation model described above. Indicator values for each scenario are shown in Table 8, Table 9. To analyze the trend of the emissions from power generation alone, we disregard the CO2 and NOx emissions of the boilers, as well as the estimated life-cycle emissions of nuclear, coal and natural gas plants (Table 10).
Conclusions
This paper assesses the sustainability and reliability of microgrids in the Northwestern European electricity market. Results suggest that a power network in which fossil-fueled microgrids and a price on CO2 emissions are included achieves the highest composite sustainability.
From an environmental point of view, the scenarios including fossil-fueled MGs are more sustainable than the ones where no microgrids are present, because they yield a reduction in total pollutant emissions. However, some
Acknowledgements
Funding for this research was provided by the National Science Foundation under NSF-EFRI grant 0835879. The authors gratefully acknowledge useful comments by two anonymous referees. Opinions and errors are the responsibility of the authors.
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