In the current era of sustainable development, energy planning has become complex due to the involvement of multiple benchmarks like technical, social, economic and environmental. This in turn puts major constraints for decision makers to optimize energy alternatives independently and discretely especially in case of rural communities. In addition, topographical limitations concerning renewable energy systems which are mostly distributed in nature, the energy planning becomes more complicated. In such cases, decision analysis plays a vital role for designing such systems by considering various criteria and objectives even at disintegrated levels of electrification. Multiple criteria decision making (MCDM) is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. This tool is becoming popular in the field of energy planning due to the flexibility it provides to the decision makers to take decisions while considering all the criteria and objectives simultaneously. This article develops an insight into various MCDM techniques, progress made by considering renewable energy applications over MCDM methods and future prospects in this area. An extensive review in the sphere of sustainable energy has been performed by utilizing MCDM technique.

A review of multi criteria decision making (MCDM) towards sustainable renewable energy development

Power networks are undergoing a fundamental transition, with traditionally passive consumers becoming ‘prosumers’ — proactive consumers with distributed energy resources, actively managing their consumption, production and storage of energy. A key question that remains unresolved is: how can we incentivize coordination between vast numbers of distributed energy resources, each with different owners and characteristics? Virtual power plants and peer-to-peer (P2P) energy trading offer different sources of value to prosumers and the power network, and have been proposed as different potential structures for future prosumer electricity markets. In this Perspective, we argue they can be combined to capture the benefits of both. We thus propose the concept of the federated power plant, a virtual power plant formed through P2P transactions between self-organizing prosumers. This addresses social, institutional and economic issues faced by top-down strategies for coordinating virtual power plants, while unlocking additional value for P2P energy trading. The rise of prosumers has led to creation of virtual power plants and peer-to-peer trading to help manage a diverse and distributed array of energy sources. This Perspective proposes the federated power plant, which combines these concepts to meet some of their individual challenges and offer new value.

/pdf/using-peer-to-peer-energy-trading-platforms-to-incentivize-3yjh4qppz5.pdf

Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants

https://ir.cwi.nl/pub/30568/1-s2.0-S096014811831231X-main.pdf

Machine learning methods for wind turbine condition monitoring: A review

As the demand for wind energy continues to grow at exponential rates, reducing operation and maintenance (OM) costs and improving reliability have become top priorities in wind turbine (WT) maintenance strategies. In addition to the development of more highly evolved WT designs intended to improve availability, the application of reliable and cost-effective condition-monitoring (CM) techniques offers an efficient approach to achieve this goal. This paper provides a general review and classification of wind turbine condition monitoring (WTCM) methods and techniques with a focus on trends and future challenges. After highlighting the relevant CM, diagnosis, and maintenance analysis, this work outlines the relationship between these concepts and related theories, and examines new trends and future challenges in the WTCM industry. Interesting insights from this research are used to point out strengths and weaknesses in today’s WTCM industry and define research priorities needed for the industry to meet the challenges in wind industry technological evolution and market growth.

/pdf/wind-turbine-condition-monitoring-state-of-the-art-review-29t23u97yb.pdf

Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges

The wind turbine power curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for modeling of wind turbine power curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric modeling techniques and critically evaluates them. The areas of further research have also been presented.

A comprehensive review on wind turbine power curve modeling techniques

Active Network Management is a philosophy for the operation of distribution networks with high penetrations of renewable distributed generation. Technologies such as energy storage and flexible demand are now beginning to be included in Active Network Management (ANM) schemes. Optimizing the operation of these schemes requires consideration of inter-temporal linkages as well as network power flow effects. Network effects are included in optimal power flow (OPF) solutions but this only optimizes for a single point in time. Dynamic optimal power flow (DOPF) is an extension of OPF to cover multiple time periods. This paper reviews the generic formulation of DOPF before developing a framework for modeling energy technologies with inter-temporal characteristics in an ANM context. The framework includes the optimization of nonfirm connected generation, principles of access for nonfirm generators, energy storage, and flexible demand. Two objectives based on maximizing export and revenue are developed and a case study is used to illustrate the technique. Results show that DOPF is able to successfully schedule these energy technologies. DOPF schedules energy storage and flexible demand to reduce generator curtailment significantly in the case study. Finally, the role of DOPF in analyzing ANM schemes is discussed with reference to extending the optimization framework to include other technologies and objectives.

/pdf/dynamic-optimal-power-flow-for-active-distribution-networks-1oey063vs7.pdf

Dynamic Optimal Power Flow for Active Distribution Networks

Power curves constructed from wind speed and active power output measurements provide an established method of analyzing wind turbine performance. In this paper, it is proposed that operational data from wind turbines are used to estimate bivariate probability distribution functions representing the power curve of existing turbines so that deviations from expected behavior can be detected. Owing to the complex form of dependency between active power and wind speed, which no classical parameterized distribution can approximate, the application of empirical copulas is proposed; the statistical theory of copulas allows the distribution form of marginal distributions of wind speed and power to be expressed separately from information about the dependency between them. Copula analysis is discussed in terms of its likely usefulness in wind turbine condition monitoring, particularly in early recognition of incipient faults such as blade degradation, yaw, and pitch errors.

/pdf/wind-turbine-condition-assessment-through-power-curve-copula-35lqgt2x53.pdf

Wind Turbine Condition Assessment Through Power Curve Copula Modeling

Delivering a highly distributed electricity system: technical, regulatory and policy challenges

The European Internal Energy Market aims to promote trade and competition in electricity generation across the EU, with investment signals for new generation capacity and interconnection coming from zonal electricity prices reflecting scarcity value. However, a growing number of EU Member States have implemented national Capacity Mechanisms in order to ensure future security of supply within their own borders, which may distort the cross-border trade of energy. This local view of energy security is in response to internal technical and economic constraints and a perceived inability of cross-border electricity flows to be a reliable source of capacity at times of maximum stress, in favour of self-sufficiency. A number of routes are available to resolve this conflict through permitting cross-border participation of generators in local Capacity Mechanisms, but this requires resolution of a number of complicating factors, not least a means for properly allocating transmission capacity without introducing further distortions to the energy market. Alternative solutions could be enacted at an EU-level, such as through the alignment of Capacity Mechanisms to a common model, or the introduction of an EU-wide single Capacity Mechanism, but the current regulatory focus appears to remain on resolution of such issues at a national level.

/pdf/electricity-security-in-the-european-union-the-conflict-3d1hnazgzs.pdf

Electricity security in the European Union - the conflict between national Capacity Mechanisms and the Single Market

The connection of high penetrations of renewable generation such as wind to distribution networks requires new active management techniques. Curtailing distributed generation during periods of network congestion allows for a higher penetration of distributed wind to connect, however, it reduces the potential revenue from these wind turbines. Energy storage can be used to alleviate this and the store can also be used to carry out other tasks such as trading on an electricity spot market, a mode of operation known as arbitrage. The combination of available revenue streams is crucial in the financial viability of energy storage. This study presents a heuristic algorithm for the optimisation of revenue generated by an energy storage unit working with two revenue streams: generation-curtailment reduction and arbitrage. The algorithm is used to demonstrate the ability of storage to generate revenue and to reduce generation curtailment for two case study networks. Studies carried out include a single wind farm and multiple wind farms connected under a ‘last-in-first-out’ principle of access. The results clearly show that storage using both operating modes increases revenue over either mode individually. Moreover, energy storage is shown to be effective at reducing curtailment while increasing the utilisation of circuits linking the distribution and transmission networks. Finally, renewable subsidies are considered as a potential third revenue stream. It is interesting to note that under current market agreements such subsidies have the potential to perversely encourage the installation of inefficient storage technologies, because of increased losses facilitating greater “utilisation” of renewable generation.

/pdf/maximising-revenue-for-non-firm-distributed-wind-generation-36w62hsljj.pdf

Simon Gill

Papers

Dynamic Optimal Power Flow for Active Distribution Networks

Wind Turbine Condition Assessment Through Power Curve Copula Modeling

Delivering a highly distributed electricity system: technical, regulatory and policy challenges

Electricity security in the European Union - the conflict between national Capacity Mechanisms and the Single Market

Maximising revenue for non-firm distributed wind generation with energy storage in an active management scheme