Review of existing peer-to-peer energy trading projects

Peer-to-Peer (P2P) energy trading is a novel paradigm of power system operation, where people can generate their own energy from Renewable Energy Sources (RESs) in dwellings, offices and factories, and share it with each other locally. The number of projects and trails in this area has significantly increased recently all around the world. This paper elaborates main focuses and outcomes of those projects, and compares their similarities and differences. The results show that although many of the trails focus on the business models acting similarly to a supplier's role in the electricity sector, it is also necessary to design the necessary communication and control networks that could enable P2P energy trading in or among local Microgrids

A bidding system for peer-to-peer energy trading in a grid-connected microgrid

Peer-to-Peer (P2P) energy trading is a novel paradigm of power system operation, where people can generate their own energy from Renewable Energy Sources (RESs) in dwellings, offices and factories, and share it with each other locally. An architecture model was proposed to present the design and interoperability aspects of components for P2P energy trading in a microgrid. A specific Customer-to-Customer business model was introduced in a benchmark grid-connected microgrid based on the architecture model. The core component of a bidding system, called Elecbay, was also proposed and simulated using game theory. Test results show that P2P energy trading is able to balance local generation and demand, therefore, has a potential to enable a large penetration of RESs in the power grid

Performance evaluation of peer-to-peer energy sharing models

With the increasing installation of distributed generation at the demand side, an increasing number of consumers become prosumers, and many peer-to-peer (P2P) energy sharing models have been proposed to reduce the energy bill of the prosumers through stimulating energy sharing and demand response. In this paper, a three-stage evaluation methodology is proposed to assess the economic performance of P2P energy sharing models. First of all, joint and individual optimization are established to identify the value contained in the energy sharing region. The overall energy bill of the prosumer population is then estimated through an agent-based modelling with reinforcement learning for each prosumer. Finally, a performance index is defined to quantify the economic performance of P2P energy sharing models. Simulation results verify the effectiveness of the proposed evaluation methodology, and compare three existing P2P energy sharing models in a variety of electricity pricing environments

Feasibility of peer-to-peer energy trading in low voltage electrical distribution networks

Peer-to-peer (P2P) energy trading is referred to as flexible energy trades between peers, where the excessive energy from many small-scale Distributed Energy Resources (DERs) including those in dwellings, offices, factories, etc., is traded among local customers. To assess the feasibility of P2P energy trading, where local electricity demand and supply balancing is desired, a so-called P2P index was developed. By clustering the historical smart metering data using the k-means method, customers were categorized by their electricity consumption patterns and representative demand profiles of low voltage electrical distribution networks were produced. A linear programming optimization was carried out to find the optimal capacity of different DERs to maximize the local demand and supply balancing. PV systems and combined heat and power units were considered as the renewable resources. This work provides network planners with guidelines of appropriate shares of DERs for better constructing their future networks, and facilitates a P2P energy trading market paradigm

Peer-to-peer energy trading in a microgrid

Peer-to-Peer (P2P) energy trading describes flexible energy trades between peers, where the excess energy from many small-scale Distributed Energy Resources (DERs) is traded among local customers. The feasibility of applying P2P energy trading to reduce costs for energy consumers, and to increase income for DER producers in a community microgrid was investigated. Three representative market paradigms were proposed, i.e. bill sharing, mid-market rate and an auction based pricing strategy. Each of them specified detailed business models, local energy exchange prices, as well as quantified individual customer's energy costs. An example of each methodology applied to a residential community microgrid with PV systems, validated the effectiveness of the proposed P2P trading mechanisms and identified the benefits

Unraveling the Impact of Phosphorus, Inorganic Carbon and Different Nitrogen Sources on the Structure, Function and Activity of Mixed Nitrifying Microbial Communities

The discovery of bacteria capable of complete ammonia oxidation (CMX) has challenged the long-held perspective of labor division between ammonia oxidizing microorganisms and nitrite oxidizing microorganisms. CMX were found to ubiquitously exist in natural and engineered environments, and co-exist with canonical ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA), and nitrite-oxidizing bacteria (NOB). However, the factors affecting the niche separation between CMX and canonical nitrifiers are not well understood. More CMX pure cultures and enrichments are needed to investigate the biokinetics of CMX. Many studies on CMX focused on the existence and abundance of CMX across diverse environments, but rarely investigated the activity of CMX and the interactions between CMX and canonical nitrifiers. This dissertation therefore had the following objectives: (1) To determine if phosphorus (P), inorganic carbon (IC) and nitrogen sources are factors driving the niche separation of CMX and canonical nitrifiers; (2) To understand the responses of mixed nitrifying communities under different P, IC loadings and nitrogen sources; and (3) To investigate the interactions between CMX and ammonia oxidizers, and between CMX and nitrite oxidizers.Firstly, CMX are more competitive under a P-excess condition. An increased proportion of CMX, and decreased proportion of AOB were observed upon switching from P-limited to P-excess condition. The major CMX species found in the P-limited condition was similar to that found in the P-excess condition. The mixed culture community upregulated the CMX pathway related to ammonia oxidation, nitrite oxidation, carbon dioxide (CO2) fixation, and the electron transport chain (ETC) after switching to P-excess from P-limited condition. On the contrary, the mixed culture community downregulated the AOB pathway related to ammonia oxidation CO₂ fixation, and the ETC under P-excess condition. The mixed culture community downregulated the NOB pathway related to nitrite oxidation, CO₂ fixation, and the ETC under P-excess condition. Collaboration between CMX and NOB under P-excess condition to achieve complete nitrification performance was observed showing that CMX provided nitrite to support NOB metabolism. These Findings support the possibility of incorporating CMX, as nitrite producer, into a partial nitrification process. Secondly, CMX were successfully enriched in a lab-scale reactor using urea as nitrogen source. A higher proportion of CMX was retained in the reactor fed with urea, as compared to the reactor fed with ammonia as nitrogen source. The nitrogen source is a factor driving the niche separation of different AOB and CMX species, including the observation that the major CMX and AOB species found in the urea-fed reactor were different from that in the ammonia-fed reactor. The CMX enrichment can be used to expand our understanding of the CMX biokinetic, stoichiometric and thermodynamic coefficients. Thirdly, AOB were found to outcompete CMX under low IC conditions, regardless of influent ammonia loading. In response to the low IC loading, the mixed culture community upregulated AOB pathway related to ammonia oxidation, CO₂ fixation and the ETC. On the contrary, the mixed culture community downregulated CMX pathway related to ammonia oxidation, nitrite oxidation, CO₂ fixation and the ETC in response to the low IC loading. Nitrite oxidation pathway by NOB was upregulated, while NOB pathway related to CO₂ fixation and the ETC were downregulated in the mixed culture community in response to the low IC loading. Fourthly, proliferation of CMX Nitrospira could be promoted with simultaneous co-feeding of ammonia and nitrite. In response to nitrite addition in the influent, the nitrite oxidation pathway by CMX and NOB in the mixed nitrifying community was upregulated, while the ammonia oxidation pathway by AOB was unchanged, and by CMX was downregulated. These results suggest that CMX may deteriorate the performance of energy-efficient BNR systems, such as shortcut nitrification-denitrification and partial nitritation-anammox, by contributing more to nitrite oxidation than to ammonia oxidation. In summary, this dissertation improves our understanding on the ecophysiology on the CMX and canonical nitrifiers. The results from this study can guide the enrichment of CMX to fully appreciate positive gains possible by enhancing the CMX ecophysiology. This dissertation, by applying metagenomics and metatranscriptomics, is one of the rare studies focusing on the overall system-wide responses of the mixed culture community to different conditions, rather than focusing on a single microorganism in relation to these varying conditions

Combining local features for robust nose location in 3D facial data

Due to the wide use of human face images, it is significant to locate facial feature points. In this paper, we focus on 3D facial data and propose a novel method to solve a specific problem, i.e., locating the nose tip by one hierarchical filtering scheme combining local features. Based on the detected nose tip, we further estimate the nose ridge by a newly defined curve, the Included Angle Curve (IAC). The key features of our method are its automated implementation for detection, its ability to deal with noisy and incomplete input data, its invariance to rotation and translation, and its adaptability to different resolutions. The experimental results from different databases show the robustness and feasibility of the proposed method. (c) 2006 Elsevier B.V. All rights reserved