Browsing by Author "Zhou, Yue"

Now showing 1 - 4 of 4
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    Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community
    (Elsevier, 2020-08-28) Zhou, Yue; Wu, Jianzhong; Song, Guanyu; Long, Chao
    As an innovative paradigm for electric power systems with a high penetration of distributed energy resources, peer-to-peer (P2P) energy trading enables direct energy trading between end customers, which is able to facilitate local power and energy balance and potentially support the operation of bulk power systems. In this paper, a framework was proposed to enable ancillary service provision from a P2P energy trading community, creating additional value for both customers in the community and power systems. Specifically, an ancillary service provision mechanism was designed along with P2P energy trading and residual balancing mechanisms to enable the power utility to obtain ancillary service from customers in a P2P energy trading community. Furthermore, the optimal bidding strategy of customers was figured out to maximize their benefits in the proposed mechanisms. Simulation studies were conducted based on a residential community in Great Britain. The results show that the proposed ancillary service mechanism can enable the power utility to obtain a significant or required amount of ancillary services of different types. The proposed mechanisms and optimal bidding strategy can achieve Pareto improvement for the revenue of each customer and result in significantly higher social welfare for the whole community. It is also revealed that increasing ancillary service prices and installation rate of electric vehicles can increase the total amount of ancillary service provision and thus bring higher revenue for the customers in the community. By contrast, increasing installation of PV systems does not necessarily increase the amount of service provision
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    Residential community with PV and batteries: reserve provision under grid constraints
    (Elsevier, 2020-02-03) Alnaser, Sahban W.; Althaher, Sereen Z.; Long, Chao; Zhou, Yue; Wu, Jianzhong
    Technological advances in residential-scale batteries are paving the way towards self-sufficient communities to make the most use of their photovoltaic systems to support local energy consumption needs. To effectively utilize capabilities of batteries, the community can participate in the provision of short term operating reserve (STOR) services. To do so, adequate energy reserves in batteries are maintained during prescribed time windows to be utilized by electricity system operators. However, this may reduce energy sufficiency of the community. Further, the actual delivery of reserve could create distribution network congestions. To adequately understand the capability of a community to provide reserve, this work proposed a residential community energy management system formulated as a Mixed-Integer Linear Programming (MILP) model. This model aims to maximize energy sufficiency by optimal scheduling of batteries whilst considering reserve constraints. The model also maintains the aggregate power of houses within export/import limits that are defined offline using an iterative approach to ensure that the reserve provision does not breach distribution network constraints. The model is demonstrated on a residential community. The maximum committed reserve power with minimal impact on energy sufficiency is determined. Results also show that the capability of a community to provide reserve could be overestimated unless distribution network constraints are adequately considered.
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    Transactive energy system for distribution network management: procuring residential flexibility services under dynamic pricing
    (IEEE, 2022-09-22) Althaher, Sereen Z.; Alnaser, Sahban W.; Zhou, Yue; Long, Chao
    The formulation of dynamic pricing is one of the emerging solutions to guide residential demand for the benefits of the bulk power system. However, the schedule of residential demand in response to time-differentiated energy prices could cause congestions in distribution networks at both the lowest-price and highest-price time intervals. To enable the adoption of dynamic pricing, this work presents a novel framework to manage the constraints of distribution networks based on the concept of Transactive Energy System (TES). The TES-based framework produces incentives during network issues to unlock customers’ flexibility services to reschedule controllable assets (e.g., batteries). By running Home Energy Management Systems (HEMS), the flexibility of customers to modify schedules are quantified against predefined set of incentives. For each incentive, the amounts of net-demand change per customer are aggregated and submitted through aggregators to the Distribution System Operator (DSO) in the forms of both generation offers (reducing demand) and demand offers (increasing demand). The latter are crucial to cater for generation-driven network issues. The resulting aggregators’ staircase bidding curves are embedded to an advanced Optimal Power Flow (OPF) model to identify the successful offers to manage network constraints whilst minimizing incentives paid to aggregators. This allows defining incentives and quantities directly without extensive iterations between DSO and aggregators. The application of the framework to an urban 11kV feeder shows its effectiveness to manage congestions. Further, the highly variations in dynamic prices increase the amounts of incentives particularly when flexibility services are requested at evening and night time intervals.
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    Transition towards solar Photovoltaic Self-Consumption policies with Batteries: from the perspective of distribution networks
    (Elsevier, 2021-10-05) Alnaser, Sahban W.; Althaher, Sereen Z.; Long, Chao; Zhou, Yue; Wu, Jianzhong; Hamdan, Reem
    The transition towards low-carbon energy systems requires increasing the contribution of residential Photovoltaic (PV) in the energy consumption needs (i.e., PV self-consumption). For this purpose, the adoption of PV self-consumption policies as alternatives to the current net-metering policy may support harnessing batteries to improve PV self-consumption. However, the technical impacts of PV policies on distribution networks have to be adequately assessed and mitigated. To do so, a two-stage planning framework is proposed. The first stage is an optimization approach that determines the best sizes of PV and batteries based on the adopted PV policy. The second stage assesses the impacts of the resulting sizes on distribution networks using Monte-Carlo simulations to cope with uncertainties in demand and generation. The framework is applied on real medium and low voltage distribution networks from the south of Jordan. For the net-metering, the results show that the uptake of residential PV penetration above 40% will result in voltage issues. It is also found that the adoption of batteries for the benefits of customers (i.e., reduce electricity bills) will not mitigate the PV impacts for PV penetration above 60%. Further, the results demonstrate the important role of distribution network operators to manage the uptake of batteries for the benefits of customers and distribution networks. Network operators can support customers to adopt larger sizes of batteries to achieve the desired PV self-consumption in return of controlling the batteries to solve network issues. This facilitates the uptake of 100% PV penetration and improves PV self-consumption to 50%.