Three-phase unbalanced conditions in distribution networks are conventionally caused by load imbalance, asymmetrical fault conditions of transformers and impedances of three phases. The uneven integration of single-phase distributed generation (DG) worsens the imbalance situation. These unbalanced conditions result in financial losses, inefficient utilisation of assets and security risks to the network infrastructure. In this study, a phase-changing soft open point (PC-SOP) is proposed as a new way of connecting soft open points (SOPs) to balance the power flows among three phases by controlling active power and reactive power. Then an operational strategy based on PC-SOPs is presented for three-phase four-wire unbalanced systems. By optimising the regulation of SOPs, optimal energy storage systems dispatch and DG curtailment, the proposed strategy can reduce power losses and three-phase imbalance. Second-order cone programming (SOCP) relaxation is utilised to convert the original non-convex and non-linear model into an SOCP model which can be solved efficiently by commercial solvers. Case studies are conducted on a modified IEEE 34-node three-phase four-wire system and the IEEE 123node test feeder to verify the effectiveness, efficiency and scalability of the proposed PC-SOP concept and its operational strategy.MAX maximum active and maximum reactive powers of DER at node i at time t * conjugate transpose

With the integration of more and more renewable energy generations (REGs), the structure of traditional distribution networks is hard to accommodate the volatile power injections of REGs. As a new power electronic device, soft open point (SOP) can be installed to control both active and reactive power flow among active distribution networks (ADNs). This paper presents a comprehensive optimization method for allocating SOPs within an ADN with high penetration of REGs. In order to find proper SOP candidate locations, a selection strategy based on two technical indices is proposed. To mitigate the risk of voltage violation caused by REG forecast errors and improve the adaptiveness of allocation results, a two-stage robust optimization model for SOP allocation is formulated to minimize the total cost of SOP investment and network operation. The proposed model is converted into a mixed-integer second-order cone programming (MISCOP) problem, which is then decoupled into a master problem of planning and a subproblem of operation and solved by column and constraint generation (CCG) algorithm. Simulation results show that the proposed method can effectively find the optimal SOP allocation schemes. Comparisons with different mathematical formulation and solution methods show the advantages of the proposed method.

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There is a growing interest from owners of distributed energy resources (DERs) to actively participate in the energy market through peer-to-peer (P2P) energy trading. Many strategies have been proposed to base P2P energy trading on. However, in those schemes neither the costs of assets usage nor the losses incurred are so far taken into account. This paper presents a transaction-oriented dynamic power flow tracing (PFT) platform for distribution networks (DNs) implemented in a geographic information system (GIS) environment. It introduces a new transaction model that quantifies the use of the DN, apportions the losses and unlocks a flexible use of the surplus generation enabling that prosumers can adopt simultaneously different mechanisms for participation in energy trading, maximizing renewable energy usage. The platform is also helpful for future distribution system operators (DSOs) to overcome the status invisibility of low voltage (LV) DNs, determine who makes use of the assets, debit the losses on them and explore the effects from new connections. A case study is conducted over the IEEE European LV Test Feeder. The tool provides a clear, intuitive, temporal and spatial assessment of the network operation and the resulting power transactions, including losses share and efficiency of DERs.