There is a significant gap between academic research and practical application for power distribution system planning (PDSP). For most of the existing PDSP models in academic research, cost is used ...as the objective function, and the most common constraints are power flow equality constraints, bus voltage or voltage drop limits, substation and feeder capacity limits, etc. Although various advanced models and methods have been proposed, they are rarely used in real distribution system companies. This paper proposes a new feeder planning model for the urban distribution network considering various practical requirements. According to field investigation, "supply electricity to loads using nearby power sources" is used as the objective, and it is analytically expressed by load moment. Block loads, practical street layout, meshed network configuration, connection mode of feeders, non-crossing requirement of feeders, power supply radius, etc., are all respected and embedded in the model. The proposed model is recast as a mixed integer linear programming (MILP) problem, and it can be solved by the state-of-art commercial solver. The effectiveness and validity of the proposed model are illustrated on a 9-block test system and a real 22-block district distribution system.
The increase in distributed energy resources and flexible electricity consumers has turned TSO-DSO coordination strategies into a challenging problem. Existing decomposition/decentralized methods ...apply divide-and-conquer strategies to trim down the computational burden of this complex problem, but rely on access to proprietary information or fail-safe real-time communication infrastructures. To overcome these drawbacks, we propose in this paper a TSO-DSO coordination strategy that only needs a series of observations of the nodal price and the power intake at the substations connecting the transmission and distribution networks. Using this information, we learn the price response of active distribution networks (DN) using a decreasing step-wise function that can also adapt to some contextual information. The learning task can be carried out in a computationally efficient manner and the curve it produces can be interpreted as a market bid, thus averting the need to revise the current operational procedures for the transmission network. Inaccuracies derived from the learning task may lead to suboptimal decisions. However, results from a realistic case study show that the proposed methodology yields operating decisions very close to those obtained by a fully centralized coordination of transmission and distribution.
Virtual power plants (VPPs) have become an effective technique to manage a growing number of flexible resources, which have posed great technical challenges to distribution system operators (DSOs). ...This article proposes a bi-level programming approach for the collaborative management of an active distribution network (ADN) with multiple VPPs by designing comprehensive prices for active and reactive power. The upper layer aims to minimize the overall operation cost of the ADN considering the system security and economic operation and the interactions among the power market, ADN and VPPs. The lower layer aims to maximize the benefits of each VPP agent considering various flexible resources. Then, the bi-level model is transformed into a tractable single-level problem by using a linearization method, the Karush-Kuhn-Tucker (KKT) optimality conditions, the Fortuny-Amat transformation and the strong duality theorem. Case analyses indicate that the proposed strategy can effectively enhance the system security and improve the system economic performance by introducing reactive power pricing. The implementation effect and superiority of the proposed strategy are profoundly analyzed under different scenarios and conditions, which indicates its promising application value in the industrial field.
Demand side participation is a fundamental property of modern power distribution networks. Time-of-use pricing is a common strategy to persuade customers to shift a part of their consumption to low ...consumption hours. In flat time-of-use pricing, it is not the price that changes over a period, it is the cost of energy. The aim of this paper was to quantify impact of cost elasticity of demand on investment plans over a multi-stage horizon, where the time-of-use pricing was taken into account. On one hand, time-of-use pricing was modeled with three load levels as peak, medium-peak and off-peak. On the other hand, the tendency of customers to participate in reduction of demand was modeled where it shows rate of response of customers to change in cost of energy and it determines maximum demand response penetration. So, it was examined how time-of-use pricing and responsive customers can postpone the investments. Mixed integer linear programming method was utilized to solve the optimal distribution expansion planning problem. Simulations were performed on an 18-node distribution network. Results revealed effectiveness of the proposed model and showed that consideration of cost elasticity of demand in expansion planning, changes optimal configuration of network and significantly influences total costs.
As a typical approach to demand response (DR), direct load control (DLC) enables a load service entity (LSE) to adjust the electricity usage of residential customers for peak shaving during a DLC ...event. Households are connected in low-voltage distribution networks, which are always three-phase unbalanced. However, existing work has not considered the detailed operational constraints of three-phase distribution networks, which may lead to decisions that deviate from reality or are even infeasible in practice. Moreover, centralised control may cause privacy and communication issues. This study proposes a distributed residential DLC method that considers the operational constraints of three-phase unbalanced distribution networks and privacy of residential customers. Numerical tests on IEEE benchmark systems demonstrate effectiveness of the method. The proposed distributed method can converge within 17 iterations in IEEE 123-bus distribution system, which demonstrates scalability of the proposed algorithm.
The current transformation scenario in power distribution networks forecasts the need for alternative solutions in communication systems employed in the process of making them intelligent. As a ...premise, these alternatives should be easy to implement and affordable to allow their adoption in rural distribution networks, where, often, the use of technologies, such as mobile, is not available. This Letter proposes a new communication architecture with mesh topology, based on LoRa technology. The architecture adapts packet prioritisation and MIMO mechanisms to ensure the communication requirements necessary for the services. In this sense, several applications and protocols of a smart grid can coexist in the same communication system. The deployment of the architecture gave rise to a routing protocol adapted to the limitations of the radio technology used. The benefits of the proposed architecture can be observed when compared to the use of traditional low power wide area network networks and cellular technologies. The robustness of the system has been proven with average latency measurement within the acceptable range for DNP3 Modbus and NBR14522 applications. The results have shown its potential employment in the management of intelligent rural distribution systems.
This paper presented a scenario-based robust distributed generation investment planning (DGIP) model, which considered the uncertainties of wind turbine (WT) generation, photovoltaic (PV) generation ...and load demand. The robust economic model aims to maximize the net present value (NPV) from the distribution network operator's (DNO's) perspective. The uncertainties are described by an uncertainty matrix based on a heuristic moment matching (HMM) method that captures the stochastic features, i.e. expectation, standard deviation, skewness and kurtosis. The notable feature of the HMM method is that it diminishes the computational burden considerably by representing the uncertainties through a reduced number of representative scenarios. The uncertainty matrix is integrated with deterministic power flow equations to formulate a cost-benefit analysis based robust DGIP model with the objective of maximizing the DNO's net present value. The effectiveness of the proposed DGIP model is firstly verified in a 53-bus distribution test feeder, and then its scalability is further validated in a 138-bus distribution network. The numerical results confirm that the proposed DGIP solution is more robust for all representative network scenarios against the deterministic solution.
It has been demonstrated theoretically and experimentally that the Vehicle-to-Grid (V2G) enabled electric vehicle (EV) charger is of a reactive power compensation ability with a battery or capacitor ...connected. To exploit the aggregated reactive power V2G abilities of massively dispersed EV chargers, a distributed model predictive control (DMPC) strategy applying to both balanced and unbalanced distribution networks (DNs) is proposed to integrate them into real-time DN voltage regulation. Firstly, based on the instantaneous power theory and voltage sensitivity matrices, a voltage regulation model considering the reactive response of EV chargers is established without violating the normal EV active charging demands. Then, a completely distributed framework is achieved by DMPC, in which prediction information and calculation results are shared in a Peer-to-Peer (P2P) way to realize the asynchronous broadcast. The proposed model and techniques are validated by numerical results obtained from the IEEE European low voltage test feeder system. The case studies indicate that the proposed DMPC is robust to communication latency (CML) and works effectively in both balanced and unbalanced DNs without any control center, which is a significant advantage for the promotion of real-time reactive power V2G in DNs with irregular user integration and relatively poor communication infrastructure.
This article proposes a cooperative energy market model for an active Distribution Network (DN) by using the theory of Generalized Nash Bargaining (GNB). The proposed energy market has three types of ...participants: the DN operator, buyers, and sellers. Two energy trading manners are allowed at the same time: 1) each of buyers/sellers trades energy with the DN operator; 2) buyers and sellers trade energy in a Peer-to-Peer (P2P) manner and pay network usage fees to the DN operator. In the market, the DN operator actively manages voltage and reactive power (Volt-VAR) via controlling on-load tap changers of transformers and shunt capacitors. The payments among participants are subject to price constraints. The GNB problem for the proposed market is formulated and then decomposed into two subproblems: social welfare maximization problem (P1) and energy trading problem (P2). Both P1 and P2 are nonconvex problems. Next, linearization techniques are employed and a grid propagation algorithm is developed, transforming P1 and P2 into their equivalent Mixed-Integer Linear Programming (MILP) problems. In simulation, the proposed market model is compared with other GNB-based market models. The results show that the proposed one can significantly increase social welfare through Volt-VAR control and also can maximize the extent of fairness of profit allocation under the price constraints.
Power distribution networks (PDNs) has played a crucial role in expediting transition towards cleaner and better distributed energy sources. Nowadays, more and more distributed generations (DGs) are ...used in PDNs which complicates the automatic fault location. This article presents an accurate impedance-based method to determine the fault location for smart PDN in the presence of DGs. In addition, phase domain equations of distributed line parameters are used to enhance the accuracy of fault location. Two types of networks are considered. The first type of network is assumed to be fully observable with <inline-formula> <tex-math notation="LaTeX">\mu PMU </tex-math></inline-formula> and in the second type there are only a few <inline-formula> <tex-math notation="LaTeX">\mu PMU\text{s} </tex-math></inline-formula> with data loggers on the rest nodes. Load impedances of all nodes are estimated using pre-fault recorded information by present <inline-formula> <tex-math notation="LaTeX">\mu PMU\text{s} </tex-math></inline-formula> and data loggers. The proposed algorithm might suggest several points as possible fault locations for a PDN. To find out the actual location of fault same fault type is simulated for all suggested points. A matching value which is mathematically defined in the article, is calculated using recorded and simulated voltage to determine the actual fault point among all the suggested candidates. The accuracy of suggested method is analyzed against various conditions.
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