UK Generic Distribution System Research Articles

Optimal planning and operation of distribution systems using network reconfiguration and flexibility services

This paper proposes a novel approach for the reliability cost-based optimization of Distribution Systems (DS), considering tie line-based network reconfiguration method with integration of Distributed Energy Resources (DER). An optimal Energy not Supplied (ENS) index is proposed, where the capacity is handled by curtailment devices in the network such as sectionalizers and the energy supplied by DERs which considers Flexibility Services (FS) within a market environment. The decision variables include the investment and operation of tie-lines and buying regulation services from DER such as Distributed Generation (DG) and Battery Energy Storage Systems (BESS). The results validate the cost-effectiveness of the proposed method through implementation of these technologies to improve the reliability of the DS, within a comprehensive set of case-study scenarios for a 16-bus UK generic distribution system (UKGDS). The case study results indicate that significant savings can be achieved through the proposed method, ranging between 36%–71% depending on the level of automation in tie-line operations in combination with the settlement price for the power-balance of FS. This illustrates that the proposed DS reliability cost-based optimization method could have a significant impact for real world DG and BESS applications.

Planning, Operation, and Design of Market-Based Virtual Power Plant Considering Uncertainty

The power systems of today seem inseparable from clean energy sources such as wind turbines (WTs) and photovoltaics (PVs). However, due to their uncertain nature, operational challenges are expected when WT and PV energy is added to the electricity network. It is necessary to introduce new technologies to compensate for the intermittent nature of renewable energy sources (RESs). Therefore, rationally implementing a demand response (DR) program with energy storage systems (ESSs) in a virtual power plant (VPP) environment is recommended as a way forward to minimize the volatile nature of RESs and improve power system reliability. Our proposed approach aims to maximize social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). Our method assesses the impact of the DR program on SW maximization. Two scenarios are examined, one with and one without a DR program. Stochastic programming theory is used to address the optimization problem. The uncertain behavior of WTs, PVs, and load demand is modeled using a scenario-based approach. The correctness of the proposed approach is demonstrated on a 16-bus UK generic distribution system. Our results show that SW and active power dispatch capacity of WT, PV, and ESS are fairly increased using the proposed approach.

Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources

Renewable energy sources (RESs) are becoming more prevalent as a source of clean energy, and their integration into the power market is speeding up. The fundamental reason for this is the growing global concern about climate change. However, their weather-dependent and uncertain nature raise questions about grid reliability particularly, when photovoltaics (PVs) and wind turbines (WTs) technologies are used. As a result, rationally managing Energy Storage Systems (ESSs) under the virtual power plant (VPP) setting is being encouraged as a way of minimizing the impact of the uncertain nature of renewable energies. A VPP is comparatively a new concept that aggregates the capacities of dispatchable and non-dispatchable energy sources, electrical loads, and energy storage systems for the purpose of improving energy supply and demand imbalance. It enables individual consumers and producers to participate in the power markets. In this study, a new market-based (MB)-VPP operational planning model is designed and developed with the aim to evaluate the optimal active power dispatched by (WT, PV, and ESS) operating in the day-ahead power market to maximize the social welfare (SW) of the market. SW can be described as the maximization of the consumer’s benefit function minus the cost of energy generation. The optimization process was carried out by using a scenario-based approach to model the uncertainties of renewable energy sources (i.e, WTs & PVs) and load demand. The proposed model and method performance is validated by simulation studies on a 16-bus UK generic distribution system (UKGDS). The simulation results reveal that the proposed approach maximizes overall system social welfare. The capacity of total active power dispatched by (WT, PV, and ESS) has a positive impact on the VPP profit maximization. This empirical study could be used as a reference baseline model for other energy services providers interested in conducting similar research in the future.

Active Distribution Networks Planning Considering Multi-DG Configurations and Contingency Analysis

This paper proposes a novel method for planning active distribution networks (ADNs) with the integration of an active network management (ANM) scheme using coordinated voltage control (CVC) through on-load tap changer (OLTC) transformers. The method was formulated as a security-constrained optimal power flow (SCOPF) problem to minimize total operational costs, which maximizes the utilization of renewable distributed generators (DGs) over a planning horizon. The ANM scheme was applied using OLTC to ensure safe operation and reduce voltage violations in the network. To analyse the impact of ANM, the planning problem was examined both with and without the ANM scheme. Moreover, SCOPF, considering the N-1 line contingency analysis and multi-DG configuration, was implemented to analyse the feasibility of the proposed method and the advantages of ANM under contingency situations. The method was validated on a weakly-meshed 16-bus UK generic distribution system (UKGDS). The results showed that ANM can lower operational costs and maintain network voltage for operation in feasible conditions even in the case of a contingency. Moreover, the ANM scheme mitigated the voltage rise effect caused by DGs and maximized their utilization.

Optimal operation of distribution networks with high penetration of wind and solar power within a joint active and reactive distribution market environment

In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands.It further investigates the impact of solar and wind power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment. A mixed-integer linear programming (MILP) is used to recast the proposed model, which is solvable using efficient off-the shelf branch-and cut solvers. The 16-bus UK generic distribution system is demonstrated in this work to evaluate the effectiveness of the proposed method.Results show that DR integration leads to increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.

Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using A∗ search

The increasing integration of Electric vehicles (EVs) and renewable generators (RGs) is an inevitable trend of power grid concerning the global control of greenhouse gas release. This will challenge constrained distribution networks due to the intrinsic intermittency of renewable power and additional charging load demand of EVs. However, appropriate dispatch of EVs via vehicle-to-grid (V2G) operation in coordination with RGs can solve the stability issues, provide operational support for the power grid, reduce the reliance on fossil fuels and benefit both the environment and EV users. This paper develops a novel algorithm to solve the optimal decentralized coordinated dispatch problem of RGs and EVs based on multi-agent and the A∗ search procedure. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem using the Analytic Hierarchy Process taking into account both power grid and EV users’ concerns and priorities. The inherent uncertainty of EV driving activities and RG output power are considered in this work, of which the stochastic modelling is established using copulas. The proposed algorithm is tested on a radial distribution network, a modified UK generic distribution system. The simulation results demonstrate the feasibility and stability of the proposed A∗-based optimal coordinated dispatch strategy.

Active distribution networks planning with high penetration of wind power

In this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly.

Optimal coordination of vehicle-to-grid batteries and renewable generators in a distribution system

The increasing penetration of electric vehicles (EVs) and renewable generators (RGs) in the power grid is an inevitable trend to combat air pollution and reduce the usage of fossil fuels. This will challenge distribution networks, which have constrained capacity. However, appropriate dispatch of electric vehicles via vehicle-to-grid (V2G) operation in coordination with the distributed renewable generators can provide support for the grid, reduce the reliance on traditional fossil-fuel generators and benefit EV users. This paper develops a novel agent-based coordinated dispatch strategy for EVs and distributed renewable generators, taking into account both grid's and EV users' concerns and priorities. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem utilizing the Analytic Hierarchy Process and is solved using a dynamic-programming-based algorithm. The proposed strategy is tested on a modified UK Generic Distribution System (UKGDS). The electricity network model is simplified using a virtual sub-node concept to alleviate the computation burden of a node's agent. Simulation results demonstrate the feasibility and stability of this dispatch strategy.

Active distribution networks planning with integration of demand response

This paper proposes a probabilistic method for active distribution networks planning with integration of demand response. Uncertainties related to solar irradiance, load demand and future load growth are modeled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Demand Response Mismatch (DRM): Concept, Impact Analysis, and Solution

Demand response (DR) is emerging as one of the key smart grid components that plays a major role in achieving adequate supply-demand balance. DR is often considered as a market resource and thus there is more focus in the literature on economic aspects, thereby neglecting the DR's interaction and impact on the power system operation. This paper identifies a potential gap while employing DR in distribution systems. Usually, the load reactive power and the load's voltage dependency are ignored in the DR studies. It is shown in this paper that the inclusion of these two elements results in an active power mismatch between the scheduled and the actually achieved DR. A new term that is capable of quantifying this mismatch is introduced and is termed as “demand response mismatch (DRM).” To overcome such problem, this paper proposes a mixed integer non linear program (MINLP) to find the optimal size and location of STATCOM and/or optimal transformer tap setting that can minimize the DRM. The phenomenon of DRM is illustrated using a standard 16-bus U.K. generic distribution system (UKGDS) while considering different load power factors, load reduction amounts, load models, as well as DR locations.

Distribution System State Estimation Using an Artificial Neural Network Approach for Pseudo Measurement Modeling

This paper presents an alternative approach to pseudo measurement modeling in the context of distribution system state estimation (DSSE). In the proposed approach, pseudo measurements are generated from a few real measurements using artificial neural networks (ANNs) in conjunction with typical load profiles. The error associated with the generated pseudo measurements is made suitable for use in the weighted least squares (WLS) state estimation by decomposition into several components through the Gaussian mixture model (GMM). The effect of ANN-based pseudo measurement modeling on the quality of state estimation is demonstrated on a 95-bus section of the U.K. generic distribution system (UKGDS) model.

A Recursive Bayesian Approach for Identification of Network Configuration Changes in Distribution System State Estimation

This paper deals with the identification of network configuration changes in distribution system state estimation (DSSE). The models of critical network configurations are stored in the form of a model bank. A recursive Bayesian approach which utilizes the output of the state estimation function of each model in the bank is used to identify the correct configuration of the network. The concept is demonstrated on a part of the U.K. Generic Distribution System (UKGDS) model.

Active power-flow management utilising operating margins for the increased connection of distributed generation

Active management provides a method to extend capacity for generation connections to distribution networks through the coordinated control of multiple network components in real-time. Identifying principles and strategies for active network management that hold for all situations will provide support to network operators and planners and form the basis for a new paradigm in utility strategy concerning the connection of distributed generation. The authors build upon previous work regarding the initial specification and economic evaluation of an active power- flow management (APFM) scheme concerned with facilitating increased generator connections. Operating margins have been identified as an essential element of the APFM scheme for the provision of network security and play a significant role in determining the economic viability of generation connected under the APFM scheme. An approach to the definition of the operating margins required to trigger generator output regulation (trimming) and tripping is introduced. These concepts are demonstrated through a case study using one of the UK generic distribution system models. The analysis considers technical, regulatory and economic factors, resulting in practical recommendations for future work and the identification of the factors that affect the implementation of such a scheme.

Reducing unnecessary disconnection of renewable generation from the power system

Future power systems with large proportions of embedded generation could be severely affected if several loss of mains (LOM) protection systems maloperate in response to a non-islanding condition, potentially leading to generation shortfall and stability problems. Although many papers discuss methods of sensitively detecting islanded conditions (a short bibliographical survey is included), almost no papers in the literature address the problems associated with the stability of such protection methods during and after perturbations on the network to which they should not react. The aim is to highlight the shortcomings in existing power system protection practices relating to islanding detection with a view to identifying necessary areas of improvement to facilitate the ongoing proliferation of renewable sources in active distribution networks. Existing LOM techniques are described and stability-related shortcomings are demonstrated using the results of rigorous laboratory testing of several commercially available relays. The testing scenarios are developed using a UK Generic Distribution System repository, a public domain database representing typical distribution system architectures. Recommendations relating to the setting of existing LOM protection devices are provided, along with an overview of research and development activities relating to improvements in anti-islanding protection, including a discussion of both technical and economical viability.