Countries around the world set ambitious targets to substantially reduce their greenhouse gasses emissions, including those which come from electricity sector. This requires a transition to a low carbon electricity generation and supply system, which in part, can be met by increasing distributed generation (DG) connection and implementing demand side response (DSR) programme on distribution network. Therefore, the role of distribution network operators (DNOs) in facilitating the connection of new DG and the implementation of DSR programme is vital. In order to encourage DNOs to be more active in the low carbon transition, the energy regulator needs to set up financial incentives for DNOs. Current DG incentive mechanism, which is applied in the UK, aims to incentivise DNOs based on the amount of DG capacity connected to the network. Consequently, in a generation-dominated area, the incentives might not be sufficient to cover the reinforcement required for connecting DGs, which in turn, the output energy from DGs will be excessively curtailed. Therefore, this research proposes a new approach, called energy-based DG incentive mechanism. This mechanism will incentivise DNOs based on the utilization of available DG energy on the network and its relation with the requirement of network reinforcement. In terms of DSR incentives, different mechanisms have been applied in some countries, including Australia and USA. Some of the mechanisms incentivise DNOs based on the investment cost or forgone revenue related to DSR initiatives, as implemented in demand management incentive and rate of return mechanisms. Other mechanisms aim to incentivise DNOs based on the energy savings or avoided costs of supply associated with DSR participation, as implemented in shared savings and avoided cost mechanisms. Those mechanisms operate independently without any correlation between them. Therefore, this research develops a new approach to assess the relation between DSR investment cost and DSR participation, called energy-based DSR incentive mechanism. This mechanism will incentivise DNOs based on the utilization of available DSR energy on the network and its relation with the required investment. Comparing with current incentive mechanisms, both energy-based DG incentive and energy-based DSR incentive can reflect the effectiveness of DNOs to deal with the required investments in association with DG connection and DSR implementation on their network.

Despite the extensive deployment of smart-meters (SMs) at the low-voltage (LV) level, which are either fully operational or will be in the near future, distribution network operators (DNOs) are still relying on a limited number of permanently installed monitoring devices at primary and secondary medium-voltage (MV) substations, for purposes of network operation and control, as well as to inform and facilitate trading interactions between generators, distributors and suppliers. Accordingly, improved and sufficiently developed models for the analysis of aggregate demands at the MV-level are required for the correct assessment of load variability, composition and time-dependent evolution, necessary for: addressing issues of robustness, security and reliability; accomplishing higher penetration levels from renewable/distributed generation; implementing demand-side-management (DSM) schemes and incorporating new technologies; decreasing environmental and economic costs and aiding towards the realisation of automated and proactive ''smart-grid'' networks. The analysis of MV-demand measurements provides an independent source of information that can capture network characteristics that do not manifest in the data collected at the LV-level, or when such data is restricted or altogether unavailable. This information describes the supply/demand interactions at the mid-level between high-voltage (HV) transmission and LV end-user consumption and opens possibilities for validation of existing bottom-up aggregation approaches, while addressing issues of reliance on survey-based data for technical and economic power system studies. This thesis presents improved and novel methodologies for the analysis of aggregate demands, measured at MV-substations, aimed at more accurate and detailed load profiling, temporal decomposition and identification of the drivers of demand variability, classification of grid-supply- points (GSPs) according to consumption patterns, disaggregation with respect to customer-classes and load-types and load forecasting. The developed models are based on a number of traditional and modern analytical and statistical techniques, including: data mining, correlational and regression analysis, Fourier analysis, clustering and pattern recognition, etc. The approaches are demonstrated on demand datasets from UK and European based DNOs, thus providing specific information for the demand characteristics, the dependencies to external parameters and to socio-behavioural factors and the most likely load composition at the corresponding geographical locations, while the approaches are also intendent to be easily adaptable for studies at equivalent voltage and demand aggregation levels.

Integration of renewable energy systems by the utility, customers, and the third party into the electric power system, most especially in the MV and LV distribution networks grew over the last decade due to the liberalization of the electricity market, rising energy demand, and increasing environmental concern. The distributed rooftop PV system contributes to relieve the overall load, reduce losses, avoid conventional generation upgrade, and better matching of demand on the LV distribution network. Originally, the LV distribution network is designed for unidirectional current flow, that is from the substation to customers. However, a high penetration of rooftop solar PVs (with power levels typically ranging from 1 – 10 kW) may lead to the current flowing in the reverse direction and this could result in a sudden voltage rise. These negative impacts on the network have discouraged the distribution network operators (DNOs) to allow increased PV penetration in the LV distribution network because some customers load, and equipment are sensitive to voltage perturbation. Presently, the most applied voltage rise mitigation strategy for high rooftop solar PV penetration is the total disconnect from the LV distribution network when the voltage at the point of common coupling (PCC) goes above statutory voltage limits. However, the sudden disconnection of the PV system from the grid can cause network perturbation and affect the security of the network. This action may also cause voltage instability in the network and can reduce the lifetime of grid equipment such as voltage regulators, air conditioner etc. Due to this negative impact, different voltage rise mitigation strategies such as the active transformer with on load tap changers (OLTC), distributed battery energy storage system and reactive power support (D-STATCOM, etc.) have been used to curtail voltage rise in the distribution network. However, the implementation of D-STATCOM device on a radial LV distribution network results in high line current and losses. This may be detrimental to the distribution network. Therefore, in this thesis, a coordinated active power reduction (CAPR) strategy is proposed using a modified PWM PI current control strategy to ramp down the output power and voltage of a grid-tied voltage source inverter (VSI). In the proposed strategy, a reactive reference is generated based on the measured voltage level at the PCC using a threshold voltage algorithm to regulate the amplitude of the modulating signal to increase the off time of the high frequency signal which shut down the PV array momentary in an extremely short time and allow the VSI to absorb some reactive power through the freewheeling diode and reduce voltage. The proposed CAPR strategy was designed and simulated on a scaled down simple radial LV distribution network in MATLAB®/Simulink® software environment. The results show that the CAPR can ramp down the PV output power, reduce reverse power flow and reduce the sudden voltage rise at the point of common coupling (PCC) within ±5% of the standard voltage limit. The study also compares the performance of the proposed CAPR strategy to that of the distributed static compensator (D-STATCOM) and battery energy storage system (BESS) with respect to response time to curtail sudden voltage rise, losses and reverse power flow. The investigation shows that the D-STATCOM has the faster response time to curtail voltage rise. However, the voltage rise reduction is accompanied by high current, losses and reverse active power flow. The introduction of the BESS demonstrates better performance than the D- STATCOM device in terms of reverse power flow and losses. The CAPR strategy performs better than both D-STATCOM and BESS in terms of line losses and reverse power flow reduction.

Yes / 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 modelled 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.

Yes / This paper proposes a probabilistic multi-objective optimization method for the operation of three-phase distribution networks incorporating active network management (ANM) schemes including coordinated voltage control and adaptive power factor control. The proposed probabilistic method incorporates detailed modelling of three-phase distribution network components and considers different operational objectives. The method simultaneously minimizes the total energy losses of the lines from the point of view of distribution network operators (DNOs) and maximizes the energy generated by photovoltaic (PV) cells considering ANM schemes and network constraints. Uncertainties related to intermittent generation of PVs and load demands are modelled by probability density functions (PDFs). Monte Carlo simulation method is employed to use the generated PDFs. The problem is solved using ɛ-constraint approach and fuzzy satisfying method is used to select the best solution from the Pareto optimal set. The effectiveness of the proposed probabilistic method is demonstrated with IEEE 13- and 34- bus test feeders.

Yes / 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.

No / This chapter proposes a novel method for the operation of active distribution networks within a distribution market environment taking into account multi-configuration of wind turbines. Multi-configuration multi-scenario market-based optimal power flow is used to maximise the social welfare considering uncertainties related to wind speed and load demand. Scenario based approach is used to model the uncertainties. The method assesses the impact of multiple-wind turbine configurations on the amount of wind power that can be injected into the grid and the distribution locational marginal prices throughout the network. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Over the past few decades, wireless local area networks (WLANs) have been widely deployed for data communication in indoor environments such as offices, houses, and airports. In order to fairly and efficiently use the unlicensed frequency band that Wi-Fi devices share, the devices follow a set of channel access rules, which is called a wireless medium access control (MAC) protocol. It is known that wireless devices following the 802.11 standard MAC protocol, i.e. the distributed coordination function (DCF), suffer from packet collisions when multiple nodes simultaneously transmit. This significantly degrades the throughput performance. Recently, several studies have reported access techniques to reduce the number of packet collisions and to achieve a collision free WLAN. Although these studies have shown that the number of collisions can be reduced to zero in a simple way, there have been a couple of remaining issues to solve, such as dynamic parameter adjustment and fairness to legacy DCF nodes in terms of channel access opportunity. Recently, In-Band Full Duplex (IBFD) communication has received much attention, because it has significant potential to improve the communication capacity of a radio band. IBFD means that a node can simultaneously transmit one signal and receive another signal in the same band at the same time. In order to maximize the performance of IBFD communication capability and to fairly share access to the wireless medium among distributed devices in WLANs, a number of IBFD MAC protocols have been proposed. However, little attention has been paid to fairness issues between half duplex nodes (i.e. nodes that can either transmit or receive but not both simultaneously in one time-frequency resource block) and IBFD capable nodes in the presence of the hidden node problem.