A Cooperative Game Theory Approach to Encourage Electric Energy Supply Reliability Levels and Demand-Side Flexibility

: In RM 23, a proof was given that the nucleolus is continuous as a function of the characteristic function. This proof is not correct; the author, at least, does not know how to complete it. In the paper a correct proof for this fact is given. The proof is based on an alternative definition of the nucleolus, which is of some interest in its own right. (Author)

With the high proportion of new energy access in power distribution networks, the operation of distribution networks becomes more uncertain and complex. The mechanism on how to extract features that embody the full perspective of the distribution network from the diverse and varying conditions is of great significance to master the operating property of distribution networks under the high proportion of new energy. This study investigates the portrait construction of power distributions. A data-driven method of portrait construction for a distribution network based on a cloud model is proposed. First, the indexes describing the operation of the medium voltage distribution network (MVDN) and low-voltage station area (LVSA) are established. By means of statistics, fuzzy label templates are provided for the indexes. Then, based on the daily monitoring power grid data, the operation index is calculated to form the collected samples, and the reverse cloud generator is used as the data-driven method to process the samples, and the fuzzy model of cloud parameter representation is obtained. Finally, the fuzzy distance between the obtained fuzzy model and the label template is calculated, and the scores of operation indexes are obtained, thus forming a portrait method of distribution network operation behavior. Taking the IEEE 33 distribution network and real distribution network as examples and taking the LVSA as an example, it is verified that this method can effectively construct the distribution network operation portrait.

Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory

Microgrid plays an important role in absorbing rural distributed renewable energy and ensuring the reliability of power supply. In order to reduce the waste of clean energy and improve the operation efficiency of microgrid, a cooperative game-based optimization method for microgrid and distribution network is proposed. Firstly, combined with the complementarity of wind power, solar power and biogas power generation in time, the cooperative operation mechanism of micro power is established. Load characteristics are taken as constraints and the minimum operating cost as objective function. Then, a microgrid alliance protocol based on cooperative game theory is proposed, in order to maximize the benefits of microgrids. In the alliance, power surplus microgrid sells electric to power shortage microgrid to realize complementary power supply. So as to improve the distribution efficiency and reduce the overall operation cost. Finally, it proposes a complementary power supply scheme between microgrid alliance and distribution network as well as a revenue distribution method. For the distribution of benefits, Shapley value method is discussed in order to distribute benefits fairly. On the basis of theoretical research, the objective function and constraint conditions are designed to build the algorithm model and write program for simulation. The analysis results show that cooperative game optimization operation of microgrid and distribution network can effectively improve the distribution efficiency and increase benefits.

Design and analysis of electrical energy storage demonstration projects on UK distribution networks

With the rapid development of the energy industry, the power industry has also begun to rise, especially the household meter system, which is being implemented now, so that the mining and approval of electricity meters are also increasing. Using BPNN algorithm, this paper studies the DN operation and maintenanceIMS, and discusses the functional requirements of DN operation and maintenance information management, as well as BPNN and design scheme; The statistical analysis of user and load control data in the DN operation and maintenance information management statistical database shows that the average load rate of DN lines of industrial users is as high as 81% and the utilization rate of power station interval is 23%; The average load rate of DN lines of users in administrative office and the utilization rate of power station interval are 62%. The confidentiality of user basic information, user load data sheet, line load and economic data sheet has reached more than 80%, and the line load operation efficiency is only 53%, which needs to be improved.

Distributed generation (DG) poses new challenges in distribution network development and operation. Distribution Network Operators (DNOs) will face more active management of networks, new commercial arrangements, and new challenges in asset management. Resolving these will require new types of analysis that were previously unnecessary or very rare. Collecting and processing information to facilitate these analyses presents a significant new burden for DNOs. However, methods are available that may assist DNOs in the collection of information. Three such methods are discussed here: a structured approach to fundamental information requirements; standard formats; and generic device types or category descriptions. Examples are provided of how DNOs would use the information collected to analyse DG connection and operation. Effective management of information will enable DNOs to characterise DG and perform the analyses necessary to ensure that a reliable and high-quality electricity supply is maintained.

In the context of global energy transformation and sustainable development, integrating and utilizing renewable energy effectively have become the key to the power system advancement. However, the integration of wind and photovoltaic power generation equipment also leads to power fluctuations in the distribution network. The research focuses on the multifaceted challenges of optimizing the operation of distribution networks. It explores the operation and control methods of active distribution networks based on energy storage and reactive power compensation equipment. The stable operation of the distribution network is analyzed under the conditions of wind and photovoltaic integration, with a particular focus on precise regulation to address the limitations of existing methods. Afterwards, the study proposes an improvement plan that combines on load tap changer transformers and reactive power compensation equipment to solve complex power balance problems through second-order cone programming relaxation method. The results of numerical analysis show that the constructed mathematical model maintains a stable voltage of 1 to 1.1 pu at distribution network nodes within 24 h. Especially during peak hours from 15:00 to 24:00, it remains normal without any abnormal fluctuations when the control equipment is not added. These results confirm that precise regulation of multiple devices ensures voltage stability and avoids low or high voltage issues.

In the context of the green energy transition, the rapid expansion of flexible resources such as distributed renewable energy, electric vehicles (EVs), and energy storage has significantly impacted the operation of distribution networks. This paper proposes a multi-objective optimization approach for active distribution networks (ADNs) based on analytical target cascading (ATC). Firstly, a dynamic optimal power flow (DOPF) calculation method is developed using second-order conic relaxation (SOCR) to address power flow and voltage issues in the distribution network, incorporating active management (AM) elements. Secondly, this study focuses on aggregating the power of flexible resources within station areas connected to distribution network nodes and incorporating these resources into demand response (DR) programs. Finally, a two-layer model for collaborative multi-objective scheduling between station areas and the active distribution network is implemented using the ATC method. Case studies demonstrate the model’s effectiveness and validity, showing its potential for enhancing the operation of distribution networks amidst the increasing integration of flexible resources.

The UK Government is working towards ambitious targets on renewable generation and CHP. Depending on the load factor assumed, this will require the installation of significant generation capacity, in the order of 10 GW by 2010. Significant proportion of this generation is expected to be connected to distribution networks (i.e. at voltages of 132 kV and below). However, under the present conditions the owners and operators of the distribution networks, the Distribution System Operators (DSOs) anticipate that they can integrate only a much more limited capacity of distributed generation (DG) without a major reinforcement. Recently, significant amount of work was carried out to analyse and demonstrate the benefits that can be derived from changing the operation philosophy of distribution networks from passive to active. The emphasis was on the design of control strategies of active distribution systems that would enhance the ability of the existing networks to accommodate additional distributed generation, and reduce the demand for reinforcements. Hence there is a need to understand the impact of various active management control strategies on the overall operation and investment performance of the entire distribution network. This kind of analysis will be essential for DSOs in order to take the most cost effective strategic decisions to optimally integrate DG in their networks. This paper presents a methodology for quantifying the value of various active distribution network management for various DG development scenarios, in the context of the UK distribution system. First the main network issues related to the connection of DG are discussed, and how they could be resolved by using active management. Indicative results quantifying the benefits of active management in the entire UK distribution network are then presented.

Nowadays, the development of human society and daily life are inseparable from the power supply. Therefore, people also put forward higher requirements for the reliability of distribution network, but power companies can only passively deal with distribution network failures, which is a bottleneck for the improvement of distribution network reliability. The Internet of Things (IoT) is the best solution for online equipment status monitoring and basic data sharing for large, widely distributed, relatively fixed, and large numbers of equipment. The construction of the IoT for power distribution equipment faces many important problems, including the selection of networking, equipment selection, and interaction standards. When researching the implementation plan, research on the distribution of IoT market was carried out. Based on the grid, the idea of optimizing the investment selection plan of the power distribution using IoT was discussed, and a result verification model was established. After the completion of the theoretical part, a case study of medium-voltage distribution grid equipment management and medium-voltage distribution network equipment management based on the grid was carried out by taking a real enterprise application situation as an example. Realizing fault diagnosis of distribution network will not only provide decision support for operation and maintenance of distribution network for power companies, but also have great economic and social benefits. Aiming at the shortcomings of single data mining method in distribution network fault diagnosis, hybrid data mining method is proposed. First, rough set theory is used to reduce the original fault data and form a simplified rule set. Because of the non-linearity of distribution network fault and the strong learning ability, adaptability, and robustness of Bayesian network, Bayesian network can be used to classify distribution network faults. Therefore, a simplified fault diagnosis system is established in this paper, and its correctness is confirmed. Then, the learning and training are carried out by using Bayesian network to call the simplest rule set, which has the characteristics of short learning and training time and high diagnostic accuracy.

Despite of the great focus of attention dedicated to demand response (DR), the potential benefits of DR on distribution networks have not yet been quantitatively studied. This paper aims to assess DR potential impacts on major attributes of the operation of a residential distribution network. For doing so, grossly metered usage of more than 1600 residential consumers from Kainuu, Finland, is disaggregated to appliance-level load profiles. The flexibility of the load profiles is also estimated from the survey data and questionnaires. The individual profiles are then adjusted within their flexibility such that the most evenly distributed aggregated load profile is realized. Finally, the resulted load profile is applied to a Finnish distribution network, and the impacts of the DR on different aspects of the network operation such as the network losses, voltage profiles, and service reliability are studied. The observations certified significant benefits of the DR potentials for the network operation and reliability. It is also revealed that almost all of the benefits can be achieved by enabling the potential of responsive heating and ventilation systems.

At present, in the process of optimizing distribution network system, economy is taken as the starting point and modern technical means are comprehensively used to realize the reliability and safety of operation mode. The operation of distribution network based on flexible switch is the result of technology development in the new era. In this paper, based on the historical background of modern science and technology development, it analyzes the application of flexible switch synthesis coordination in the economic operation of distribution network. Firstly, it analyzes the current research status of distribution network with the coordination of flexible switches synthesis, and then optimizes the operation mode of traditional distribution network, and again, explores the flexible representation of distribution network in the operation process, optimizes the flexible synthesis of distribution network operation mode, finally completes the verification analysis.

Harmonics mitigated multi-objective energy optimization in PV integrated rural distribution network using modified TLBO algorithm

In this paper, the problem of microgrid group participating in active and reactive power trading on the distribution side is studied. A Nash bargaining model based on cooperative game theory is proposed for the transaction between microgrid operators (MGO) and distribution network operator (DNO). Taking the optimal operating cost of direct transaction between MGO and DNO as the disagreement point of Nash bargaining. The solution of Nash equilibrium is obtained. Finally, a case study is given to verify the effectiveness of the proposed method in solving the economic dispatching problem of active power and reactive power.