Collaborative Planning Method Research Articles

Optimization of Participatory and Collaborative Planning Methods for Accelerating the Preparation of Detailed Spatial Plans

The availability of Detailed Spatial Plans (RDTR) is crucial for supporting development implementation and ease of doing business. However, there are still problems in the preparation of RDTR, necessitating acceleration. Regarding this acceleration, it is necessary to analyze how participatory and collaborative planning methods can play a role. Participatory and collaborative approaches are important because public trust and stakeholder relationships in participatory and collaborative planning influence the implementation process and planning outcomes. This study aims to identify the relationships between implementing actors and stakeholders involved in the preparation of RDTR so that they can be optimized with a participatory and collaborative approach. The research methods used are Social Network Analysis (SNA), Organizational Network Analysis (ONA), and post-review surveys. The results show that the relationships between implementing actors and stakeholders related to RDTR preparation are not yet optimal, therefore requiring remapping and rearrangement within the legal framework. Participatory and collaborative approaches will elaborate the possibility of more effective and efficient relationships with changes in roles and media of interaction. Keywords: Collaborative, Network Analysis, Participatory, RDTR, Spatial Planning

A multi-objective collaborative planning method for a PV-powered hybrid energy system considering source-load matching

A hybrid system including photovoltaic panels, an air-source heat pump, batteries, and a hot water tank is proposed to satisfy the building’s demands. To discover the optimal energy scheduling scheme, a multi-objective two-stage planning method is developed. In the first stage, considering the seasonal fluctuations of photovoltaic power and the loads, several operation modes are designed. Moreover, the influence of objective functions with and without the energy self-consumption (SCR) and self-sufficiency rate (SSR) on the system configuration is analyzed. The second stage aims to explore the synergetic benefits with demand response, in which the hourly loads are reconstructed accounting for the municipal tariffs. The results show that when accounting for the annual cost (AC) and primary energy (PE), the ideal operation mode is as follows: favor thermal storage during periods of energy surplus and prioritize discharging electricity in winter and heat in summer in cases of insufficient power. When considering the SCR and SSR additionally, storing heat in summer with charging batteries in winter is preferred when excess energy is available. Otherwise, give priority to thermal storage. Furthermore, based on the proposed energy scheduling scheme, the AC, PE, SCR, and SSR are improved by −31.1 %, −19.4 %, +1.5 %, and +11.3 %, respectively.

Multi-Stage Coordinated Planning for Transmission and Energy Storage Considering Large-Scale Renewable Energy Integration

Due to the large-scale integration of renewable energy and the rapid growth of peak load demand, it is necessary to comprehensively consider the construction of various resources to increase the acceptance capacity of renewable energy and meet power balance conditions. However, traditional grid planning methods can only plan transmission lines, often resulting in low utilization rates of newly constructed lines. Additionally, static planning methods can only address single-target scenarios and cannot cope with dynamic growth in load and renewable energy. To address these issues, this paper proposes a multi-stage collaborative planning method for transmission networks and energy storage. This method considers the non-line substitution effect of energy storage resources and their characterization methods. It establishes the coupling relationship between resources across different planning stages to achieve coordinated multi-stage planning for transmission networks and energy storage. Based on the IEEE-24 node system and a case study in a northern province of China, the results show that the proposed method reduces investment costs by approximately 30% compared to static planning methods and by about 7.79% compared to conventional grid planning methods. Furthermore, this method can accommodate more renewable energy.

Multi‐objective interval planning for 5G base station virtual power plants considering the consumption of photovoltaic and communication flexibility

AbstractLarge‐scale deployment of 5G base stations has brought severe challenges to the economic operation of the distribution network, furthermore, as a new type of adjustable load, its operational flexibility has provided a potential way to promote the consumption and utilization of photovoltaic. In this paper, a multi‐objective interval collaborative planning method for virtual power plants and distribution networks is proposed. First, on the basis of in‐depth analysis of the operating characteristics and communication load transmission characteristics of the base station, a 5G base station of virtual power plants participating in the cellular respiratory demand response model is constructed. In view of the inherent contradiction between system economy and environmental performance, a multi‐objective interval optimization model for collaborative planning of virtual power plants and distribution networks is established with the lowest system investment and operating costs and the lowest carbon emissions as the optimization goals. The established model is transformed into a deterministic optimization problem, which is solved by NSGA‐II algorithm. The modified IEEE‐33 node system is used in the case analysis to analyse the impact of different planning schemes and response characteristics on the system economy. The calculation results verify the effectiveness of the proposed method.

Collaborative Planning and Comprehensive Evaluation Method for Energy Storage System and Flexible Interconnection in Distribution Networks Considering Island Operation

Introduction: When the superior power grid fails and loses power, due to the traditional single power supply radial grid structure of low-voltage substation areas, all loads in the lowvoltage substation area will lose power, causing a poor electricity consumption experience for low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in distribution networks, considering island operation, is proposed. Method: This method integrates GFM-ESS and flexible interconnections, taking islanding operations into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed. The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly, minimizing the annual comprehensive cost and the annual power outage load are the objective functions. A bilevel programming model for GFM-ESS and flexible interconnection of lowvoltage distribution networks, considering island operation, has been established. Moreover, a comprehensive evaluation method based on the analytic hierarchy process for proposed lowvoltage distribution network structural schemes is introduced. An evaluation index system is established to assess the rationality of these proposed network structural planning schemes. Finally, the superiority of the proposed collaborative planning method is verified through a comparative analysis of three planning methods. Result: The proposed collaborative planning method can effectively ensure the continuous power supply of low-voltage distribution networks under the fault scenario of the upper power network. Conclusion: Moreover, the rationality of the results obtained from the proposed collaborative planning method is verified through a comprehensive evaluation method of grid structure schemes based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine which two areas are optimal for grid planning. result: The superiority of the proposed collaborative planning method was verified by comparative analysis of three planning methods. And the rationality of the proposed collaborative planning method results was verified by the comprehensive evaluation method of grid structure schemes based on analytic hierarchy process.

From process-based to technology-driven: a study on functionalities as key elements of collaborative planning methods for construction projects

With the advancement of emerging technologies, significant attempts have been made to develop collaborative planning methods and to involve as many project stakeholders as possible in the construction project planning and control process. However, inadequate consideration has been paid to the characteristics, goals, and principles underlying these methods to meet the needs of collaboration for project planning between project teams. To deal with this, a multi-stage methodology was carried out to achieve the aims of this study. The first step was identifying collaborative planning methods and their functionalities in the construction sector. Further, a quantitative analysis based on Social Network Analysis (SNA) was conducted to determine the most frequently utilized functionalities in collaborative planning methods. The results revealed that process-based collaborative planning methods’ functionalities prioritized process and people-related characteristics such as team trust and promise, as well as social interactions, whereas technology-driven methods highlighted visualization along with collaboration and communication as a key element of collaborative planning. Subsequently, this study contributes to the body of construction project planning and control knowledge from both theoretical and practical perspectives by enhancing the understanding and sensemaking of project stakeholders towards the underlying concepts and objectives of collaborative planning methods.

Research on Control Strategy of Two Arm Collaborative Robot Based on Vision

<p>Double arm robots are increasingly being used in automated production due to their higher work efficiency and better flexibility. This article focuses on the research of visual recognition based robots applied in automated production lines. Firstly, the visual system has been improved and image labeled to make it more accurate in identifying targets. Then, path planning has been carried out for the coordinated movement of both arms. Through the unconstrained collaborative planning method of both arms, the efficiency and robustness of path planning have been improved. Finally, experimental simulation has been conducted to verify the effectiveness of visual assistance conditions. The effectiveness of the dual arm planning method.</p> <p> </p>

Strategic Collaborative Planning for Urban Liveability: A Comparative Review of Metropolitan Area Case Studies

The issue of urban liveability has been extensively debated by global agencies and scholars, as evidenced by the New Urban Agenda, in response to the impact of urbanisation. Urban liveability pertains to the ability of urban communities to achieve a high-quality living environment. While participatory planning is often presented as a means of empowering communities to attain better living conditions, it has presented challenges for decision-makers. Furthermore, dominant actors often influence participation processes, benefiting certain community segments. As a result, collaborative planning has emerged as an approach that seeks to address the interests of multiple urban factors by promoting consensus in decision-making. This paper aims to examinethe collaborative planning methods that have been used in strategic planning that have empowered the community to participate in the planning process.Content analysis was employed as a research method to explore the empirical evidence of collaborative planning that has successfully empowered community participation in strategic planning and its impact on the liveability of metropolitan areas. Correspondingly, the Melbourne, Vancouver, and Helsinki case studies were selected based on five liveable city indices. This study's findings suggest a positive correlation between the implementation of collaborative planning by the selected metropolitan areas and their status as the most liveable cities. This paper contributes to the ongoing debate on the role of collaborative planning in promoting urban liveability.

A Collaborative Planning Method for the Source and Grid in a Distribution System That Considers Risk Measurement

The existing distribution system planning methods do not fully consider improving power supply capacity and reliability through the coordination of multiple planning factors, and they are not comprehensive enough in quantifying planning risks. Therefore, this paper proposes a collaborative planning method for sources and networks that considers risk measurement. A multi-layer planning model is first constructed that includes a grid planning layer, a power planning layer, a switch planning layer, and an operation optimization layer. In the model, a risk measurement method combining opportunity constraints and conditional value-at-risk objectives is used to comprehensively assess the risk of the node voltage and branch current exceeding the limit caused by load uncertainty. Then, a solution strategy based on a genetic algorithm and a sparrow search algorithm is proposed to coordinate the contradiction between the solution time and the accuracy of the multi-layer model. Finally, taking a planned area to be expanded as an example, the results show that compared to the existing collaborative planning methods for sources and networks, the proposed method in this paper reduces the planning risks caused by load uncertainty by more than 50% and increases the annual net income of the power distribution company and the DG operators by RMB 1.5 million and RMB 1.1 million, respectively.

Collaborative Planning of Community Charging Facilities and Distribution Networks

The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community’s electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given.

Collaborative planning of cyber physical distribution system considering the flexibility of data centers

With the development of energy transition and smart grid, the traditional distribution network has transformed into a cyber–physical distribution network (CPDS), which is multidimensional and heterogeneous. The increasingly abundant cyber and physical resources and deep coupling characteristics provide new challenges for distribution network planning. Based on a distribution network with multiple distributed resources and data centers, this paper proposes a cyber–physical collaborative planning method for a distribution network. First, according to the overall architecture of CPDS and the cross-layer control manner, the multiple distributed resources model and spatial–temporal migration model of data loads are established. Then, taking the minimal annual cost of distributed resources as the objective function, the collaborative planning of energy storage systems (ESSs) and corresponding smart terminal units (STUs), spatial–temporal migration strategy of data load, and communication network topology is carried out. Finally, the economics and feasibility of the proposed planning scheme are verified by the modified IEEE-33 bus distribution system. The results show that the collaborative planning method proposed in this paper can reduce the investment cost of distribution network planning and solve the voltage variation problem to a certain extent, so as to improve the economy and operational reliability of distribution network, and provide theoretical guidance for planners.

Hierarchical Collaborative Planning of County Energy Internet

Building a County Energy Internet (CEI) is crucial for achieving green and low-carbon transition and sustainable development of county energy systems. This paper proposes a bi-level collaborative planning method for CEI to configure devices’ capacities in multiple regional CEIs (RCEIs) and plan the interconnected networks simultaneously. Firstly, the models of multi-energy devices and networks are constructed. Then, an optimal partitioning method based on a clustering algorithm is proposed to divide the CEI into multiple RCEIs by considering the load distribution pattern and complementary characteristics. On top of that, a bi-level planning model for CEI is established, wherein the lower-level problem aims at configuring the capacities of devices in RCEIs through mixed-integer linear programming (MILP), while the upper-level problem is the determination of the interconnected multi-energy network topologies by searching the minimum spanning tree. This two-level planning problem is resolved iteratively, in which the network topologies of CEI and energy imbalance in each RCEI are shared information. Case studies on the modified CEI validate the effectiveness and practicality of the proposed method.

An optimal coordinated planning strategy for distributed energy station based on characteristics of electric vehicle charging behavior under carbon trading mechanism

Under the dual-carbon goal, the number of electric vehicle (EV) has surged, and the uncertainty of the temporal and spatial characteristics of the load has become prominent, which brings the challenge for higher requirements to the equipment composition of distributed energy station (DES) and performance of station-network. This paper proposes a collaborative planning method for low-carbon DES with networks, which is focusing on the characteristics of EV charging behavior. First of all, based on the quantitative analysis of the temporal and spatial distribution of charging load of four typical types of EV, including private vehicle, public vehicle, taxi and bus, the Monte Carlo method is used to construct the charging load modeling of EV in the region area. In addition, the low-carbon DES is modeled equipped with photovoltaic (PV) and power to gas (P2G) devices, and the Prim algorithm is adopted to search for the optimal network layout of energy transmission pipelines in the region area. Under carbon trading mechanism, aiming at the lowest annualized total cost of the regional station-network, a station-network collaborative planning modeling strategy for the capacity allocation of low-carbon DES with networks is established. Finally, the case study for a project in Beijing China is implemented on MATLAB, to prove the effectiveness of the method proposed in the paper. The time-of-use electricity price scheme changes the temporal and spatial characteristics of EV load. For example, more than 2 MW the EV load can be brought into the valley price range, which reduces the carbon transaction cost and energy purchase cost of DES by 50 thousand yuan almost when peak-valley electricity price difference is close to 1.2 yuan. At the same time, the growth of EV charging load(the penetration rate of EV can reach up to 20%) in the planning area has not increased the investment and operation-maintenance costs of DES equipment.

Coordinated Planning of Power Grids in Information Parks considering the Time-Space Transfer Characteristics of Data Center Loads

With the development of green energy, the penetration rate of new energy in the power grid is rising rapidly. Incorporating a large amount of new energy into the power grid will affect the power supply balance of the power grid, and even in severe cases will affect the safe and stable operation of the power grid. The information park has various small and medium data centers. The adjustable load of the data center can be transferred in time and space through the optical fiber and other communication networks, which can enhance the controllability of the power grid to a certain extent and promote the consumption of new energy. This paper proposes a collaborative planning method for information parks that considers the temporal and spatial transfer characteristics of data center loads, builds a load transfer model for data centers and builds a park power grid expansion model with the goal of minimizing the total cost of construction and operation. In this paper, an example of a park is used to verify the calculation example, and it is compared with other schemes to verify the feasibility of the method in this paper.

Research on collaborative planning of distributed resources and energy storage in regional integrated energy system

Aiming at the problem of high operation cost caused by low energy utilization of users in the region, a collaborative planning method of distributed resources and energy storage of regional integrated energy system is proposed. We designed the operation framework of the regional integrated energy system, and described the operation state of the equipment and the energy coupling relationship. According to the relationship between cooling, heating and power supply, the objective function is established with the lowest total operating cost, the highest reliability and the highest system emission reduction rate, and the control constraints are established for the total load in the system. We have established a collaborative ownership model for distributed resources and energy storage, and distributed energy supply and energy storage equipment in the system. It enables each energy supply and energy storage device to adjust the operating mode according to its own needs. So as to realize the reasonable supply of energy and the economical and optimal operation of all users. Taking three typical users in a park as an example, the results show that the operating costs of the three users are reduced by 15532.92 yuan, 5906.63 yuan and 24495.62 yuan respectively. The planning method can not only ensure the stable operation of the energy system, but also reduce the operation cost of users.

Study on Collaborative Planning Method for the Electricity-gas Storage Regional Integrated Energy System

Abstract In order to fully play the role of electricity and gas storage in the regional integrated energy system, a common planning method for regional integrated storage of electricity and natural gas is proposed. On this basis, mathematical models of energy storage, gas storage, electricity grid, gas grid topology and p2g were created to minimize the costs of expanding energy storage. Finally, based on current project data in Zhejiang Province, the economic benefits of joint planning of the electricity and gas storage system are examined, and the results show that an electric gas storage system can reduce system pressure and optimize equipment selection.

Power Grid Low Carbon Collaborative Planning Method Using Improved Cat Swarm Optimization Algorithm in Edge Cloud Computing Environment

The current power grid planning mostly realizes the calculation and analysis based on the factors of operation reliability or operation economy, but low-carbon green operation has become the main melody of power system development. Aiming to support the green and reliable operation of the power grid, this paper proposes a power grid low-carbon collaborative planning method based on improved cat swarm optimization algorithm. First, the carbon emission characteristics of the whole cycle of power grid construction are analyzed on the edge side, and a power grid planning model including environmental, economic, and reliability is constructed; on the cloud side, the cat swarm optimization algorithm is improved based on quantum mechanics and chaotic algorithm to achieve efficient solution to the power grid low-carbon planning model, which can support the stable and sustainable operation. Finally, the simulation experiment is realized based on IEEE 39 bus system. In this experiment, the construction cost and carbon emission of the proposed collaborative planning method are 23 million yuan and 2.28 t/MWh, respectively, which can reduce carbon emission while optimizing the construction cost and maintaining the low-carbon and stable operation.

Collaborative planning of resilient backbone grids and PMU placement for power systems

Constructing a resilient backbone grid can enhance the power supply capability and disaster resistance ability of power systems in some disaster scenarios. At the same time, it is of great importance to guarantee the global observability of power systems for real-time control and operation management during disasters. On the basis of these two requirements, a mixed integer linear programming (MILP) model is proposed to co-optimize backbone grid planning and PMU placement. Firstly, a backbone grid model is formulated with considering the node-importance and line-importance rate index. The disaster-resisting ability of power systems can be promoted by hardening important nodes and lines selectively. Meanwhile, according to the principle of the optimal PMUs placement (OPP), a method to map constraints of nodes and lines is proposed in order to guarantee the global PMU-observability of not only the whole network but also the backbone grid. Then, the solutions that do not satisfy the AC power flow will be removed by adding linear-cut constraints. Finally, the simulation was demonstrated on New England 10-unit 39-bus and IEEE 118-bus systems to prove the validity of the proposed method. The results show that the collaborative planning method can not only ensure the global observability of both the whole network and the backbone grid but also reduce the differentiated investment and PMU-placement cost.

Coordinated Development Based Grid-Source-load Collaborative Planning Method of Uncertainty and Multi-agent Game

When planning the power grid, it is necessary to obtain the optimal decision scheme according to the market behavior of different stakeholders. In this paper, the virtual game player "nature" is introduced to realize the deep integration of game theory and robust optimization, and a source network load collaborative planning method considering uncertainty and multi-agent game is proposed. Firstly, the planning decision-making models of different stakeholders of DG investment operators, power grid investment operators and power users are constructed respectively; then, the static game behavior between distributed generation (DG) investment operators and power grid investment operators is analyzed according to the transmission relationship of the three; at the same time, robust optimization is used to deal with DG. In this paper, we introduce the virtual game player "nature" to study the dynamic game behavior between the virtual game player and the power grid investment operator. On this basis, the dynamic static joint game planning model is proposed.

A collaborative planning method of distribution network including EV charging piles and Distributed Generations

With the growing penetration rate of distributed generations (DGs) and large number of unordered charging electric vehicles (EVs), the distribution network (DN) is facing more challenges than before. Therefore, the DN planning integrated of EVs and DGs is the primely problem. Firstly, an traffic network model and a distributed power supply output model are established to simulate the actual traffic network flow distribution through the principle of user equilibrium flow distribution. Secondly, an improved adaptive free search algorithm is proposed to coordinate site selection planning of EV charging pile and DG considering the factors of economy and users’ satisfaction of charging. Finally, taking the modified IEEE 33-node distribution network as an example, the proposed model and algorithm are simulated and verified. The simulation results show that the proposed model and programming method are feasible and effective.