Multistage Expansion Planning Research Articles

Rational capacity investment for renewable hydrogen-based steelmaking systems: A multi-stage expansion planning strategy

To improve energy efficiency and mitigate environmental impact, the iron and steel industry (ISI) is responsible for implementing a low-carbon transition. The renewable hydrogen-based steelmaking system (RHSS) has emerged as an innovative energy system in the pathway of reducing the carbon footprint of ISI. Nonetheless, the sustainable development requirements of RHSS emphasize the critical need for well-planned capacity investments to boost its economic viability. This study introduces a novel planning strategy for RHSS referred to as a multi-stage expansion planning (MSEP) model, which is aimed to minimize the levelized cost of crude steel over the planning horizon from 2025 to 2050 (EU climate neutrality year). The MSEP model incorporates the construction sequence and dynamic techno-economic parameters to formulate investment strategies that adapt to changing system requirements and external conditions over the planning horizon. To address the complexity of the MSEP model, a rolling-horizon approach (RHA) is proposed to solve the model sequentially while integrating updated information. The proposed approach is benchmarked against both the single-stage approach and the perfect-sight approach through case studies. The numerical results show that the proposed RHA (i) guarantees a rational capacity investment strategy for RHSS considering the construction sequence and dynamic techno-economic parameters over multiple planning stages; (ii) achieves a reduction in the levelized cost of crude steel by approximately 50% relative to the single-stage approach; (iii) resolves the convergence issues encountered with the perfect-sight approach while achieving an optimal solution in a reasonable time frame. Additionally, sensitivity analysis evaluates the uncertainties of multiple factors on the planning results, while the robustness analysis confirms the applicability and adaptability of RHA across various scenarios.

Multi-stage expansion planning of energy storage integrated soft open points considering tie-line reconstruction

With the rapid development of flexible interconnection technology in active distribution networks (ADNs), many power electronic devices have been employed to improve system operational performance. As a novel fully-controlled power electronic device, energy storage integrated soft open point (ESOP) is gradually replacing traditional switches. This can significantly enhance the controllability of ADNs. To facilitate the utilization of ESOP, device locations and capacities should be configured optimally. Thus, this paper proposes a multi-stage expansion planning method of ESOP with the consideration of tie-line reconstruction. First, based on multi-terminal modular design characteristics, the ESOP planning model is established. A multi-stage planning framework of ESOP is then presented, in which the evolutionary relationship among different planning schemes is analyzed. Based on this framework, a multi-stage planning method of ESOP with consideration of tie-line reconstruction is subsequently proposed. Finally, case studies are conducted on a modified practical distribution network, and the cost–benefit analysis of device and multiple impact factors are given to prove the effectiveness of the proposed method.

A Bi-Level Framework for Expansion Planning in Active Power Distribution Networks

This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare. The expansion plans consider the investments in DER owners’ assets as well as variety of network assets in which the profitability of DER owners’ investment is guaranteed. The Karush-Kuhn-Tucker optimality conditions and the strong duality theory are employed through which the model is converted to a mixed integer linear programming optimization problem. The implementation of the suggested model on the 24-bus and 86-bus distribution test systems validates its performance and efficacy in making cost-effective planning decisions.

Multi-Stage Expansion Planning of Distribution Network Considering Distributed Power Generation

With the gradual increase in the penetration rate of distributed power sources, in view of the planning problem of coordinating the location and capacity of distributed power sources with the grid frame and transformers of the distribution network, a distribution network that takes into account distributed power sources is proposed. Aiming at the lowest cost of investment, maintenance, energy production, energy loss, and load loss penalty, and considering the power flow constraints, planning and operation constraints of each planning stage, a multi-stage expansion planning model for the distribution network is established. The mixed-integer linear programming algorithm is used to solve the problem, and the optimal planning scheme at each stage is obtained. The simulation results show that the multi-stage expansion planning method for coordinating distributed power and distribution network proposed in this paper can prevent the problems of isolated nodes and transmission nodes, improve the reliability of the planning scheme, and have good economic benefits.

Multistage Expansion Planning of Active Distribution System Network

Introduction: This paper presents an approach for multistage expansion planning of the active distribution system network problems by considering multiple strategies based on system investment cost, including renewable energy sources based on distributed generation units, operational cost, and reliability. Objective: The developed framework model fulfills the prospects related to techno-economical and reliable multistage expansion planning of active distribution system network for the sustainable development of electric power system. Methods: The mathematical model of the multi-objective function has been developed with the investment decision variables to compute the investment cost. The reliability of the active distribution system network is evaluated in non-supplied energy costs under contingency conditions with and without DGs. Result: The result validates the constraints associated with planning, investment decisions, power quality, and reliability of the system. Conclusion: This study also demonstrates the improvement in per unit (p.u.) voltage of bus nodes for each period of network expansion with DGs over the planning horizon. The proposed method is tested and validated on a 54-bus, 11 kV long-term active distribution network.

Transmission Network Expansion Planning Considering Optimal Allocation of Series Capacitive Compensation and Active Power Losses

This paper presents a modeling and solution approach to the static and multistage transmission network expansion planning problem considering series capacitive compensation and active power losses. The transmission network expansion planning is formulated as a mixed integer nonlinear programming problem and solved through a highly efficient genetic algorithm. Furthermore, the Villasana Garver’s constructive heuristic algorithm is implemented to render the configurations of the genetic algorithm feasible. The installation of series capacitive compensation devices is carried out with the aim of modifying the reactance of the original circuit. The linearization of active power losses is done through piecewise linear functions. The proposed model was implemented in C++ language programming. To show the applicability and effectiveness of the proposed methodology several tests are performed on the 6-bus Garver system, the IEEE 24-bus test system, and the South Brazilian 46-bus test system, presenting costs reductions in their multi-stage expansion planning of 7.4%, 4.65% and 1.74%, respectively.

Multistage Expansion Planning of Integrated Biogas and Electric Power Delivery System Considering the Regional Availability of Biomass

Centralized biogas plant (CBP) provides an attractive solution to the energy supply for district heating, electric loads, and residential cooking in remote areas via a local biogas delivery network. To overcome the challenges of biomass availability for CBPs, an integrated expansion planning model is proposed in this paper. The model makes investment decisions on the sequential planning of integrated electric power distribution and biogas delivery networks and uses the constrained biomass transportation network to optimally determine CBP locations in the integrated network. The proposed approach also considers the biomass availability and the cost of biomass supply in the integrated model. The proposed multistage stochastic planning problem makes investment decisions considering the gradual realization of uncertainties as loads grow and biomass is made available. The polyhedral approximation method is applied to convert the proposed mixed-integer second-order cone programming (MISOCP) problem to a mixed-integer linear programming (MILP) problem for making the problem more tractable for large-scale cases. The effectiveness of the proposed integrated model is validated using an 8-node and a 24-node test system.

Smart distribution grid multistage expansion planning under load forecasting uncertainty

The optimal distribution system planning (ODSP) is a complicated problem with multi-objective function and multi-constraints. The complexity of the problem is increased in smart distribution grids with uncertainties in both load and generation. In this study, problem of optimal smart distribution grids multistage expansion planning is presented in which reinforcement or installation time, capacity and location of MV substation and DER are taken into consideration. The binary global search optimization algorithm is proposed to solve the ODSP problem. The proposed cost function considers the capital investment, operation and the levelized energy cost (LEC) of each energy source. Loss characteristic matrix has been used for locating of MV substation and DER. The aspect of modeling under load growth uncertainty and multistage planning and multiple objective functions which are related to ODSP problem are considered in an integrated model. The multistage planning procedure is proposed to consider the pseudo-dynamic behavior of planning and continuing growth of demand. Load uncertainty is represented by point estimated approach and the results are compared with the Monte Carlo simulation (MCS). Presented methodology has been tested from base to long-term period on distribution network. The obtained results confirm the ability and validity of the presented method.

On optimal multistage electric power distribution networks expansion planning

The optimal expansion planning of electric power distribution network to meet system load growth and overcome to pseudo dynamic behavior of network parameters considering a large number of constraints is a hard satisfactory multiobjective optimization problem. This paper implements new developed Imperialist Competitive Algorithm (ICA) for the optimal expansion planning of distribution network. The topology of medium voltage (MV) distribution network as backbone of electric power distribution systems is designed by optimal sizing, siting and timing of medium voltage network components such as HV substation and MV feeders’ routes. A multistage expansion planning is proposed to consider dynamic behavior of the system parameters asset management and geographical constraints. In order to reach the global solution an efficient coding is developed for ICA parameters. The Greedy algorithm is used to solve the minimum spanning tree problem to construct a radial configuration of the mesh network. At each stage of the problem the results are fully illustrated either by figures or by tables. A sensitivity analysis is used to show the robustness of the results with respect to ICA parameters variation. The obtained results are compared with GA as well known heuristic optimization tool. The efficiency and capability of the methodology has been tested on an under developed relatively large-scale distribution network.

Multistage expansion planning of generation and interconnections with sustainable energy development criteria: A multiobjective model

A novel multiobjective, multiarea and multistage model to long-term expansion planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a “bottom-up” energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewables, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The proposed model considers three objectives belonging to sustainable energy development criteria such as: (a) the minimization of investments and operation costs of power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; (b) minimization of Life-Cycle Greenhouse Gas Emissions (GHG); and (c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM – Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework.

Robust Optimal Design in Multistage Expansion of a Gas Turbine Cogeneration Plant Under Uncertain Energy Demands

In designing cogeneration plants, the estimation of energy demands is an important work. However, many conditions under which energy demands are estimated have some uncertainty at the design stage. Therefore, designers should consider that energy demands have some uncertainty, evaluate the robustness in the performance under uncertain energy demands, and design plants rationally in consideration of the robustness. The authors have developed a robust optimal design method based on the minimax regret criterion for the single-stage planning of energy supply plants. In this paper, the method is extended for the multistage expansion planning. Under uncertain energy demands increasing stepwise, equipment capacities and utility contract demands as well as energy flow rates for each expansion period are determined in consideration of their sequential relationships to minimize the maximum regret in the annual total cost and satisfy all the possible energy demands for all the expansion periods. Through a case study on a gas turbine cogeneration plant for district energy supply, features of the economic robustness and the robust optimal design are clarified in relation to the uncertainty in energy demands and the numbers of years for the expansion periods.

Robust Optimal Design in Multistage Expansion of Energy Supply Systems.

A robust optimal design method based on the minimax regret criterion is proposed for multistage expansion planning of energy supply systems. Under uncertain energy demands increasing stepwise, equipment capacities and utility contract demands as well as energy flow rates for each expansion period are determined in consideration of their hierarchical relationships to minimize the maximum regret in the annual total cost and satisfy all the possible energy demands for the whole planning period. This optimization problem is formulated as a kind of multilevel linear programming problem, and its solution is derived by repeatedly evaluating upper and lower bounds for the optimal value of the maximum regret. Through a numerical case study on a cogeneration system for district energy supply, features of the economic robustness and multistage expansion planning are clarified in relation to the uncertainty in energy demands and the number of years for expansion periods.

Optimal Multistage Expansion Planning of a Gas Turbine Cogeneration Plant

A multistage expansion planning problem is discussed concerning a gas turbine cogeneration plant for district heating and cooling using an optimization approach. An optimal sizing method for single-stage planning proposed by the authors is extended to this case. Equipment capacities and utility maximum demands at each expansion stage are determined so as to minimize the levelized annual total cost subject to increasing energy demands. A numerical study on a simple-cycle gas turbine cogeneration plant to be installed in a district development project clarifies the relationship between optimal expansion planning and energy demand trend, and shows the effectiveness of the proposed method.