A hybrid resilient static power system expansion planning framework

A comparative analysis of generation and transmission expansion planning models for power loss minimization

In general, power system expansion planning can be classified into three types such as generation expansion planning (GEP), transmission expansion planning (TEP) and distribution system expansion planning (DEP). Several researches have been performed in GEP and TEP. But, a huge research gap is still available in the topic of DEP. DEP can be classified into two optimization problems, namely substation expansion planning (SEP) and optimal feeder routing. This study attempts to solve real-time SEP problem for the power sector of Tamil Nadu, a state in India. Due to several design variables, the grouping of discrete and continuous variables frames the SEP problem as complicated. Hence, a promising optimization algorithm is essential to solve this complicated problem. The application of differential evolution (DE) algorithm has been presented to obtain the results with the sizes and sites of both the existing and proposed substations (SS) by satisfying the subjected constraints.KeywordsSubstation expansion planningDifferential evolutionTamil NaduLeast cost

Environmental concerns and limits on CO2 emissions entail expanding the capacity of renewable generation units. However, the increase in the renewable generation capacity can significantly impact the hosting power system voltage stability. Therefore, the consideration of voltage stability in the expansion planning problem is of an increasing importance. In this paper, we present a multi-stage low carbon voltage stability constrained generation and transmission expansion planning (G&TEP) model. The developed G&TEP model accounts for the investment and operation costs of generation units and transmission lines, as well as the load and wind curtailment costs, and determines the optimal installation year and location for transmission lines and generation units to meet the anticipated load demand increase. The voltage collapse proximity indicator (VCPI), which is a line voltage stability index based technique, is used to account for the voltage stability of the developed expansion plans. To this end, the VCPI is incorporated in the G&TEP model to guarantee an acceptable level of voltage stability for the developed expansion plans over the planning horizon. The effectiveness of the proposed framework is validated using numerical cases studies on the IEEE 24-bus RTS test system developed in General Algebraic Modeling System (GAMS) environment.

The transmission network expansion planning is necessary for supplying the future needs, considering load growth. Furthermore, in restructured environments, transmission lines provide the required infrastructure for creating a competitive environment. In recent years, there has been a significant advancement in storage technologies. This advancement leads to using energy storage systems to postpone the construction or replacement of transmission lines. Therefore, in this paper, the problems of transmission expansion planning and energy storage systems deployment are investigated simultaneously. Considering the presence of storage devices and their effect on network operation cost, in this paper, the operation cost is modeled as an independent objective function along with investment cost. Moreover, the problems of transmission and storage expansion planning are modeled as a tri-objective optimization problem with the objectives of reducing costs and increasing the social welfare index in the power market. The multi-objective shuffled frog leaping evolutionary algorithm is used to solve these problems. The presented model for expansion planning is implemented and analyzed on IEEE 24-bus test system in the presence and absence of energy storage systems, and the effect of change in the price of energy storage systems is studied. The results of this research show that as the technology advances and the storage costs decrease, energy storage systems can play a pivotal role in reducing expansion planning costs of the power network and improving market-based indices in the restructured environment.

Network Expansion Planning (NEP) plays a pivotal role in the development of power systems. It involves investing in new generating units and transmission lines to meet growing load demands and ensure a reliable electricity supply. Historically, the incorporation of demand response (DR) factors in power system planning has been limited due to their complexity and evaluation challenges. However, with advancements in smart grid technologies, increased integration of renewable energy, and the emergence of flexible loads, the inclusion of DR models has become crucial for enhancing power system reliability. While numerous studies have delved into generation and transmission expansion planning (GTEP) problems, only a few have explored the integration of network payment schemes and DR within the GTEP framework. This study proposes a multi-annual generation and transmission expansion planning model that incorporates three network payment schemes and two DR techniques. The objective is to secure financing for new generating units and transmission lines while minimizing the overall system cost. The proposed models employ the mixed-integer linear programming (MILP) optimization method and are validated using a modified IEEE 24-bus system. Two key system performance metrics, namely the network congestion index and network saturation index, are employed to assess system reliability and effectiveness. These results demonstrate that the integration of network payment schemes and DR techniques into the generation and transmission expansion planning model can lead to a cost reduction of 32.1% as compared to base model, reduced power system congestion and saturation (22.1%, 2.73%) to allow more renewable energy integration and enhanced power system reliability and operational flexibility.

In this two‐article set, a new multi‐level framework is presented for coordination of generation and transmission expansion planning (G&TEP) in liberalised electricity markets. Part I is mainly dedicated to mathematical modelling of the G&TEP problem. The main aims of the proposed framework are not only to develop a holistic model for the G&TEP problem, but also to evaluate impacts of expansion plans on market participants’ strategic behaviours. To do so, the proposed methodology is decomposed into a planning master problem and an operating slave problem. In the slave problem, the first level indicates market participants’ strategic interactions and the second level represents a pool‐based electricity market. In the master problem, an independent system operator model is described to coordinate decentralised generation expansion planning in the third level with centralised transmission expansion planning in the fourth level. In addition, the offered framework uses a well‐founded information‐gap decision theory to minimise risks of planning arising from severe uncertainties. The newly developed framework is formulated as a non‐convex mixed‐integer non‐linear optimisation problem. Hence, a novel two‐stage multi‐dimensional melody search algorithm is widely employed to determine the best solution. The profitableness of the developed framework is illustrated in part II of this two‐article set.

The two previous chapters describe and analyze the generation expansion planning (GEP) problem as well as the joint generation and transmission expansion planning (G&TEP) problem, both from the perspective of a central planner that determines the expansion plan that is most beneficial for the system as a whole. Unlike the problems in those two chapters, referred to as centralized expansion problems, this chapter addresses a market-oriented generation investment problem, in which a single power producer competing in an electricity pool seeks to maximize its own profit through making the best generation investment decisions. It is important to note that a market-oriented decision-making problem is generally more complex than a centralized one, since the former is subject to additional uncertainty related to the behavior of other producers (rivals). In this chapter, we provide and analyze different investment models that progressively incorporate additional details with emphasis on solution techniques.

Community energy projects in the context of generation and transmission expansion planning

Composite generation and transmission system expansion analysis should take into account both economic considerations and adequacy requirements. An optimum expansion plan should achieve the minimum total investment, operation and damage cost. A minimum cost assessment method for composite system expansion planning, which can be used to consider generation expansion and transmission expansion simultaneously, is presented. The minimization model proposed to incorporate both operating and outage costs can recognize different customer damage functions at different load buses and includes the duration of the simulated contingency system states . A computer program based on the presented method has been developed to provide a set of line, load bus, generator bus and system indices which can be used to select optimal expansion plans at different load growth levels. Case studies in which the method is applied to the IEEE Modified Reliability Test System indicate its effectiveness.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Due to the unbundling of power generation and transmission in the restructured power system, the coordination between generation expansion planning and transmission expansion planning has become a new challenge for both generation companies and transmission companies. In this article, a single-stage deterministic model is proposed to study the strategic interaction between generation and transmission enterprises. The Cournot model is used to simulate the expansion behaviours for generation and transmission enterprises. Equilibrium is obtained using the approach for the mixed complementarity problem, and the proposed model is applied to a three-bus system.

Generation and transmission expansion planning with high penetration of wind farms considering spatial distribution of wind speed

Experience with the transmission expansion planning of a longitudinal power system is reported. To reach an optimal choice among several feasible expansion plans, indices such as maximum power transfer limits, fault currents, transient stability, system losses, and cost, which have been widely used by utilities, are computed to compare the relative merits of these alternatives. In view of past experience with low-frequency oscillations taking place in the study system, oscillatory stability of the power system under each expansion plan is examined in detail by means of eigenvalue-eigenvector analyses. Recommendations are made with regard to future expansion plans on the basis of the present study.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper presents the generation and transmission expansion planning (GTEP) in electricity and gas networks by considering their resilience against floods and earthquakes. These networks supply electricity, heat, and gas consumption energies as a multi‐carrier microgrid. The scheme is expressed in the form of bi‐level optimization, the upper level of which is the minimization of generation and transmission planning cost (total investment cost and expected operating cost) in the mentioned networks constrained to the investment budget and the planning model of the mentioned elements. Lower‐level formulation minimizes the total expected annual operating cost of these networks and the expected outage cost of electricity, heat, and gas consumers in the event of floods and earthquakes. This formulation is bound by the power flow equations of electricity and gas networks, the operation and resilience constraints of the networks, and the limitation on generation capability. In this problem, the expected energy not‐supplied and the outage cost during natural disasters are considered resilience indicators. Next, a single‐level model for the proposed design is extracted from the Karush–Kuhn–Tucker (KKT) method. The basic requirement of this method is the convexity of the lower‐level constraints. For this purpose, first, a linear approximation model is obtained for the lower‐level constraints of the problem. Furthermore, stochastic optimization is adopted to model the uncertainty of load, renewable power, and network equipment availability during floods and earthquakes. Finally, the extracted numerical results confirm the capability of the proposed scheme in improving the operation and resilience of the mentioned networks using optimal generation and transmission planning.

The shipboard power system of an all-electric ship can be characterized as an isolated microgrid system with limited capacity and no support from external grid. Its resilience problem is more prominent when confronting some extreme events, compared to land-based power system. Currently, there are few researches concerning about the shipboard power system's resilience. It's urgent to fill the comprehensive evaluation need of ship power system's resilience. This paper proposes a comprehensive evaluation framework for all-electric ship's power system resilience. Furthermore, evaluation metrics of shipboard power system resilience comprising resistance, security, self-healing ability, environmental friendless and personnel quality are established. Based on Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation methods, a comprehensive assessment framework is performed to evaluate the resilience of shipboard power system. Numerical results demonstrate that the proposed method can provide guidance for all-electric ship's fault recovery and resilience improvement strategy.

Generation expansion planning is one of the major modules of power system planning studies, normally performed for the next 10-30 years. Optimal generation expansion planning is a non-linear and limited optimization problem. All solutions are compared to each other in order to reach final optimal solution. Some simplifications are made to reduce the problem dimensions which will not lead to unreal results. In this paper, WASP software package, one of the well known power expansion planning softwares, is used to optimize lran generation expansion planning. For modeling the power system, WASP uses the probabilistic simulation, while for optimization the dynamic programming method is used. In this paper, the generation system expansion planning is performed from 2009 till 2024 (a duration of 16 years). Finally, the sensitivity analysis is performed on the capital cost and the fuel cost of power plants.