Expected Energy Not Supplied Research Articles

Economic dispatch in grid-connected and heat network-connected CHP microgrids with storage systems and responsive loads considering reliability and uncertainties

Combined heat and power microgrids (CHP MGs) are energy efficient solutions for simultaneous supply of electric and thermal demand in a neighborhood and play a very important role in sustainable cities and societies MGs have energy management systems (EMSs) that aim to minimise their operation cost and include two modules; unit commitment module that determines commitment status of generating units and schedule of storage systems and dynamic economic load dispatch (DELD) module that determines the schedule of committed units and storage systems In this research, DELD in grid-connected and heat network-connected MGs with CHP units, boilers, microturbines, photovoltaic (PV) and wind units, electric and thermal storage systems, adjustable electric and thermal demand is formulated as a mixed-integer linear problem, while the reliability of the MG as well as uncertainties of PV and wind power, electric and thermal demand have been considered Monte Carlo Simulation and stochastic method is used to model the uncertainties In order to have a convex model in which the achievement of the global optimum is guaranteed, the non-convex feasible operating region (FOR) of CHP units is transformed into two convex feasible operating regions Moreover, effect of grid and heat network on MG operation and the sensitivity of MG operation cost to electricity and heat price are investigated The results show the effect of reliability and uncertainties on dispatch of resources and MG operation cost The results show that for the studied MG, with consideration of reliability, the operation cost increases by 14%, while.89, 10% of the cost is for Expected energy not supplied (EENS) cost and the remaining 90% is for other MG costs.

Generation expansion planning considering efficient linear EENS formulation

Power system equipment outages are one of the most important factors affecting the reliability and economy of power systems. It is crucial to consider the reliability of the planning problems. In this paper, a generation expansion planning (GEP) model is proposed, in which the candidate generating units and energy storage systems (ESSs) are simultaneously planned by minimizing the cost incurred on investment, operation, reserve, and reliability. The reliability cost is computed by multiplying the value of lost load (VOLL) with the expected energy not supplied (EENS), and this model makes a compromise between economy and reliability. Because the computation of EENS makes the major computation impediment of the entire model, a new efficient linear EENS formulation is proposed and applied in a multi-step GEP model. By doing so, the computation efficiency is significantly improved, and the solution accuracy is still desirable. The proposed GEP model is illustrated using the IEEE-RTS system to validate the effectiveness and superiority of the new model.

Multi-objective resilient-constrained generation and transmission expansion planning against natural disasters

In this paper, the resilient-constrained generation and transmission expansion planning (RCGTEP) considering natural disasters such as earthquake and flood is presented. The proposed model contains a two objective problem that the first objective function minimizes the construction and operation costs of resiliency sources (RSs) and, in the second objective function, the minimization of the expected energy not supplied (EENS) due to the outage of the system against the mentioned natural disasters is formulated. Also, the proposed model is constrained to linearized AC optimal power flow (AC-OPF) equations, the planning and operating of RSs constraints such as generation units, hardening transmission lines, parallel and series FACTS devices, resiliency constraints and power system angular stability against earthquakes and floods in the presence of critical and non-critical loads. In order to achieve the best compromise response, the RCGTEP single-objective problem is formulated based on the ε constraint-based Pareto optimization. In addition, this model has the uncertainty of RSs availability against natural disasters, so stochastic programming is used for RCGTEP. Then, the Benders decomposition (BD) method is used to solve the proposed problem and achieve the optimal solution in the shortest possible time. Finally, by implementing the proposed model on an IEEE standard transmission network, the numerical results confirm the capability of this method in improving the economic, operation, angular stability and resiliency indices of the power system simultaneously.

Multi-objective stochastic operation of multi-microgrids constrained to system reliability and clean energy based on energy management system

The paper presents the multi-objective operation of multi-microgrids (MGs) based on an energy management system (EMS) to achieve MGs with high reliability, clean energy, and optimal operation mode. The proposed problem minimizes the expected operating cost of the MG and non-renewable energy sources (NRESs), the expected energy not-supplied (EENS) as the reliability index, expected environmental emission level, and voltage deviations function (VDF) in different objective functions. Furthermore, the scheme is constrained to AC optimal power flow (AC-OPF) equations in MGs, reliability constraints, and mathematical models of power sources and active loads (ALs). Also, stochastic programming based on the combined Monte Carlo Simulation (MCS) method and Kantorovich technique is utilized to model uncertainties of the load, energy price, RESs generation power, energy demand of some ALs, and availability of MGs equipment. Moreover, the problem is converted into a single-objective problem using the Pareto optimization theory based on the ε-constraint method. The hybrid grey wolf optimization (GWO) and Teaching-Learning-based Optimization (TLBO) is then used to reach a reliable optimal solution. Finally, the suggested strategy is simulated on a standard system, where the numerical results verify capabilities of the scheme in improving operation and reliability of multi-MGs along with reducing environmental emission level.

Locational marginal price computation in radial distribution system using Self Adaptive Levy Flight based JAYA Algorithm and game theory

Abstract This study presents a computational approach to compute locational marginal price (LMP) at distributed generation (DG) buses in an electric power distribution system using self-adaptive levy flight based JAYA algorithm and proportional nucleolus theory (PNT). This method provides financial incentive to DG owners based on their contribution in reliability improvement, loss and emission reduction. In this study expected energy not supplied (EENS) is used for measuring the reliability of a given radial distribution network. This method is implemented on 38 bus distribution system under MATLAB environment to compute LMP values at each DG as per its contribution towards reliability improvement, loss reduction and emission reduction. It is found from the study that reliability has been improved, losses and emissions of system were reduced by providing proper financial incentives to DG owners. The proposed method can be utilized by a distribution company (DISCO) to operate network optimally and to estimate state of network.

Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty

A novel stochastic multi-area unit commitment (MAUC) framework is proposed to coordinate scheduling of generators and tie lines. In consideration of the randomness and volatility characteristics of wind energy, a worst-case based scenario selection method (SSM) based on the peak and valley shaving of the system, the ramping-up/down rates of net load, and the dispersion of uncertainty factors is presented to reduce the number of scenarios and improve the robustness of unit commitment (UC) schemes. Regarding the balance of efficiency and flexibility of tie-line scheduling, tie-line operation modes are established on the basis of the tie-line load rate (TLLR). Besides, the number of reversals of tie-line power flow directions during the entire scheduling period is also modeled. By linearizing the tie-line operation modes’ equations, the MAUC can be converted into a mixed-integer linear programming (MILP) formulation. Case studies show that more wind energy can be consumed by connecting power systems through tie lines and coordinating scheduling of generators and tie lines. Expected energy not supplied (EENS) of scenario reduction techniques based on the clustering method, i.e. k-means, Gaussian mixture model (GMM) and Fuzzy C-means (FCM), are 147%, 38%, and 130% higher than that of the SSM.

An Effective Algorithm for MAED Problems with a New Reliability Model at the Microgrid

This paper proposes a new framework for multi-area economic dispatch (MAED) in which the cost associated with the reliability consideration is taken into account together with the common operational and emission costs using expected energy not supplied (EENS) index. To improve the reliability level, the spinning reserve capacity is considered in the model as well. Furthermore, the MAED optimization problem and non-smooth cost functions are taken into account as well as other technical limitations such as tie-line capacity restriction, ramp rate limits, and prohibited operating zones at the microgrid. Considering all the above practical issues increases the complexity in terms of optimization, which, in turn, necessitates the use of a powerful optimization tool. A new successful algorithm inspired by phasor theory in mathematics, called phasor particle swarm optimization (PPSO), is used in this paper to address this problem. In PPSO, the particles’ update rules are driven by phase angles to essentially ensure a spread of variants across the population so that exploitation and exploration can be balanced. The optimal results obtained via simulations confirmed the capability of the proposed PPSO algorithm to find suitable optimal solutions for the proposed model.

Reliability based modeling of hybrid solar/wind power system for long term performance assessment

This paper is concerned with reliability based long-term performance assessment of hybrid solar/wind power system. In particular, an analytical expression is obtained for the theoretical distribution of the power output of the hybrid system by taking into account the reliability values of renewable energy components. An expression for the expected energy not supplied (EENS) is also derived and used to compute the energy index of reliability (EIR) that is directly related to EENS. Because the derived expressions involve reliability values which are related to mechanical states of the renewable energy components, the results enable us to evaluate properly the performance of the hybrid system. A numerical example is included to illustrate the results.

Reliability Analysis and Improvement of Debre Berhan Power Distribution Network by Using Fuzzy Logic Optimization Technique

This paper presents determination and allocation optimal number of sectionalizer switches using fuzzy based approach to improve the reliability of Berhan power distribution network. My intention to present in this study on the reliability assessment and method of improving reliability is that Debre Berhan power distribution network has frequent instructions. To improve customer reliability of power distribution system different methods can be used. Thus to complete this study MATLAB Simulink models of distribution network initial and optimal number of sectionalizer switch allocation are developed. Sheno 15kV feeder of the distribution network is selected for simulation studies to test the efficiency of the proposed approach. Simulation studies using ETAP software are carried out reliability indies of distribution network with and without optimal number of switch allocation. The simulation results show optimal allocation of sectionalizer switches improve the reliabity indices such as SAIFI, SAIDI and expected energy not supplied (EENS) and evaluates the reliability of Debre Berhan power distribution network using analytical techniques, software simulation and level of optimization achievable through the application optimal placement of switches. At the result of optimal placement of sectionalizers switches for sheno 15kV feeder SAIFI is improved by 12.76% and SAIDI are 41.61%. From the test result the proposed technique presents better interruption cost in comparison that of existing system 64,806.06$/yr. to 57,346.57$/yr. (which is 11.5% reduction) along with improvement in reliability indices and expected energy not supplied (EENS) was improved from 17828.014MWh/yr. to1533.75MWh/yr. (91.04%).

A Novel Multi-Objective Based Reliability Assessment in Saudi Arabian Power System Arrangement

In a smart grid power system, reliability performance plays a crucial factor and requires additional focus. Moreover, the integration of Battery Energy Storage (BES) scheme, Solar Photovoltaic (SPV) and wind system in the smart grid system provide significant proficiency and reliability to the utilities. However, the grid coordination with the PV and other resources tends to cause major problems such as power interruption or else power outage. The outage of the power in the grid can cause power loss to the distribution system. Therefore, the novel reliability valuation of the smart grid system is developed for exaggeration of the SPV, wind and BES utilities based on the grid incorporation in Saudi Arabia. Furthermore, a novel Hobbled Shepherd Optimization (HSO) for boost converter control and Multi-Objective Based Golden Eagle (MOGE) algorithm for inverter control is proposed. The execution of this work has been done in MATLAB/Simulink. The simulation outcomes show that the projected method has attained the finest Total Harmonic Distortion (THD) and power loss. Also, the optimal reliability improvement has achieved by the projected methods while compared with the conventional methods in terms of Loss of Load Expected (LOLE), Loss of Load Probabilities (LOLP) and Expected Energy Not Supplied (EENS).

Operation Strategies for Coordinating Battery Energy Storage with Wind Power Generation and Their Effects on System Reliability

The variability of wind power generation requires the allocation of a flexible energy reserve which is capable of compensating for possible imbalances between the load and generation. To reduce the variability of wind power generation and loss of load in generation deficit, we propose operation strategies for coordinating battery energy storage with wind power generation. The effects of the operation strategies on system reliability are evaluated by the developed computation model that represents the main aspects and operation limitations of the batteries. The performance evaluation of the power system is based on the composite reliability indices of loss of load probability (LOLP) and expected energy not supplied (EENS), which is calculated through sequential Monte Carlo simulation. Tests are performed by the developed model with a tutorial system consisting of five busbars and the IEEE RTS system. The results show that the use of large-scale batteries is an alternative to physically guarantee the wind power plants and to act as an operation reserve to reduce the risk of loss of load.

Reliability assessment and congestion management of power system with energy storage system and uncertain renewable resources

The high penetration of Renewable Energy Sources (RES) makes the power system unreliable due to its uncertain nature and to deal with this uncertainties installation of an Energy Storage System (ESS) is suggested. In this paper, the quantifying impact of ESS capacity on power system network reliability and relieving the congestion is analyzed. The proposed reliability assessment and congestion relief problem is formulated by considering generation cost and demand interruption cost for N-1 contingency criteria. The proposed algorithm manages the optimal charging and discharging of ESS to mitigate the uncertainties associated with RES and relieving the congestion. The impact of ESS capacity on reliability indices Expected Energy not Supplied (EENS) and Expected interruption Cost (ECOST) for Generating Companies (GENCOs), Transmission Companies (TRANSCOs), customers, and entire power system are calculated. The appropriate size of ESS is selected by the trade-off between investment cost of ESS and percentage change in EENS and ECOST value for the entire power system, GENCOs, TRANSCOs, and customers. The effectiveness of the proposed approach is tested on the modified IEEE RTS 24 bus system. The problem is modeled in the Generic Algebraic Solver (GAMS) environment and solved using CONOPT as an NLP solver.

Composition Assessment of a Power Distribution System with Optimal Dispatching of Distributed Generation

Increasing penetration of distributed generation (DG) is imminent in the new age of power distribution networks, which are smarter than the conventional grids. They enable the integration of DG into the power distribution network. This paper presents an assessment methodology for determining the optimal capacity and location of DG to ensure high reliability in a radial distribution network. The approach considers cost and the impact of aging on the DG and network topology for interconnection using genetic algorithm, which is a robust technique with wide solution space searchability and can potentially find global optima with fewer chances of getting trapped into local optima. A case study is simulated using three different scenarios to evaluate the impact of DG interconnection on the 13.8 kV power distribution network. The scenarios comprise of situations without any DG, with DG interconnection and optimization of DG interconnection. The case study shows that the penetration of DG increases the reliability of the distribution network while reducing the expected energy not supplied (EENS). Although, the difference between EENS in the optimized DG integration and non-optimized DG integration is not very significant in a small network, however, it becomes apparent with the aging curve that optimized allocation of DG possesses significant benefits.

Study of Reliability of Power Distribution System and Improvement Options at Awash7 kilo Substation, Ethiopia

This paper presents a study of reliability of power distribution system and improvement options at Awash7 kilo substation in Ethiopia. Basically, power distribution reliability has been a major challenge in Awash7 kilo city. The existing substation has encountered frequent and long power interruptions problems. The interruptions are caused mainly by the short circuit (SC) and earth fault (EF). There are also planned outages for operation and maintenance purpose. Thus, the objective of the study is to assess the reliability of the existing distribution system and suggest solutions for reliability improvement in heuristic techniques. To limit the scope of the study, 15 kV Awash7 kilo city feeder of the substation has been chosen for the reliability improvement measures. In the study, four different mitigation scenarios have been assessed using the heuristic method to improve the system reliability. From the mitigation scenarios with the lowest SAIDI, SAIFI and Expected Energy Not Supplied (EENS) has been selected as an optimal one. The simulation results have been done with the help of Electrical Transient Analysis Program (ETAP 16.0) software. The result of this study reveals that the overall reliability of Awash7 kilo city feeder has been improved by 86%, 85.4% and 92.94% for SAIFI, SAIDI, and EENS respectively as compared with the existing system by incorporating a mitigation technology in to the network model. The economic analysis shows that the selected solution results in a cost saving of 20,229.47 USD per year from the unsold energy of one feeder only with three years payback period investment for the implementation of the reliability mitigation technology.

Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks

Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curtailment optimization problem. Best performances regarding optimal value and processing time were obtained using a PSO algorithm, qualifying the technique as the most appropriate for this study. To assess the methodology, the CIGRE MV distribution network benchmark was used, assuming dynamic load profiles during an entire week. Results show that it is possible to determine the optimal unattended power of the system. This way, improvements in the minimization of the expected energy not supplied (ENS) as well as the System Average Interruption Frequency Index (SAIDI) at specific hours of the day were made.

Value of Loss Load Analysis of Java-Bali System Based on Macro Economic Data

Industrial and business sectors have big influence to gross domestic product in some regions (GDP). Beside that, GDP is influenced by electricity consumption. That statement is the reason why value of loss load (VOLL) had to be calculated. This research calculates VOLL for getting the value of outage cost, efficiency and productivity industrial and business sector in each Area Pengaturan Beban (APB) and in entire Java-Bali region. VOLL is calculated by macroeconomic analysis because this method has more time efficiency than survey analysis. VOLL forecasting in 2016-2023 are calculated too in this research. After that, the outage cost forecasting in hierarchical level 1 (HL 1) can be gotten if expected energy not supplied (EENS) from HL 1 is calculated. Before EENS calculation is held, analysis of another reliability indices such as loss of load expectation (LOLE) and loss of load probability (LOLP) were calculated. The calculation results show that VOLL in 2017 is 35,100.67 Rp/kWh and EENS in HL 1 is 7.25 MWh. Total outage cost from calculation is 289 million rupiahs.

Economical and Technical Assessment of Hybrid Renewable Energy Systems for Optimal Performance Applied in Hurghada, Egypt.

This paper deals with economic and technical evaluation of the hybrid power system which is fed six-megawatt load located in a city in Egypt called Hurghada. There is two types of economical evaluation. The first type is Economical evaluation which has two parts, the first part is cost estimation to know the price of generating power of the hybrid system in every season to reveal the lowest and the highest cost of the power unit in every season and The second part is an economic load dispatch for the six-megawatt load to know which hybrid system topology gives the required power at low cost and which topology gives the required power at a higher cost, economic load dispatch made for eight possible hybrid system topologies for four hybrid system units. The technical evaluation made by studying generating reliability indices Loss of Load Probability (LOLP), Loss of Load Expectation, (LOLE) Expected Energy Not Supplied (EENS) in every season of the year to know which season is more reliable to supply power to the load area. Studying generating reliability at the probabilities for generating units to achieve reliability index calculation according to the load duration curve of the load area in one year. The evaluation made by simulation of the hybrid system in MATLAB Simulink in every season and optimize power by using the Genetic Algorithm and Partial Swarm Optimization to ensure economical and technical optimal performance of the hybrid system.

Optimal scheduling of resources for a price-maker distribution company in electricity markets considering network component failures

Electricity generation and storage resources, demand-side participation, along with modern communication infrastructure, have led distribution companies (DisCos) to increasingly play a strategic role in wholesale electricity markets. Although these resources have increased the security of power supply in modern distribution networks, this is still affected by random failures of distribution and sub-transmission network components. Therefore, the main issue that needs to be addressed is how the random failure of the components of the network has an impact on the performance of the strategic DisCos. In this paper, a new framework is proposed to assist a strategic DisCo to determine the strategy of purchasing electricity from the wholesale market and selling electricity to end-users, considering the failure of network components. The proposed model is designed as a stochastic bi-level optimization problem that, at the upper-level, aims at maximizing the expected profit of the DisCo, optimal decisions on the use of resources, and prices offered to the wholesale and retail markets are adopted. Distributed generation (DG) units, battery-based storage sysetm, demand response (DR) programs, and load curtailment (LC) are the resources of the DisCo. Random failures of components are modeled by a set of scenarios. The expected energy not supplied (EENS) is used as the reliability index. The lower-level problem involves the wholesale market clearing problem, with the aim of maximizing the social welfare in which the power allocated to DisCo as well as locational marginal prices (LMPs) are calculated. The model is recast to the MPEC model and then linearized to a MILP model by KKT optimality conditions and dual theorem. Simulations show that, due to the constraints in the distribution network, the failure of distribution and sub-transmission lines reduces the strategic role of the DisCo in the wholesale market. The proposed model can used for analyzing the behavior of strategic DisCos in electricity markets under uncertainty.

Optimal Reserve Determination Considering Demand Response in the Presence of High Wind Penetration and Energy Storage Systems

Qualification of the reserve requirement of power systems in the presence of load uncertainties and renewable energy resources is one of the most important challenges of system operators. Especially, existence of wind turbines with unavoidable volatility in their generated powers makes this problem more serious. In this paper, is proposed a probabilistic method for optimal determining of the spinning and non-spinning reserves. In this method, the required optimal reserve level would be determined via simultaneously optimizing the operation cost (OC) and the expected energy not supplied (EENS) cost under security constraint unit commitment. That is, OC includes the cost of both reserve market and energy markets and EENS is computed using a piecewise linear function. The demand response program is considered to provide the reserve service from the demand side. These improve the power system reliability and also reduce the OC. Besides, energy storage systems have been included as a promising approach to diminish the uncertainties of wind power and electrical load. The method is formulated in a two-stage stochastic programming framework, where the first stage represents the day-ahead market, and the second stage deals with the real-time market. Also, a multi-step algorithm has been presented to implement the proposed model. Finally, the well-known 3-buses and 24-buses test systems would be used to verify the efficiency of proposed model.

Reliability evaluation of multi-carrier energy system with different level of demands under various weather situation

Multi-carrier systems enable the cooperation between different energy types to answer the electricity, water, heating and cooling demand together. One of the most important problems related to procuring energy for consumers is the reliability of delivered energy. This paper contributes a framework to assess the reliability of energy hub based on its elements and input energy carriers. Loss of load expectation (LOLE), loss of load probability (LOLP) and expected energy not supplied (EENS) have been employed to determine the reliability of the multi-energy carrier system in two different weather condition. The interactions between different energy carriers have been formed based on the exact model of energy storages. The calculation of the reliability assessment for energy hub has been performed by using MATLAB software. The results of the employment of the presented framework on a case study with various types of energy converters have been illustrated that the reliability of demands has been increased significantly by the use of an energy hub concept. Also, the reliability of energy hub has been imposed based on the size of components to recognize the impacts of each component on the general reliability of the system.