Economics of energy storage in a residential consumer context

With the increase of electricity tariffs and thedecreasing costs for distributed generation technologies, moreand more residential consumers are deploying local generationsystems to satisfy their electricity demand in order to reduceoverall cost. Typically, however, a mismatch between electricitygeneration and demand remains. Storage systems enableconsumers to reduce this mismatch by storing locally generatedelectricity for later consumption, instead of feeding excessgeneration into the grid. This paper analyzes the economics ofstorage installations in a residential consumer context. A linearprogram is presented to determine the optimal dispatch, andSimulated Annealing is used to identify the cost minimizingsystem configuration. The developed approach is tested for amulti-family house in Germany

Evaluation of the performance of space reduction technique using AC and DC models in Transmission Expansion problems

Transmission Expansion Planning (TEP) is anoptimization problem that has a non-convex and combinatorialsearch space so that several solution algorithms may converge tolocal optima. Therefore, many works have been proposed to solvethe TEP problem considering its relaxation or reducing its searchspace. In any case, relaxation and reduction approaches shouldnot compromise the quality of the final solution. This paper aimsat analyzing the performance of a search space technique using aConstructive Heuristic Algorithm (CHA) admitting that the TEPproblem is then solved using a Discreet Evolutionary ParticleSwarm Optimization (DEPSO). On one hand the reductionquality is performed by analyzing whether the optimal expansionroutes are included in the CHA constrained set and, on the otherhand, the relaxation quality of the DC model is analyzed bychecking if the optimal solution obtained with it violates anyconstraint using the AC model. The simulations were performedusing three different test systems. The results suggest that theproposed CHA provides very good results in reducing the TEPsearch space and that the adoption of the DC model originatesseveral violations if the full AC model is used to model theoperation of the power system

Economic evaluation of combined generation and storage solutions in low voltage Portuguese consumers

This paper presents the results that were obtained inthe scope of a consultancy study developed by INESC TEC for aPortuguese distribution network company to evaluate theinterest of installing storage devices and PV panels in LVinstallations. We conducted simulations for consumers withannual demands of 5000 kWh (Type C consumers) and 7500kWh (Type B consumers). In general, we concluded that theinstallation of storage devices is still of little economic interestgiven the current investment level and the tariffs paid to injectelectricity in the networks. The largest NPV values wereobtained when only installing PV panels in Type B consumers,the larger ones, and selling the surplus energy to the network

Simulation of the operation of hydro plants in an electricity market using Agent-Based Models

The optimization and simulation of power systemscontinues to be an area of concern for electricity companies andresearchers worldwide namely considering the development ofelectricity markets and competition in the generation activityTherefore generation companies are devoting an increasingattention to market issues justifying the development of modelsto help them preparing bidding strategies to the day-aheadmarket. In this context, agent-based models have been reportedas a complement to optimization and equilibrium models whenthe problem is too complex to be analyzed by traditionalapproaches. This paper details an Agent-Based Model for anelectricity market considering a detailed modeling for hydrostations and presents some preliminary results taking theIberian Electricity Market as an example

Multiyear and multi-criteria AC Transmission Expansion Planning model considering reliability and investment costs

One of the major concerns in Power Systems issurely related with their reliability. Long-term expansionplanning studies traditionally use the well-known deterministic"N-1" contingency criterion. However, this criterion is appliedbased on worst-case analyses and the obtained plan mayoriginate over-investments. Differently, probabilistic reliabilityapproaches can incorporate different type of uncertainties thataffect power systems. In this work, a long term multi-criteriaAC Transmission Expansion Planning model was developedconsidering two objectives - the probabilistic reliability indexExpected Energy Not Supplied (EENS) and the investment cost.The Pareto-Front associated with these two objectives wasobtained using Genetic Algorithms and the final solution wasselected using a fuzzy decision making function. This approachwas applied to the IEEE 24 Bus Test System and the resultsensure its robustness and efficiency

Simultaneous co-integration of multiple electrical storage applications in a consumer setting

In a consumer setting, storage systems can be dispatched in order to shift surplus generation to periods when a local generation deficit exists. However, the high investment cost still makes the deployment of storage unattractive. As a way to overcome this problem existing literature looking at storage installed at the grid-level suggests dispatching the storage device for multiple applications simultaneously in order to access several value streams. Therefore, in this work, a Mixed Integer Linear Program is developed in order to schedule the operation of a storage device in a consumer context for multiple objectives in parallel. Besides shifting locally generated energy in time, the peak demand seen by the electric grid is reduced and the storage device is operated to provide primary reserve control. The model is applied in a case study based on the current German situation in order to illustrate the value contribution of stacking multiple services. When pursuing multiple applications simultaneously, the revenues of storage can be increased significantly. However, the revenues are not additive due to conflicting operations which originates a revenue gap as illustrated in the paper

Evaluation of the impact of storage systems on grid electricity demand in the German context

This paper analyzes the impact of storageinstallations on grid electricity demand. Storage systems allowthe decoupling of consumption from electricity generation andtherefore have the potential to change the daily demand profileseen by the network in a significant way. This has far reachingconsequences for many stakeholders, as changes in the netdemand would for example impact electricity prices or changethe requirements for peak generation. The developed approachconsiders the installation of storage devices to increase self consumption of locally generated electricity in a residential andsmall commercial end users context as well as its application forelectricity arbitrage. Assumptions about their implementationon a system level are described and their impact on overallelectricity demand is determined considering the German case

Artificial intelligence for transmission expansion planning in Sub-Saharan Africa

Transmission networks are facing very demanding challenges in Sub-Saharan Africa: African utilities are focused on rural electrification, as the access to power is limited to 32 % of the overall population; load increase rates are very high; the connection of renewables and new bulk generation requiresinterconnection to already existing transmission grids, in some situations thousands of kilometers long; interconnectivity among Southern Africa Power Pool (SAPP) systems is very weak; the existing infra-structure requires improvement and maintenance. As a result of all these concerns, SAPP hasalready identified transmission expansion as one of the most important issues to be addressed on the next years in Southern Africa. It is also important to recognize that the connection of new generation plays an important role on interconnectivity amongst Sub-Saharan African countries, as relevant energy sources are typically located very far from the main consumers, and are often located in different countries. This is a quite different paradigm from that what is normally found in othercontinents. Huge investment is needed to implement new transmission projects; and investors have to be identified outside the region. These investors require well established technical and stable legal frameworks. Both local stakeholders and investors need suitable dynamic tools to model the expansion of the systems. On these tools one has to take into account the complexity of the system on both spaceand time dimensions. Artificial intelligence based models, like Evolutionary Particle Swarm Optimization (EPSO) either real or discrete approach, have already been tested in real transmission networks, and may be also useful to plan the future Sub-Saharan transmission network. In this scope,this paper aims at describing a mathematical model to perform long term transmission expansion studies having a multiyear nature in order to identify the most adequate expansion plan while considering a number of criteria as the investment and operation costs, the reliability of operation and the uncertainties on loads

Simultaneous co-integration of multiple electrical storage applications in a consumer setting

In a consumer setting, storage systems can be dispatched in order to shift surplus generation to periods when a local generation deficit exists. However, the high investment cost still makes the deployment of storage unattractive. As a way to overcome this problem existing literature looking at storage installed at the grid-level suggests dispatching the storage device for multiple applications simultaneously in order to access several value streams. Therefore, in this work, a Mixed Integer Linear Program is developed in order to schedule the operation of a storage device in a consumer context for multiple objectives in parallel. Besides shifting locally generated energy in time, the peak demand seen by the electric grid is reduced and the storage device is operated to provide primary reserve control. The model is applied in a case study based on the current German situation in order to illustrate the value contribution of stacking multiple services. When pursuing multiple applications simultaneously, the revenues of storage can be increased significantly. However, the revenues are not additive due to conflicting operations which originates a revenue gap as illustrated in the paper

Application of the Matlab® Linprog function to plan the short term operation of hydro stations considered as price makers

The restructuring of power systems induced newchallenges to generation companies in terms of adequatelyplanning the operation of power stations in order to maximizetheir profits. In this scope, hydro resources are becomingextremely valuable given the revenues that their operation cangenerate. In this paper we describe the application of theMatlab® Linprog optimization function to solve the Short TermHydro Scheduling Problem, HSP, admitting that some stationsare installed in the same cascade and that some of them havepumping capabilities. The optimization module to solve the HSPproblem is then integrated in an iterative process to take intoaccount the impact that the operation decisions regarding thehydro stations under analysis have on the market prices. Theupdated market prices are then used to run again the HSPproblem thus enabling considering the hydro stations as pricemakers. The developed approach is illustrated using a systembased on the Portuguese Douro River cascade that includes 9hydro stations (4 of them are pumping stations) and a totalinstalled capacity of 1485 MW